JP4321443B2 - Specific apparatus, processing system, control method for specific apparatus, control program for specific apparatus, recording medium recording control program for specific apparatus - Google Patents

Description

  The present invention accepts a characteristic value indicating the quality of a workpiece processed by any of the m processing devices from any of the n measuring devices, and adjusts the processing device or the measuring device. It is related with the specific apparatus which performs.

  Conventionally, in order to improve the production efficiency of products, for example, processing machines with multiple identical functions or processing tables with multiple identical functions are provided for each production process, and flow work from the first process to the final process A production method for producing products is used. In such a production system, a plurality of production lines are usually provided, and product processing or the like is performed in parallel through each production line.

  A plurality of measuring instruments for measuring the characteristics of the processed product in order to check whether the processed product satisfies the specified quality in the middle of each production line or in the final process ( Measuring device).

  This characteristic indicates quality such as product performance or accuracy such as the size and bonding strength of the produced product. Hereinafter, a value indicating this characteristic is referred to as a characteristic value.

  By the way, in the above-described production method, the characteristic value obtained as a measurement result by the measuring instrument may be outside the range of values that can be taken when the quality of the processed product satisfies the specified quality. As a factor in such a case, there may be a problem of adjustment of the processing table, the processing machine, or the like, or a measurement error of the measuring device itself.

  However, in order to produce a high-quality product, the processing table, processing machine, or measuring instrument so that the characteristic value measured by the measuring instrument falls within the range that can be taken when the specified quality is satisfied. It is necessary to adjust.

  Therefore, in the conventional method, when it is necessary to adjust the processing table, processing machine, or measuring instrument as described above, the product is engaged in the production work of the product according to the state of the characteristic value obtained from the measuring instrument. In particular, skilled workers identify and make adjustments on devices that have experienced problems.

  Regarding the adjustment of the measurement error of the measuring device, for example, in Patent Document 1, each measuring device measures a standard product having the same reference characteristics, and uses the measurement result to determine the measurement result of each measuring device. A calibration method for a production line measuring instrument that adjusts variations is disclosed.

Also in the case of the configuration shown in Patent Document 1, if a malfunction occurs in an apparatus other than the measuring instrument (for example, a processing machine), the skilled worker adjusts based on the state of the characteristic value measured from the measuring instrument. The target will be specified.
JP 10-132914 A (published May 22, 1998)

  However, in the above conventional method, the adjustment target is specified and adjusted depending on the empirical knowledge of the worker. Thus, since it depends on the empirical knowledge of the worker, the adjustment target cannot be immediately specified, and the problem of reducing the productivity of the product arises.

  The present invention has been made in view of the above-mentioned problems, and the object thereof is that the characteristic value measured from the processed object to be processed satisfies the specified quality of the processed object to be processed. If the specified characteristic value is outside the range of possible characteristic values, the specific device, the processing system, the control method for the specific device, the control program for the specific device, and the recording medium on which the control program for the specific device is recorded It is to provide.

  In order to solve the above-described problem, the specific apparatus according to the present invention provides a characteristic value indicating the quality of a workpiece processed by any one of the m processing apparatuses, as one of the n measuring apparatuses. Is an identification device that identifies an object to be adjusted, wherein m and n are different natural numbers from each other, and based on the characteristic value received from the measurement device, the processed object to be processed satisfies a specified quality. A determination means for determining whether or not the processing object processed by the determination means does not satisfy the specified quality, the processed object processed satisfies the specified quality If a characteristic value that falls outside the range of possible characteristic values is an abnormal characteristic value, a specification that identifies the adjustment target based on whether the abnormal characteristic value appears in m cycles or n cycles Characterized in that it comprises a stage.

  According to the above configuration, since the specifying device includes the determination unit, it is possible to determine whether or not the quality of the processed object that has been processed satisfies a specified quality.

  In addition, the said processing apparatus is an apparatus concerned when processing with respect to processing target objects, such as a processing machine and a processing stand, for example.

  By the way, as a case where it is determined that the quality of the processed object processed by the determination means does not satisfy the specified quality, for example, when the processing apparatus is not normally operated, or the measuring apparatus is operated normally. The case where it is not movable is mentioned.

  For example, when the processing apparatus is not moving normally, the characteristic value of the processing object processed by the processing apparatus is outside the range of characteristic values that can be taken when the specified quality is satisfied. That is, when any one of the m processing apparatuses does not move normally, the characteristic value received from the measuring apparatus becomes a value outside the above range in m cycles.

  On the other hand, when the measuring device is not moving normally, the characteristic value measured by the measuring device falls outside the range of characteristic values that can be taken when the specified quality is satisfied. That is, when any one of the n measured values is not normally moved, the characteristic value received from the measuring device becomes a value out of the above range at a cycle of n.

  Therefore, the specifying means determines whether the adjustment target is based on whether the appearance period of the characteristic value that is outside the range of characteristic values that can be taken when the specified quality is satisfied is m periods or n periods. Whether it is a processing device or a measuring device can be specified.

  As described above, since the specifying device according to the present invention includes the specifying means, the adjustment target is specified based on the appearance period of the characteristic value that is out of the range of characteristic values that can be taken when the specified quality is satisfied. can do. For this reason, in the specifying apparatus according to the present invention, it is not necessary to manually perform troublesome operations such as setting adjustment of the processing apparatus or the measuring apparatus, and to determine which apparatus has an abnormality and specify the adjustment target.

  That is, the specifying device according to the present invention can efficiently specify the adjustment target without changing the setting of the processing device or the measuring device.

  Therefore, the specific device according to the present invention has a characteristic value measured from the processed object to be processed is outside the range of characteristic values that can be taken when the processed object to be processed satisfies the specified quality. There is an effect that the adjustment target can be efficiently specified.

  In the above-described configuration, the specific device according to the present invention stores the characteristic value received from the measuring device in association with the order in which the workpiece having the characteristic value is processed, Period detecting means for detecting the periodicity of the abnormal characteristic value indicating whether the abnormal characteristic value appears in m cycles or n cycles based on the characteristic value stored in the storage device, The specifying unit may be configured to specify the adjustment target based on the detection result by the period detecting unit.

  According to the above configuration, the characteristic value received from the measuring device can be stored in the storage device in association with the order in which the object to be processed having the characteristic value is processed.

  For this reason, the period detection means is based on the characteristic value stored in the storage device, and the characteristic value outside the range (non-normal characteristic value) generated when the processing device or the measurement device is not normally operated. The appearance period can be detected.

  Therefore, the specifying means can efficiently specify the adjustment target based on the result detected by the period detecting means.

  Further, in the configuration described above, the specifying device according to the present invention is a calculation unit that calculates a statistical characteristic of the characteristic value related to the periodicity of the abnormal characteristic value based on the characteristic value stored in the storage device. And the period detection means determines whether to detect the m periods or the n periods among the periodicity of the abnormal characteristic value to be detected based on the statistical feature calculated by the calculation means. It is preferable that it is comprised.

  According to the above configuration, based on the statistical feature calculated by the calculating means, the period detecting means determines whether to detect m periods or n periods out of the periodicity of the abnormal characteristic value to be detected. Can be determined.

  Thus, since the period detection means can determine the periodicity of the abnormal characteristic value to be detected based on the statistical feature, the periodicity can be efficiently detected.

  Therefore, the specifying device according to the present invention can efficiently specify the adjustment target because the period detecting unit can efficiently detect the periodicity.

  Further, in the specific device according to the present invention, in the configuration described above, the characteristic value stored in the storage device is further stored in association with the measurement device number assigned to the measurement device that measured the characteristic value. The calculation means divides a range of possible values of the characteristic value into predetermined sections based on the characteristic values stored in the storage device, and features of the frequency distribution information of the characteristic values included in the respective ranges of the sections A distribution feature calculation unit that calculates distribution feature information indicating the individual failure rate, and an individual failure rate calculation unit that calculates an individual failure rate that is a ratio of an abnormal characteristic value in each of the characteristic values measured for each of the measurement devices. There may be.

  According to the above configuration, since the distribution feature calculation means is provided, the feature of the frequency distribution information of the characteristic value can be calculated. Note that. Here, the frequency distribution information of the characteristic value is, for example, a histogram indicating the frequency distribution state of the characteristic value. The distribution feature information is the distribution feature of the frequency of the characteristic value appearing in the histogram, and is, for example, the number of sections whose frequency is larger than the frequency of the characteristic value belonging to the preceding and following sections.

  For example, when any one of the m processing devices is not normally movable, the histogram based on the characteristic value of the processing object processed by any one of the processing devices, Two of the above sections appear. For this reason, it can be said that there is a high possibility of an abnormal characteristic value in m cycles when this distribution feature information appears in two sections. Therefore, when the distribution feature information appears in two sections, the period detecting means may detect whether or not the abnormal characteristic value appears in m periods.

  Moreover, since the specific apparatus according to the present invention includes the individual defect rate calculation means, it is possible to calculate the ratio of the abnormal characteristic value in each characteristic value measured by each measuring apparatus.

  For example, when any one of the n measuring devices is not normally moving, any one of the ratios of the abnormal characteristic values calculated by the individual defect rate calculating means becomes large.

  For this reason, when any one of the ratios of the abnormal characteristic values calculated by the individual defect rate calculation means is large, it is highly likely that any one of the n measuring devices is not operating normally. I can say that. Therefore, when any one of the ratios of the abnormal characteristic values increases, the period detecting means may detect whether or not the abnormal characteristic values appear in n periods.

  As described above, in the specific apparatus according to the present invention, the period detection unit can efficiently detect the periodicity of the abnormal characteristic value.

  Therefore, the specific apparatus according to the present invention has a characteristic value measured from the processed object to be processed is outside the range of characteristic values that can be taken when the processed object to be processed satisfies the specified quality. Therefore, the adjustment target can be identified efficiently.

  Further, the specifying device according to the present invention, in the configuration described above, when the processing device is specified as an adjustment target by the specifying means, changing means for changing a set value that defines the operation of the processing device, Change instruction means for instructing the change means to change the set value so that the frequency distribution information approaches the frequency distribution information based on the characteristic value of the processed object that satisfies the specified quality. Preferably, the changing means is configured to change any set value of the m processing apparatuses in accordance with a change instruction from the change instruction means.

  Further, in the specific apparatus according to the present invention, in the configuration described above, the change instructing unit includes frequency distribution information based on a post-change characteristic value of a processing target processed after the set value is changed by the changing unit. However, it may be configured to instruct the change means to change the set value until it approaches frequency distribution information based on a characteristic value obtained from a workpiece that satisfies the specified quality.

  According to the above configuration, since the changing unit is provided, when the processing unit is specified as an adjustment target by the specifying unit, the set value of the processing unit can be changed. The set value is a value for defining the operation of the processing apparatus. By changing the set value, the quality of the processing object processed by the processing apparatus changes. That is, by changing this set value, the characteristic value of the processed object to be processed changes.

  Further, since the change instruction means is provided, the set value is set so that the frequency distribution information of the measured characteristic value approaches the frequency distribution information of the characteristic value of the processed object that satisfies the specified quality. Can be instructed to change means. This change instruction is given to the changing means until the frequency distribution based on the post-change characteristic value approaches the frequency distribution information based on the characteristic value obtained from the workpiece that satisfies the specified quality.

  For this reason, the changing means can change the set value of any one of the m processing apparatuses so that a processing object that is processed by the processing apparatus and that satisfies the specified quality is obtained. .

  Therefore, in the specific device according to the present invention, the characteristic value measured from the processed object to be processed is outside the range of characteristic values that can be taken when the processed object to be processed satisfies the specified quality. The adjustment target can be efficiently identified.

  Furthermore, the adjustment target is adjusted so that the characteristic value measured from the processed object to be processed is within the range of characteristic values that can be taken when the processed object satisfies the specified quality. Can do.

  In the above-described configuration, the specifying device according to the present invention preferably further includes output means for outputting information indicating the adjustment target specified by the specifying means.

  According to the above configuration, since the output unit is provided, it is possible to notify an operator or the like who is engaged in the processing of the processing target object of the adjustment target.

  As described above, since the worker can easily know the adjustment target, any one of the m processing devices or any one of the n measuring devices is not normally movable. Even so, it is possible to quickly adjust the processing apparatus or the measuring apparatus that requires adjustment.

  Further, in the above-described configuration, the specific apparatus according to the present invention has a relationship between the characteristic values measured by the measuring apparatus and the order in which the characteristic values are processed for each product corresponding to the characteristic values. The data shown is regarded as time-series data and corresponds to a specific period in which the sum of spectrum values when the time-series data is frequency-converted, a value indicating the degree of variation of the entire characteristic value, and an abnormal characteristic value appears. Based on the value of the spectrum in the frequency range, further includes a variation degree calculating means for calculating a variation amount of the variation degree of the characteristic value before and after adjustment of the adjustment target, and the output means is calculated by the variation degree calculating means. It is preferable that the information indicating the variation amount of the variation degree is output.

  According to the above configuration, since the variation degree calculating unit is provided, it is possible to calculate the amount of change in the variation degree of the characteristic value before and after the adjustment of the adjustment target. Further, since the output means outputs the result calculated by the variation degree calculating means, for example, the worker knows the change in the degree of variation in the characteristic value before and after the adjustment of the adjustment target based on the output result by the output means. Can do.

  Therefore, since the above-mentioned workers and the like can know how much the variation degree of the characteristic value is improved by adjusting the device specified as the adjustment target, adjustment is performed on the device specified as the adjustment target by the specifying means. It can be determined whether or not to do so.

  Note that the change amount of the variation degree of the specific value before and after the adjustment of the adjustment target can be calculated as follows, for example.

  That is, when the frequency obtained as a result of computing the time series data by FFT is considered as a sine wave, the FFT power spectrum obtained from the computation result by FFT corresponds to the square of the amplitude of the frequency component of each period.

  For this reason, the sum of the FFT power spectrum is substantially proportional to the square of the standard deviation of the time series data. Therefore, the following relationship is established.

P_all = K (σ_all) ² (a)
(P_all is the sum of the FFT power spectrum before adjustment of the device specified as the adjustment target)
(K is an arbitrary constant)
(Σ_all is the overall standard deviation before adjustment of the device specified as the adjustment target)
Here, assuming that the device specified by the specifying means as the adjustment target is completely adjusted, the amount of decrease in the variation in the characteristic value at this time, that is, the standard deviation caused by adjusting the adjustment target The decrease amount σ3 of can be expressed as follows.

P3 = K (σ3) ² (b)
(P3 is the value of the FFT power spectrum at a specific frequency at which an abnormal characteristic value appears)
Here, when σ3 is solved from the relationship of (a) and (b) above, the amount of change in the degree of variation of the specific value before and after adjustment can be obtained (σ3 = σ_all * √ (P3 / P_all). (C)).

  Further, in the above-described configuration, the specific device according to the present invention has a characteristic value variation degree determined that the storage device does not need to adjust the adjustment target with respect to the characteristic value measured by the measurement device. The variation tolerance information is further stored, and the variation tolerance information stored in the storage device, the value indicating the degree of variation of the entire characteristic value measured by the measurement device, the characteristic value, and the characteristic value, respectively. Data indicating the relationship with the order in which the characteristic values were processed for each corresponding product is regarded as time-series data, and the above identification is performed based on the sum of spectrum values when the time-series data is subjected to frequency conversion. When a threshold for determining whether or not the adjustment target specified by the means needs to be adjusted is obtained, and the time-series data is subjected to frequency conversion And an adjustment execution determination unit that compares the magnitude of the spectrum at a specific frequency at which an abnormal characteristic value appears in the apparatus with the threshold value and determines whether or not to adjust the device specified as the adjustment target by the specifying unit. You may be comprised so that it may be.

  The variation tolerance information is a value determined according to quality accuracy required for a product to be manufactured, and is a characteristic value measured before and after adjustment target specified by the specifying unit. It shows the amount of change in the degree of variation. The variation tolerance information is set to an appropriate value by the user and stored in advance in a storage device.

  According to the above configuration, since the adjustment execution determination unit is provided, it is possible to determine whether or not adjustment to the adjustment target is necessary. In other words, it is automatically determined whether or not to adjust the device specified as the adjustment target, considering what happens to the variation in the characteristic value variation by adjusting the device specified as the adjustment target. can do.

  Note that the threshold value for determining whether or not the adjustment target specified by the specifying unit needs to be adjusted can be obtained as follows, for example.

  That is, as described above, the value indicating the degree of variation of the entire characteristic value (standard deviation), the characteristic value measured by the measuring device, and the order in which the product having the characteristic value is processed and the characteristic value is measured Is a time-series data, and the relationship between the entire power spectrum when frequency conversion is performed using FFT or the like and the power spectrum at a frequency corresponding to a specific period in which an abnormal characteristic value occurs is “σ3 = σ_all * √ (P3 / P_all) (c) ”.

Here, the value of the variation allowable information is γ3, and P3 (the value of the power spectrum at the frequency corresponding to the specific cycle in which the abnormal characteristic value occurs) is Q3 as a threshold value for whether or not to adjust the adjustment target. , Solving equation (c) for Q3,
Q3 = P_all * (γ3 / σ_all) ² (d) is established.
The threshold value Q3 calculated here is, for example, the FFT power spectrum in which the variation degree of the characteristic value is allowed as a range in which adjustment of the adjustment target need not be performed.

  Here, the adjustment execution determination means compares the value of Q3 with the power spectrum obtained by FFT or the like with respect to the actually measured characteristic value, and determines whether or not the adjustment target needs to be adjusted. Can be determined.

  Moreover, in order to solve the above-described problem, the processing system according to the present invention includes any one of the above-described specific device, m processing devices that perform processing of a processing object, and the processing device. And n measuring devices for measuring characteristic values indicating the quality of the processed workpiece.

  Since the processing system according to the present invention includes the above-described specific device, if it is determined that the processed object does not satisfy the specified quality based on the measured characteristic value, the adjustment target Can be identified efficiently.

  Further, the adjustment target is adjusted so that the characteristic value measured from the processed object to be processed falls within the range of characteristic values that can be taken when the processed object to be processed satisfies the specified quality. I can do this.

  In addition, in order to solve the above-described problem, a control method for a specific device according to the present invention is a control method for a specific device that receives an adjustment from any of n measuring devices and specifies an adjustment target. n is a natural number different from each other, and based on the characteristic value received from the measuring device, a determination step for determining whether or not the processed object to be processed satisfies a specified quality, and the processing step If it is determined that the processed object does not satisfy the specified quality, a characteristic value that is outside the range of characteristic values that can be taken when the processed object that has been processed satisfies the specified quality is abnormal. The characteristic value includes a specific step of specifying an adjustment target based on whether the abnormal characteristic value appears in m cycles or n cycles.

  As described above, the control method of the specific device according to the present invention efficiently selects the adjustment target when it is determined that the processed object does not satisfy the specified quality based on the measured characteristic value. There is an effect that it can be specified.

  In addition, each means with which the said specific apparatus is provided may be implement | achieved by a computer, In this case, the control program of the detection apparatus which implement | achieves the said detection apparatus with a computer by operating a computer as said each means is recorded. Such computer-readable recording media also fall within the scope of the present invention.

  As described above, the specific apparatus according to the present invention receives and adjusts the characteristic value indicating the quality of the workpiece processed by any of the m processing apparatuses from any of the n measuring apparatuses. A specific device for specifying an object, wherein m and n are different natural numbers from each other, and based on a characteristic value received from the measurement device, whether or not the processed object to be processed satisfies a specified quality. It can be determined when the determination means and the processing object processed by the determination means are determined not to satisfy the prescribed quality, and the processed object to be processed satisfies the prescribed quality. A characteristic value outside the range of the characteristic value is set as an abnormal normal value, and a specific unit for specifying an adjustment target is provided based on whether the abnormal characteristic value appears in m cycles or n cycles. The And butterflies.

  Therefore, the specifying means determines whether the adjustment target is based on whether the appearance period of the characteristic value that is outside the range of characteristic values that can be taken when the specified quality is satisfied is m periods or n periods. Whether it is a processing device or a measuring device can be specified.

  Therefore, the specific device according to the present invention has a characteristic value measured from the processed object to be processed is outside the range of characteristic values that can be taken when the processed object to be processed satisfies the specified quality. There is an effect that the adjustment target can be efficiently specified.

  In addition, as described above, the processing system according to the present invention is processed by any one of the above-described specific device, m processing devices that perform processing on the processing object, and the processing device. And n measuring devices that measure characteristic values indicating the quality of the workpiece.

  Since the processing system according to the present invention includes the above-described specific device, if it is determined that the processed object does not satisfy the specified quality based on the measured characteristic value, the adjustment target Can be identified efficiently.

  Further, the adjustment target is adjusted so that the characteristic value measured from the processed object to be processed falls within the range of characteristic values that can be taken when the processed object to be processed satisfies the specified quality. There is an effect that it can be done.

  In addition, as described above, the control method for the specific device according to the present invention is a control method for the specific device that accepts from any of the n measuring devices and specifies the adjustment target, and the above m and n are different from each other. It is a natural number, and based on the characteristic value received from the measuring device, a determination step for determining whether or not the processed object to be processed satisfies a specified quality, and the processing target processed by the determination step When it is determined that the product does not satisfy the specified quality, a characteristic value that is outside the range of characteristic values that can be taken when the processed object that has been processed satisfies the specified quality is set as an abnormal characteristic value. And a specific step of specifying an adjustment target based on whether the abnormal characteristic value appears in m cycles or n cycles.

  As described above, the control method of the specific device according to the present invention efficiently selects the adjustment target when it is determined that the processed object does not satisfy the specified quality based on the measured characteristic value. There is an effect that it can be specified.

  An embodiment of the present invention will be described below with reference to FIGS. That is, the manufacturing line system (processing system) 100 according to the present embodiment converts a product (processing object) to be processed as shown in FIG. 1 into two processing machines (processing apparatus). It is a system which performs processing by any one of 5a-5b. The production line system 100 can check the quality of the processed product by any one of the three measuring devices (measuring devices) 6a to 6c. That is, the production line system 100 can process two products in parallel with each of the two processing machines 5a to 5b, and the characteristic values of the products processed with three measuring instruments 6a to 6c. Can be measured in parallel.

  FIG. 1 shows an embodiment of the present invention, and is a block diagram showing a main configuration of a production line system.

  As shown in FIG. 1, the production line system 100 according to the present embodiment includes a product insertion port 1, a conveyor belt 8, processing machines (processing devices) 5a to 5b, processing tables (processing devices) 3a to 3l, and turns. A table 4, measuring instruments (measuring devices) 6 a to 6 c, and an adjusting device 7 are provided.

  The product input port 1 is used by an operator who operates the production line system 100 according to the present embodiment to process a product. And the thrown-in product is conveyed toward the process bases 3a-3l.

  The conveyor belt 8 conveys the product. Specifically, the conveyor belt 8 conveys the product put into the product insertion port 1 to the processing bases 3a to 3l, or processes the processed product. Transport from the bases 3a to 3l to the measuring instruments 6a to 6c. In addition, when further processing steps of the product are required, the conveyor belt 8 is provided with a device for executing the next processing step on the product subjected to the measurement processing by the measuring devices 6a to 6c. Carry to the place. In addition, the conveyance direction of the workpiece | work of the conveyance belt 8 is a direction of the arrow a shown in FIG.

  Further, when the characteristic value 31 measured by each of the measuring devices 6a to 6c is outside the range of values that can be taken when the processed product satisfies the specified quality, the conveying belt 8 has the characteristic value 31. The product having the is moved so as to be removed from the production line as defective products.

  The said processing bases 3a-3l fix a product in order to be able to process with the processing machines 5a-5b. In the production line system 100 according to the present embodiment, twelve processing tables 3a to 3l are respectively provided along the outer periphery of the circular turntable 4 as shown in FIG. And according to rotation of the turntable 4, it moves to the direction of arrow b (clockwise direction).

  That is, the products conveyed by the conveyor belt 8 are installed one by one on each of the processing tables 3a to 3l. In addition, when the product is installed on any one of the processing tables 3a to 3l, the processing table on which the product is installed corresponds to one processing table in the direction of the arrow b. Just move. The newly transported product is then placed on the processing table that has come to the position of the transport belt 8.

  The turntable 4 rotates in the direction of the arrow b to move the processing bases 3a to 3l to a place where the processing machines 5a to 5b are processed, or the processed products to the measuring instruments 6a to 6c. It moves to the position of the conveyance belt 8 to convey.

  That is, the turntable 4 rotates so that the products conveyed by the conveying belt 8 can be installed one by one on each of the processing tables 3a to 3l and the products can be processed by the processing machines 5a to 5b. . Furthermore, the turntable 4 moves the product from the installation location of the processing machines 5a to 5b to the location of the conveyor belt 8 in order to place each processed product on the conveyor belt 8 that conveys the processed products to the measuring instruments 6a to 6c. Rotate to let

  The rotation speed of the turntable 4 is a speed that satisfies the following condition. That is, this rotational speed is a speed at which each product conveyed by the conveyor belt 8 can be installed on each of the processing tables 3a to 3l. The rotational speed is a speed at which each of the processing machines 5a to 5b can perform processing on each of the installed products. Furthermore, this rotational speed is adjusted to a speed at which the processed product can be moved to the conveyor belt 8 that conveys the processed product to the measuring instruments 6a to 6c.

  Each of the processing machines 5a to 5b performs predetermined processing on each of the products installed on the processing bases 3a to 3l. In the production line system 100 according to the present embodiment, as shown in FIG. 1, two processing machines 5a to 5b are provided, and these processing machines 5a to 5b are simultaneously arranged in front of the processing machines 5a to 5b. The processing for each product placed in is executed.

  That is, in the production line system 100 according to the present embodiment, two products can be simultaneously processed by two processing machines 5a to 5b.

  Each of the measuring instruments 6a to 6c measures a characteristic value 31 of each product in order to check the quality of the processed product. In the production line system 100 according to the present embodiment, as shown in FIG. 1, three measuring devices 6a to 6c are respectively provided, and each of these measuring devices 6a to 6c has a characteristic simultaneously with respect to a conveyed product. The value 31 is measured. That is, in the production line system 100 according to the present embodiment, the characteristic values 31 of the three products can be measured at once by the three measuring devices 6a to 6c.

  Further, a channel number is assigned to each of the measuring devices 6a to 6c so that the measuring device 6a to 6c can identify which characteristic value 31 is measured.

  Then, each of the measuring instruments 6 a to 6 c transmits the channel number assigned to the own apparatus together with the measured characteristic value 31 to the adjusting apparatus 7.

  The adjustment device 7 estimates the adjustment target based on the characteristic value 31 of each product measured by each of the measuring instruments 6a to 6c, instructs the adjustment to the adjustment target, or changes the set value of the adjustment target. It is something to do.

  In the production line system 100 according to the present embodiment, the adjustment target is any one of the processing machines 5a to 5b, any one of the processing tables 3a to 3l, or any of the measuring instruments 6a to 6c. The detailed configuration of the adjusting device 7 will be described below.

(Configuration of adjusting device)
As shown in FIG. 1, the adjustment device 7 according to the present embodiment includes an information storage unit 12 (storage device), a reception unit 11, a totaling unit 13, a determination unit (determination means) 21, a histogram feature detection unit (distribution feature). (Calculation means) 15, defect rate calculation unit (individual defect rate calculation means) 14, period information detection unit (period detection unit) 16, abnormality estimation unit (specification unit) 17, instruction output unit (output unit) 19, adjustment unit ( A change instruction unit) 18, a state change detection unit 20, and a setting unit (change unit) 22.

  The information storage unit 12 is a readable / writable recording medium, and can be realized by, for example, a flash EEPROM (Electrically Erasable Programmable Read Only Memory). In the information storage unit 12, a characteristic value 31 received by the receiving unit 11 and a device initial value 32 which is a set value set in advance in each of the processing machines 5a to 5b are recorded.

  The set value is a value for defining the operation of each of the processing machines 5a to 5b, and the processing result of the product changes by changing the set value. For this reason, when this set value is changed, the characteristic value 31 of the product processed by the processing machine a or the processing machine b whose setting value has been changed is changed.

  In addition, although not shown in FIG. 1, predetermined threshold information used for performing an abnormal factor estimation process described later is also recorded in the information storage unit 12.

  Although not shown, the information storage unit 12 also records a warning flag used when the abnormality estimation unit 17 performs an abnormality factor estimation process described later.

  Further, in the information storage unit 12, although not shown, histogram information and setting values based on the characteristic values of the products processed by the processing machine 5 a or the processing machine 5 b before the setting values are changed are changed. The histogram information based on the characteristic value of the product processed by the processing machine 5a or the processing machine 5b is recorded. The information of the histogram is information necessary for the setting value adjustment process described later for changing the setting value of any of the processing machines 5a to 5b.

  The characteristic value 31, the device initial value 32, the threshold information, the warning flag, and the histogram information may be recorded in one information storage unit 12, or a memory in which each value is individually provided. Or may be recorded on a recording medium.

  Furthermore, when the adjustment device 7 according to the present embodiment can communicate with other external devices through a communication network, the above-described information may be acquired from the external device.

  The receiving unit 11 receives the measured product characteristic value 31 from each of the measuring devices 6a to 6c. The receiving unit 11 receives each characteristic value 31 as a channel number assigned to each of the measuring devices 6a to 6c that are transmission destinations of the characteristic value 31, and a measurement time measured by each of the measuring devices 6a to 6c. Are stored in the information storage unit 12 in association with each other.

  The aggregating unit 13 reads the characteristic value 31 from the information storage unit 12 and aggregates the characteristic value 31 for each channel number of each measuring instrument 6a to 6c, or totalizes the measured characteristic value 31 of the entire product. Is. That is, the totaling unit 13 calculates the number of products and the number of defective products based on the characteristic value 31 totaled for each channel number of each measuring instrument 6a to 6c, and creates a histogram. Also, the number of measured products and the number of defective products are calculated for the entire measured characteristic value 31, and a histogram is created.

  The determination unit 21 also determines whether or not to perform a process of estimating an abnormality factor based on the characteristic values 31 totalized by the totalization unit 13. That is, the determination unit 21 confirms the presence / absence of the characteristic value 31 that is outside the possible range of the characteristic value of the product satisfying the specified quality (hereinafter referred to as the specified range) based on the characteristic value 31. Then, it is determined whether or not to perform the process of estimating the abnormality factor. Details regarding the process of estimating the abnormality factor will be described later.

  In this determination, the determination unit 21 may determine to perform the process of estimating the abnormality factor if there is even one characteristic value 31 that is outside the specified range. Further, when the presence of the characteristic value 31 that falls outside the above specified range is recognized at a certain rate, it may be determined that the process of estimating the abnormality factor is performed. This criterion is preferably determined according to the quality required for the processed product.

  Here, the number of measured products is the number of products for which the characteristic value 31 is measured by the measuring devices 6a to 6c in a predetermined period. For example, assume that 300 products have been processed within a predetermined period. In this case, the characteristic value 31 of the processed product is measured three by three at the same time by the three measuring devices 6a to 6c. Therefore, the number of measurement products for each of the measuring instruments 6a to 6c is 100. The number of measurement products obtained from all the measuring instruments 6a to 6c is 300.

  Further, the number of defective products is the number of products for which the measured characteristic value 31 is recognized as abnormal. That is, in the production line system 100 according to the present embodiment, a range of characteristic values obtained when a processed product satisfies a specified quality, that is, a specified range is determined in advance. Therefore, in the measured characteristic value 31, the number of products corresponding to the characteristic value 31 outside the specified range is the number of defective products.

  The histogram indicates the distribution of the frequency (frequency n) of the product characteristic value 31 measured by any of the measuring instruments 6a to 6c. That is, as shown in FIG. 2, the range that can be taken as the characteristic value 31 is divided into a plurality of sections (y), and the frequency (frequency n) of the characteristic value 31 included in each of the divided sections is shown. .

  When the determination unit 21 determines that there is a characteristic value 31 outside the specified range, the histogram feature detection unit 15 detects the distribution feature of the histogram based on the histogram created by the aggregation unit 13.

  For example, when all the products are normally processed by any of the processing machines 3a to 3l and the measurement processing of the characteristic value 31 is normally performed on each of the processed products, that is, in a normal state, FIG. As shown in FIG. 2 (a), all the characteristic values 31 are in the range between α and β. The range between α and β indicates the specified range, where α indicates the lower limit value of the specified range and β indicates the upper limit value of the specified range.

  In the histogram distribution created by totaling all the characteristic values 31, there is only one section (point A in FIG. 2) in which the number of products is larger than the preceding and following sections. That is, normally, when the processed product satisfies the specified quality, the frequency becomes the largest near the center value of the specified range α-β. Hereinafter, a section where the number of products is larger than the preceding and following sections in the histogram distribution, such as point A, is referred to as a peak.

On the other hand, when the product is not processed normally or the characteristic value 31 of the processed product is not accurately measured, that is, in an abnormal state, the histogram distribution is shown in FIG. As shown. That is, in the case of the abnormal state, as shown in FIG. 2B, a product having a plurality of peaks (peak A ₁ , peak A ₂ ) or a characteristic value 31 outside the specified range α-β is obtained. Or exist.

  This is because, for example, when either the processing machine 5a or the processing machine 5b is not moving normally, the characteristic value 31 of the product processed by the processing machine that is not moving normally is a specified range α-β. The frequency of the section deviating from the center value of is the largest. For this reason, a histogram formed based on the characteristic value 31 of the product processed normally by the processing machine, and a histogram formed based on the characteristic value 31 of the product processed by the processing machine not operating normally. Then, the sections where the peaks appear do not coincide with each other and are shifted sections.

  Therefore, in the case of an abnormal state as shown in FIG. 2B, two peaks appear in the histogram.

  Thus, the created histogram has a characteristic distribution depending on whether it is the product characteristic value 31 in the normal state or the product characteristic value 31 in the abnormal state.

  Therefore, the histogram feature detection unit 15 analyzes the number of peaks described above based on the histogram created by the totalization unit 13 in response to an instruction from the determination unit 21. Then, the histogram feature detection unit 15 transmits the analyzed number of peaks to the abnormality estimation unit 17.

  When the determination unit 21 determines that there is a characteristic value 31 outside the specified range, the defect rate calculation unit 14 calculates a defect rate of the measured characteristic value 31. That is, the defect rate calculation unit 14 calculates the defect rates of the characteristic values 31 measured by the measuring instruments 6a to 6c and all the measured defect rates.

In addition, the said defective rate calculating part 14 can calculate the said defective rate by performing the calculation shown to Numerical formula (1) shown below with respect to all the characteristic values 31 and the characteristic value 31 for every measuring apparatus. .
NGRation = (N_i−OK_Num_i) / N_i (1)
NGRation; defective rate OK_Num_i; number of characteristic values 31 within the specified range in the measurement result by the measuring device of channel number i, or number of characteristic values 31 within the expected range of the measurement results by all the measuring devices N_i; measurement of channel number i The number of characteristic values 31 measured by the measuring device, or the number of characteristic values 31 measured by all the measuring devices, and the defect rate calculation unit 14 calculates the defect rate obtained by performing the calculation according to the above equation (1). The periodic information detection unit 16 transmitted to the abnormality estimation unit 17 examines the relationship between the order of the processed and measured products and the characteristic values 31 of the products. More specifically, a mathematical expression to be described later is calculated to detect periodicity generated in the relationship between the order of the processed and measured products and the characteristic value 31 of the products.

  By the way, in the production line system 100 according to the present embodiment, the products are always conveyed in the order of the products input from the product input port 1. In addition, the three measuring instruments 6a to 6c are configured so that the product in which the order in which they are put is measured in the order of the measuring instrument 6a, the measuring instrument 6b, and the measuring instrument 6c is measured.

  As described above, in the information storage unit 12, the channel number assigned to each of the measuring instruments 6 a to 6 c and the date and time when the characteristic value 31 is measured are associated with the measured characteristic value 31. It is recorded.

  Therefore, by referring to the date and time and the channel numbers of the measuring instruments 6a to 6c, the order of the characteristic values 31 of the processed products can be grasped. Channel number 1 is assigned to measuring instrument 6a, channel number 2 is assigned to measuring instrument 6b, and channel number 3 is assigned to measuring instrument 6c.

  That is, in the production line system 100 according to the present embodiment, the order of the products to be transported, the processing machines 5a to 5b for processing the products, the processing bases 3a to 3l for fixing the products to be processed, and the processing The following relationship is established between the measuring devices 6a to 6c that measure the characteristic values of the manufactured products.

Products processed and measured for characteristic values; OB ₁ , OB ₂ , OB ₃ , ...
Processing machine 5a, processing machine 5b; W ₁ , W ₂
Work table _{3a~3l; P 1, P 2,} P 3, ... P 12
Instrument _{6a~6c; M 1, M 2,} M 3
The order of products OB ₁ , OB ₂ , OB ₃ ,... Processed by the processing machines W ₁ and W ₂ is as follows:
W ₁ ; OB ₁ , OB _{(x + 1)} , OB _{(2x + 1)} , ...
W ₂ ; OB ₂ , OB _{(x + 2)} , OB _{(2x + 2)} , ...
It becomes.
In addition, the order of the products OB ₁ , OB ₂ , OB ₃ ,... That the measuring instruments M ₁ , M ₂ , M ₃ measure specific values is as follows:
M ₁ ; OB ₁ , OB _{(y + 1)} , OB _{(2y + 1)} , ...
M ₂ ; OB ₂ , OB _{(y + 2)} , OB _{(2y + 2)} , ...
M ₃ ; OB ₃ , OB _{(y + 3)} , OB _{(2y + 3)} , ...
It becomes.
Similarly, the order of the products OB ₁ , OB ₂ , OB ₃ ... Fixed by the processing tables 3a to 3l is as follows.
P ₁ ; OB ₁ , OB _{(z + 1)} , OB _{(2z + 1)} , ...
P ₂ ; OB ₂ , OB _{(z + 2)} , OB _{(2z + 2)} , ...
P ₃ ; OB ₂ , OB _{(z + 3)} , OB _{(2z + 3)} , ...
...
P ₁₂ ; OB ₁₂ , OB _{(z + 1)} , OB _{(2z + 12)} , ...
It becomes.

  Therefore, in the predetermined number of measured products, the horizontal axis represents the order in which processed and measured products are conveyed, and the vertical axis represents the natural number value obtained by normalizing the characteristic value 31 of each product corresponding to this order. When the measured characteristic values 31 are plotted, they are as shown in FIGS. 3 (a) to 3 (d).

  FIG. 3A to FIG. 3D are diagrams showing the relationship between the conveyance order of products that are processed and the characteristic values are measured, and the characteristic values 31 of the products.

  FIG. 3A shows the relationship between the conveyance order of products that are processed and the characteristic values are measured in the normal state, and the characteristic values 31 of the products.

  FIG. 3 (b) shows the conveyance order of the product to be processed and the characteristic value measured when any of the processing machines 5a to 5b is not moving normally, and the characteristic value 31 of the product. The relationship is shown.

  FIG. 3 (c) shows the order of conveyance of products that are processed and the characteristic values are measured when any one of the measuring instruments 6a to 6c is not moving normally, and the characteristics of the products. The relationship with the value 31 is shown.

  Further, FIG. 3D shows the order of conveyance of products processed and measured for characteristic values, and the characteristics of the products when any one of the processing tables 3a to 3l is not moving normally. The relationship with the value 31 is shown.

  For example, when all 100 products are processed normally and the characteristic value 31 is measured normally, the value indicating the characteristic value 31 of the product from 1 to 100 as shown in FIG. It will be within the specified range. In this case, there is no particular periodicity in the relationship between the order of processed products and the characteristic value 31 of the products.

  On the other hand, when any one of the processing machines 5a to 5b is not moving normally, as shown in FIG. 3B, every other measured characteristic value 31 defines a value indicating the characteristic value 31 of the product. Out of range. That is, in a predetermined number of measured products, a characteristic value 31 outside the specified range is generated in two cycles.

  Further, when any one of the measuring instruments 6a to 6c is not normally moved, every two characteristic values 31 measured are out of the specified range as shown in FIG. That is, in a predetermined number of measured products, characteristic values 31 outside the specified range are generated in a cycle of three.

  In addition, when any one of the processing tables 3a to 3l is not normally moved, the measured characteristic values 31 are out of the specified range every 11 as shown in FIG. That is, in a predetermined number of measured products, characteristic values 31 outside the specified range are generated in a cycle of 12 pieces.

  As described above, when any one of the processing machines 5a to 5b, any one of the measuring instruments 6a to 6c, and any one of the processing tables 3a to 3l is not normally movable, the processed product is measured. And a characteristic value 31 of the product, a certain periodicity appears.

  In each of FIGS. 3B to 3D described above, the case where the characteristic values 31 measured every other, every second, or every eleven is outside the specified range has been described. However, the periodicity in which the characteristic value 31 outside the specified range occurs is not limited to this.

  That is, this periodicity is determined according to the number of processing machines, processing tables, or measuring instruments provided in the production line system 100, and naturally, the processing machines, processing tables, or measuring instruments provided. If each number changes, this periodicity also changes.

  As described above, the periodicity described above varies depending on the number of apparatuses such as the processing machines 5a to 5b provided in the production line system 100 according to the present embodiment, or the number that needs to be adjusted in each apparatus. It becomes.

  Here, the periodicity detection method described above by the periodic information detection unit 16 will be described.

  Specifically, by performing calculations according to the following mathematical formulas (2) to (4), the period information detection unit 16 relates the order of products processed and measured, and the characteristic value 31 of the product. It is possible to detect what kind of periodicity is recognized in.

  That is, when the number of measured products is 100 and it is checked whether every other measured characteristic value 31 falls outside the specified range (in two cycles), the following formula (2) is calculated. To do.

Σ ((x (t) −x (t−1)) ² ) (2)
x (t); characteristic value of t-th product x (t−1); characteristic value of t−1-th product t; 1 ≦ t ≦ 100
In addition, when the number of measured products is 100 and it is checked whether every second characteristic value 31 measured is out of the specified range (in three cycles), the following formula (3) is calculated. To do.

Σ ((x (t) −x (t−2)) ² ) (3)
x (t-2); characteristic value of t-2th product Whether the number of measured products is 100 and the measured characteristic value 31 falls outside the specified range every 11 (in 12 cycles) In order to check this, the following mathematical formula (4) is calculated.

Σ ((x (t) −x (t-11)) ² ) (4)
x (t-11); characteristic value of t-11th product Here, as a result of performing the calculation shown in the above formulas (2) to (4), the measured product characteristic values 31 are all normal. In the case where every other characteristic value 31 is out of the specified range, every second characteristic value 31 is out of the specified range, and every other characteristic value 31 is out of the specified range every 11th. The results for the case are shown in FIG.

  As shown in FIG. 4, when the calculation is performed using the formula (2) with respect to the characteristic value 31 in the normal state, the calculation using the formula (2) is performed with respect to every other characteristic value 31 outside the specified range. Comparing with the case of performing the above, it can be seen that the latter has a larger value than the former.

  Therefore, in the adjustment device 7 according to the present embodiment, every other characteristic value 31 is obtained by determining whether or not the calculation result of Equation (2) by the period information detection unit 16 is equal to or greater than a predetermined threshold. It is possible to check whether or not periodicity outside the specified range appears.

  In addition, when the calculation according to Equation (3) is performed on the characteristic value 31 in the normal state, and when the calculation according to Equation (3) is performed on every other characteristic value 31 that is outside the specified range, , It can be seen that the latter has a larger value than the former.

  Therefore, in the adjustment device 7 according to the present embodiment, every second characteristic value 31 is obtained by determining whether or not the calculation result of Equation (3) by the period information detection unit 16 is equal to or greater than a predetermined threshold value. It is possible to check whether or not periodicity outside the specified range appears.

  In addition, when the calculation according to Equation (4) is performed on the characteristic value 31 in the normal state, and when the calculation according to Equation (4) is performed on every other characteristic value 31 that is outside the specified range, , It can be seen that the latter has a larger value than the former.

  Therefore, the periodic information detection unit 16 determines whether or not the calculation result by the mathematical expression (4) by the periodic information detection unit 16 is equal to or greater than a predetermined threshold value, so that the characteristic value 31 falls outside the specified range every 11th. Whether or not periodicity appears can be examined.

  Then, the period information detection unit 16 transmits the calculation results of the above formulas (2) to (4) to the measured characteristic value 31 to the abnormality estimation unit 17.

  By the way, in the production line system 100 according to the present embodiment, for example, the product may not be continuously input from the product input port 1 and the product may be lost. However, even in such a case, the periodic information detection unit 16 is configured to perform the above-described mathematical formulas (2) to (4) for a relatively large predetermined number of characteristic values 31, so In the value 31, the above-described periodicity is mostly maintained.

  Therefore, even when a gap occurs in the order of products processed as described above, the calculation result by the period information detection unit 16 can obtain a value approximate to the value shown in FIG.

  The abnormality estimation unit 17 estimates an abnormality cause based on the following information. That is, this information is the defect rate in the entire measured characteristic value 31 received from the defect rate calculating unit 14 and the defect rate in each of the characteristic values 31 measured in the measuring devices 6a to 6c. This information is information indicating the characteristics of the histogram received from the histogram feature detection unit 15. Furthermore, this information is information indicating the periodicity received from the periodic information detection unit 16.

  Then, the abnormality estimation unit 17 transmits information indicating an instruction to the operator to the instruction output unit 19 or transmits information indicating an adjustment instruction to the adjustment device 7 according to the estimated cause of the abnormality. .

  The said instruction | indication output part 19 gives the adjustment instruction | indication of the work table or the measuring devices 6a-6c with respect to the worker who is operating the manufacturing line system 100 which concerns on this Embodiment. The adjustment device 7 according to the present embodiment includes a display device (not shown), and the instruction output unit 19 transmits the adjustment instruction information received from the abnormality estimation unit 17 to the display device, and performs the adjustment. Instructs to display instruction information.

  In this way, the display device can instruct the adjustment member to the worker by displaying the adjustment instruction. In addition, the report of the adjustment instruction to the worker is not limited to this. For example, when each worker is provided with a mobile terminal device and this mobile terminal device is connected to the adjustment device 7 so as to be communicable, an adjustment instruction is transmitted from the instruction output unit 19 to the mobile terminal device. It may be configured. Further, when the adjustment device 7 according to the present embodiment includes a printing device, the adjustment instruction is output to the printing device and printed on a sheet so that the operator is notified of the adjustment instruction. Good.

  The adjustment part 18 adjusts the setting value of the processing machine which is an abnormality factor, when the abnormality estimation part 17 estimates that there exists an abnormality factor in any one of the processing machines 5a-5b. The adjustment unit 18 instructs the setting unit 22 to change the setting value of the processing machine that is an abnormality factor.

  In addition, the adjustment process of the setting value with respect to either of the processing machines 5a-5b by the adjustment part 18 is mentioned later.

  The setting unit 22 changes the set value of the processing machine 5a or the processing machine 5b in accordance with an instruction from the adjustment unit 18.

  The state change detection unit 20 receives the instruction from the adjustment unit 18 and totals the characteristic value 31 of the product processed after the set value of any of the processing machines 5a to 5b is changed. It is instructed to try again. The state change detection unit 20 also instructs the abnormality estimation unit 17 to stop the abnormality factor estimation processing.

  Here, in the manufacturing line system 100 according to the present embodiment, the cause of the abnormality of the characteristic value 31 measured from the processed product will be described with reference to FIG. In addition, this FIG. 5 shows the phenomenon derived from the characteristic value in the case where the cause which becomes abnormal, the factor which becomes abnormal each of the processing machines 5a-5b, the processing bases 3a-3l, and the measuring devices 6a-6c, It is drawing which shows the countermeasure with respect to the factor which becomes this abnormality.

  As described above, the production line system 100 according to the present embodiment includes the processing machines 5a to 5b, the processing table, and the measuring instruments 6a to 6c. For this reason, when any of these members does not function normally, the measured characteristic value 31 becomes abnormal.

  The causes when the processing machine 5a or the processing machine 5b does not function normally include mechanical errors of the processing machine 5a or the processing machine 5b and wear due to processing of the processing machine 5a or the processing machine 5b.

  In addition, as a cause when any of the processing bases 3a to 3l is not functioning normally, a jig that is a member used for installing a product on the processing bases 3a to 3l is loosened, For example, scraps may adhere to the installation part.

  Moreover, as a cause when the measuring instruments 6a to 6c do not function normally, there are a measurement error in any of the measuring instruments 6a to 6c, and a jig position used for fixing the product when the measuring instrument 31 measures the characteristic value 31. There is a gap.

  Therefore, if the product is processed in a state in which any one of these machines 5a to 5b, processing tables 3a to 3l, or measuring instruments 6a to 6c is not normally moved due to the above-described causes, The following phenomenon is observed in the characteristic value 31 measured from the processed product.

  That is, when any one of the two processing machines 5a to 5b is not functioning normally, every other one in the relationship between the order of the processed and measured products and the characteristic value 31 of the products. The characteristic value 31 becomes abnormal. That is, the value obtained by the calculation result of the above formula (2) is larger than the predetermined threshold value.

  In addition, as a further feature of the characteristic value 31 that appears when one of the two processing machines 5a to 5b is not functioning normally, the histogram based on all the characteristic values 31 generated by the tabulation unit 13 includes: As shown in FIG. 2B, two peaks appear.

  For this reason, when two peaks appear in the histogram, any of the processing machines 5a to 5b functions normally if the calculation result by the formula (2) of the period information detection unit 16 is larger than a predetermined threshold value. It can be determined that it is not.

  Moreover, when any one of the processing bases 3a to 3l is not functioning normally, the defect rate in the entire characteristic value 31 of the measured product is equal to or higher than a predetermined threshold value.

  Further, when any one of the processing bases 3a to 3l is not functioning normally, the characteristic value 31 becomes abnormal every 11th. That is, the value obtained by the calculation result of the above mathematical formula (4) is larger than the predetermined threshold value.

  Further, when any one of the measuring instruments 6a to 6c is not functioning normally, the characteristic value 31 obtained from any one of the measuring instruments 6a to 6c is the characteristic obtained from the other measuring instrument. Compared with the value 31, the number of characteristic values that become abnormal increases. That is, in the characteristic value 31 measured by the measuring devices 6a to 6c having a specific channel number as shown in FIG. 7, the defect rate of the characteristic value 31 is measured by the measuring devices 6a to 6c having other channel numbers. It becomes larger than the defect rate of value 31.

  FIG. 7 is a diagram showing a histogram based on the characteristic value 31 measured in each of the measuring instruments 6a to 6c. As shown in this figure, when an abnormality occurs in the measuring device 6a of channel number 1, the distribution of the characteristic value 31 measured by the measuring device 6a also appears in a range other than between the specified ranges α and β. In addition, the peak appears at a position greatly deviated from the median value of the specified range.

  In addition, when any one of the measuring instruments 6a to 6c is not functioning properly, every two in the relationship between the order of the processed and measured products and the characteristic value 31 of the products. The characteristic value 31 becomes abnormal. In other words, the value obtained from the calculation result of the above mathematical formula (3) becomes larger than the predetermined threshold value.

  By the way, even when any one of the 12 processing tables is abnormal, the defect rate of the characteristic value 31 measured by the measuring devices 6a to 6c having a specific channel number is the measuring device 6a having another channel number. May be larger than the defect rate of the characteristic value 31 measured by ~ 6c.

  However, in this case, the probability that the characteristic value 31 measured by the measuring devices 6a to 6c having the specific channel number is recognized as abnormal is approximately 25%.

  Therefore, in order to be able to distinguish whether any one of the measuring instruments 6a to 6c is abnormal or whether any one of the twelve processing tables 3a to 3l is abnormal, A configuration in which the above condition is further provided may be employed. That is, the defect rate of the characteristic value 31 measured from the measuring devices 6a to 6c of a specific channel number is larger than the defect rate of the characteristic value 31 measured from the measuring devices 6a to 6c of other channel numbers, and This defect rate is a predetermined threshold value (a value greater than 25%).

  In addition, the predetermined threshold value with respect to the value obtained by each calculation result of the above formulas (2) to (4) may be individually provided for each calculation or used in common. Also good.

  For example, when a common value is provided as a predetermined threshold for the values obtained from the calculation results of the above formulas (2) to (4), the predetermined threshold is set at least for the characteristic value 31 in the normal state. It is a value larger than the respective calculation results of the mathematical formulas (2) to (4), and is set appropriately in the adjustment target candidates, that is, the processing machines 5a to 5b, the processing bases 3a to 3l, and the measuring instruments 6a to 6b. Is done.

  Moreover, when providing individually as a predetermined | prescribed threshold value with respect to the value obtained by each calculation result of Numerical formula (2)-Numerical formula (4), a threshold value can be determined as follows.

  That is, when the predetermined threshold value for the value obtained from the calculation result of Expression (2) is normal, the characteristic value 31 of every other product is abnormal, and the characteristic value 31 of every other product is abnormal. In this case, it can be set from the result obtained by performing the calculation according to the formula (2) when the characteristic value 31 of every eleventh product becomes abnormal. Note that the calculation result is as shown in FIG. 4, for example, as described above. For this reason, referring to the calculation result shown in FIG. 4, the threshold value is larger than “160733” and is a range obtained as a calculation result when the characteristic value 31 becomes abnormal every other one, and is equal to or lower than “214833”. Set to value.

  In addition, when the predetermined threshold value for the value obtained from the calculation result of Expression (3) is normal, the characteristic value 31 of every other product is abnormal, and the characteristic value 31 of every other product is abnormal. In this case, it can be set from the result obtained by performing the calculation according to Equation (3) when the characteristic value 31 of every eleventh product is abnormal. Note that this calculation result is, for example, as shown in FIG. 4 as described above. For this reason, with reference to the calculation result shown in FIG. 4, the threshold is set to a value equal to or less than “165419” in the range obtained as the calculation result when the characteristic value 31 of every second product becomes abnormal.

  The predetermined threshold value for the value obtained by the calculation result of Equation (4) is normal, every other characteristic value 31 is abnormal, every other characteristic value 31 is abnormal, every other characteristic value 31 is normal. In the case where the characteristic value 31 is abnormal, it can be set from the result obtained by performing the calculation according to the equation (4). Note that this calculation result is, for example, as shown in FIG. 4 as described above. For this reason, referring to the calculation result shown in FIG. 4, the threshold value is larger than “8467”, and is a range obtained as a calculation result when the characteristic value 31 of every eleventh product becomes abnormal, and is “37789” or less Set to the value of.

  Further, the predetermined threshold for the defect rate in the entire characteristic value 31 is set as follows, for example. That is, the processing tables 3a to 3l have the smallest defect rate among the candidates for adjustment. Therefore, as a threshold value of the defect rate, when the characteristic value 31 is measured for 100 products, when any one of the processing tables 3a to 3l is not functioning normally, it is 12 times. Abnormality is observed in the characteristic value 31 measured at one rate. For this reason, the defect rate is about 8%. Therefore, 8% is set as the threshold value of the defect rate.

  Further, in practice, measurement errors of measuring instruments or variations in measured characteristic values occur. Therefore, in consideration of these, the predetermined threshold value described above has a certain range as a range of values that the threshold value can take. It is preferable to set it.

  Note that in the adjustment device 7 according to the present embodiment, the information regarding each threshold described above is stored in advance in the information storage unit 12 as threshold information (not shown).

  By the way, when the adjustment target member is specified using the above-described abnormality detection condition, the following countermeasures are performed in the production line system 100 according to the present embodiment.

  For example, when an abnormality is recognized in any of the processing machines 5a to 5b, the set value of any of the processing machines 5a to 5b is adjusted.

  On the other hand, if any one of the processing tables 3a to 3l or the measuring instruments 6a to 6c is abnormal, the operator can adjust the tightening of the jigs provided in the processing tables 3a to 3l and clean the processing tables 3a to 3l. Instructing the structure of the measuring instruments 6a to 6c, adjusting the contact of the jig provided in the measuring instruments 6a to 6c, and cleaning the jig.

Next, how the abnormality factor is specifically estimated using the abnormality detection condition described above will be described below with reference to FIG.
(Abnormal factor estimation process)
Next, an abnormality factor estimation process performed by the adjustment device 7 according to the present embodiment when the determination unit 21 determines that there is a characteristic value 31 that is outside the specified range will be described.

  Here, as preconditions, the failure rate of the measured characteristic value 31 as a whole is 5%, the failure rate of the characteristic value 31 measured in each measuring device 6a to 6c is 10%, and the equations (2) to (4) ) Is set to 10,000 as a threshold value set for the calculation result. These threshold values are stored in advance in the information storage unit 12 although not shown.

  Further, the histogram distribution feature (number of peaks) from the histogram feature detection unit 15, the defect rate of each of the characteristic values 31 measured by the measuring devices 6 a to 6 c from the defect rate calculation unit 14, and all measured failures It is assumed that the periodicity information is received from the periodic information detection unit 16.

  First, the abnormality estimation unit 17 clears the setting of the warning flag before performing the abnormality factor estimation process (step S11, hereinafter referred to as S11). The warning flag is a flag used to indicate what kind of estimation process has been performed, and is stored in the information storage unit 12 (not shown).

  The warning flag indicates whether any one of the measuring instruments 6a to 6c has an abnormality, whether any one of the processing machines 5a to 5b has an abnormality, the measuring instruments 6a to 6c. It is provided for each determination as to whether or not an abnormality has occurred in any one of 6c.

Therefore, when the abnormality factor estimation process is not yet executed, the warning flag must not be set in the information storage unit 12. For this reason, the abnormality estimation unit 17 clears the setting of the warning flag before performing the abnormality factor estimation process. Specifically , the abnormality estimation unit 17 sets this flag to “0” when “1” is set as the warning flag recorded in the information storage unit 12.

  Next, the abnormality estimation unit 17 compares the defect rates of the characteristic values 31 measured by the measuring devices 6a to 6c among the information on the failure rate received from the failure rate calculation unit 14. Then, the abnormality estimation unit 17 determines whether or not there is a defect rate of the characteristic value 31 associated with the channel number of each of the measuring devices 6a to 6c that is greater than or equal to a predetermined threshold (failure rate 5%). (S12).

  Here, the abnormality estimation unit 17 sets a warning flag when only one of the defect rates is equal to or greater than a predetermined threshold in the above-described determination result (“YES” in S12) (S13). ). That is, the abnormality estimation unit 17 sets 1 in the information storage unit 12 as a warning flag according to the determination as to whether or not an abnormality has occurred in any one of the measuring instruments 6a to 6c.

  On the other hand, if “NO” in the step S12, it is determined whether or not the failure rate in the measured overall characteristic value 31 is equal to or higher than a predetermined threshold (8%) (S21).

  When the abnormality estimation unit 17 completes the setting of the warning flag, the abnormality estimation unit 17 determines whether or not the calculation result is equal to or greater than a predetermined threshold (10000) based on the calculation result of Equation (3) by the cycle information detection unit 16 ( S14). Here, when any one of the measuring instruments 6a to 6c is in an abnormal state, as shown in FIG. 4, the calculation result according to the equation (3) is “165419”. For this reason, it becomes a preset threshold value “10000” or more.

  Therefore, in this determination result, when the calculation result is equal to or greater than a predetermined threshold (“YES” in S14), the abnormality estimation unit 17 estimates that any one of the measuring instruments 6a to 6c is in an abnormal state.

  On the other hand, if “NO” in the determination of step S14, it is determined whether the failure rate in the measured overall characteristic value 31 is equal to or higher than a predetermined threshold (8%) (S21). .

  Here, in Step S15, when it is estimated that any one of the measuring instruments 6a to 6c is in an abnormal state, the abnormality estimating unit 17 indicates that any one of the measuring instruments 6a to 6c is in an abnormal state. Information indicating this notification is output to the instruction output unit 19.

  In this way, the abnormality estimation unit 17 can specify the measurement device as an adjustment target and notify the operator of the measurement when any one of the measurement devices 6a to 6c is in an abnormal state.

  Next, in the case of “NO” in step S12 or “NO” in step S14, the abnormality estimation unit 17 determines whether or not the defect rate in the measured characteristic value 31 as a whole is equal to or greater than a predetermined threshold value. Determine (S21). When any one of the processing tables 3a to 3l is in an abnormal state, the overall defect rate is 8.3% or more, which is equal to or more than a predetermined threshold (8%).

  In this determination, if the defect rate in the entire characteristic value 31 is equal to or greater than a predetermined threshold (10000) (“YES” in S21), the abnormality estimation unit 17 sets a warning flag (S22). That is, the abnormality estimation unit 17 sets “1” in the information storage unit as a warning flag according to the determination process of whether any one of the processing tables 3a to 3l is in an abnormal state.

  On the other hand, if “NO” in the step S21, it is determined whether or not the number of peaks appears in the histogram for the entire characteristic value 31 (S31).

  When the warning flag is set in step S22, the abnormality estimation unit 17 determines whether or not the calculation result according to Equation (4) is equal to or greater than a threshold value (S23). In this determination, when it is determined that the calculation result according to Equation (4) is equal to or greater than the threshold value (“YES” in S23), the abnormality estimation unit 17 indicates that any one of the processing tables 3a to 3l is in an abnormal state. Estimate (S24). That is, when any one of the processing bases 3a to 3l is in an abnormal state, as shown in FIG. 4, the calculation result by the formula (4) is “37789”, which is equal to or greater than the threshold (10000).

  Therefore, if “YES” in the step S23, the abnormality estimating unit 17 can estimate that any one of the processing tables 3a to 3l is abnormal. And in this case, in order to notify the worker that any one of the processing tables 3a to 3l is in an abnormal state, the abnormality estimation unit 17 provides information indicating the notification of the abnormal state as an instruction output unit. 19 output.

  On the other hand, if “NO” in the step S23, the abnormality estimating unit 17 determines whether or not the number of peaks of the histogram with respect to the entire measured characteristic value 31 is 2 or more, in the process shown in the step S31.

  In this way, when any one of the processing tables 3a to 3l is in an abnormal state, the abnormality estimation unit 17 can identify the processing table as an adjustment target and notify the operator.

  Next, in the case of “NO” in step S21 or “NO” in step S23, the abnormality estimation unit 17 has two or more peaks in the histogram created based on the measured characteristic value 31 as a whole. Or 1 (S31).

  In the determination of step S31, when the abnormality estimation unit 17 determines that the number of peaks in the histogram is 2 or more (“YES” in S31), a warning flag is set. That is, the abnormality estimation unit 17 sets “1” in the information storage unit as a warning flag according to the determination process of whether any one of the processing machines 5a to 5b is in an abnormal state.

  On the other hand, when it is determined in step S31 that the number of peaks in the histogram is 1, the abnormality estimation unit 17 checks whether there is a warning flag recorded in the information storage unit 12 (S41).

  When the warning flag is set in step S32, the abnormality estimation unit 17 determines whether or not the calculation result of Formula 2 is equal to or greater than a threshold value (10000) (S33). If “YES” in the determination in step S33, the abnormality estimation unit 17 estimates that one of the processing machines 5a to 5b is in an abnormal state (S34). That is, when any one of the processing machines 5a to 5b is in an abnormal state, as shown in FIG. 4, the calculation result according to Equation (2) is “37789”, which is equal to or greater than the threshold value “10000”.

  On the other hand, if “NO” in the step S33, the process proceeds to a step S41. That is, the abnormality estimation unit 17 performs processing for determining the presence or absence of a warning flag.

  Therefore, if “YES” in the step S33, the abnormality estimating unit 17 can estimate that any one of the processing machines 5a to 5b is abnormal. In this case, the abnormality estimation unit 17 notifies the adjustment unit 18 that any one of the processing machines 5a to 5b is in an abnormal state. In addition, the abnormality estimation part 17 transmits the information of the histogram based on the measured characteristic value 31 whole to the adjustment part while performing this notification.

  Thus, when any one of the processing machines 5a to 5b is in an abnormal state, the abnormality estimation unit 17 can identify the adjustment target as the processing machines 5a to 5b and notify the adjustment unit 18 of the adjustment target.

  By the way, if it is determined in step S31 that the number of peaks in the histogram is 1, or if it is determined in step S33 that the calculation result according to equation (2) is less than the threshold, the abnormality estimation unit 17 generates a warning flag. Whether or not is set is determined (S41). That is, depending on whether or not the warning flag is set, the abnormality estimation unit 17 performs an estimation process for any abnormality of the measuring devices 6a to 6c, the processing tables 3a to 3l, and the processing machines 5a to 5b. You can tell if it was.

  Here, when the warning flag is set, at least the measured characteristic value 31 has a defect rate of any one of the characteristic values 31 corresponding to the channel numbers of the measuring instruments 6a to 6c equal to or greater than the threshold value. Alternatively, it can be seen that the defect rate in the entire characteristic value 31 is equal to or greater than the threshold. These phenomena indicate that some abnormal state has occurred in any of the apparatuses provided in the production line system 100 as described above.

  Therefore, the abnormality estimation part 17 notifies the warning which shows that the abnormal condition has arisen in the instruction | indication output part, when it is "YES" in step S41. By this notification, the worker can confirm that an abnormality has occurred in some apparatus.

  On the other hand, when no warning flag is set (“NO” in S41), the abnormality estimation unit 17 determines that diagnosis is impossible (S43) and ends the process.

  As described above, the adjustment device according to the present embodiment identifies an adjustment target in which an abnormality has occurred, notifies the specified adjustment target, or instructs to adjust the setting value of the adjustment target. Can do.

(Setting value adjustment processing)
Next, referring to FIG. 8 and FIG. 9, adjustment is performed when a notification that either the processing machine 5 a or the processing machine 5 b is not operating normally (in an abnormal state) is received from the abnormality estimation unit 17. A setting value adjustment process performed by the unit 18 will be described.

  FIG. 8 is a diagram illustrating an example of setting value adjustment processing in the adjustment device 7 according to the present embodiment. FIG. 9 is a flowchart showing correction value search processing in the adjustment apparatus 7 according to the present embodiment.

By the way, when either the processing machine 5a or the processing machine 5b is not moving normally, in the histogram based on the characteristic value 31 of the product processed by either one, the peak section is determined from the center value M between the specified ranges α and β. Appears at a shifted position. For this reason, when either the processing machine 5a or the processing machine 5b does not move normally, two peaks are generated in the histogram based on the measured characteristic value 31 as a whole (A ₁ , A ₂ ).

Here, the adjustment device 7 according to this embodiment, adjustment unit 18, and a value of the section value and the peak A ₂ of the section peaks A ₁ appears appears, a central value M of the regular range alpha-beta Compare with the interval value. Then, the set value of the processing machine is changed so that the value of the other peak approaches the value of the peak closest to the value of the section of the center value M.

  That is, the product processed by either the processing machine 5a or the processing machine 5b is normally processed. That is, in the histogram distribution based on the characteristic value 31 of the product processed by either the processing machine 5a or the processing machine 5b, the histogram in which the peak appears in the section closest to the center value M satisfies the specified quality. It can be regarded as a histogram based on the characteristic value 31.

Therefore, the setting value of the processing machine is changed so that the value of the other peak approaches the value of the peak closest to the center value M of the specified range α-β among the peaks A ₁ and A ₂ . In this way, it is possible to approximate a histogram based on the characteristic value 31 of the product that satisfies the specified quality.

Thus, the example of the histogram shown in FIG. 8, the value of the interval in which the peak A ₂ appears is in the vicinity of the central value M, the processing machine 5a so Yoriyori large value the value of the section in which the peak A ₁ appears or What is necessary is just to change the setting value of the processing machine 5b.

Note that conversely, if the direction of the peak A ₁ appears in the vicinity of the central value M, the change of the set value of the processing machine 5a or the processing machine 5b so that smaller value of the section of appearance of the peak A ₂ Do.

On the other hand, on the histogram as shown in FIG. 8, it is not known which peak value reflects the characteristic value 31 of the product processed by which processing machine at peak A ₁ and peak A ₂ .

  Therefore, in the adjustment unit 18 according to the present embodiment, specifically, the setting value of one of the processing machines 5a or 5b is set to be the first set value of the processed product so that the characteristic value 31 of the processed product is increased. To change. Then, the set value of the other processing machine is changed according to the change result.

For example, as shown in FIG. 8, when the set value of the processing machine 5 a is first changed so that the characteristic value 31 increases, among the peaks A ₁ and A ₂ of the histogram based on the measured characteristic value 31. , a peak a ₂ is moved to the position of the value of the section indicated by S. That is, it is assumed that the distribution of the characteristic value 31 indicated by the histogram is in a state where the distribution has spread beyond the upper limit value β in the specified range.

In this state, it is clear that the variation of the distribution of the characteristic value 31 is broadened, and it is not possible to adjust well. Therefore, if the adjustment cannot be made in this way, the setting value of the processing machine 5a is restored to the original value with reference to the device initial value 32 stored in the information storage unit 12 in advance. Then, this time, the set value of the processing machine 5b is changed as if it was performed on the processing machine 5a. As a result, the value of the peak A ₁ of the histogram as shown in FIG. 8 is that it has moved to the value of the section shown in T.

That is, when the value of the peak A ₁ changes to the value of T, the total number of peaks in the histogram becomes one, and the peak appears in the vicinity of the center value M between the prescribed ranges α and β of the characteristic value 31. . Further, all the characteristic values 31 are within the specified range α-β.

  When a histogram based on the characteristic value 31 measured in such a state appears, it can be determined that the adjustment of the processing machine 5b is successful by changing the set value of the processing machine 5b.

  Thus, in the production line system 100 according to the present embodiment, the processing machine 5a or the processing machine 5b can be appropriately adjusted by changing the value at which the peak appears in the histogram. In the following, with reference to FIG. 9, the flow of a setting value adjustment process for adjusting the setting value of either the processing machine 5a or the processing machine 5b will be described.

  First, when the adjustment unit 18 receives a notification from the abnormality estimation unit 17 that either the processing machine 5a or the processing machine 5b is not operating normally (in an abnormal state), the adjustment unit 18 causes the abnormality estimation unit 17 to report an abnormality factor. Is instructed to be stopped (S51). In this way, the adjustment unit 18 stops the abnormality factor estimation process by the abnormality estimation unit 17 while the setting value adjustment process is being performed.

  Next, the adjustment unit 18 determines the setting change policy of the processing machine 5a or the processing machine 5b based on the information of the histogram transmitted together with the notification from the abnormality estimation unit 17 (S52). The setting change policy is to change the setting of the processing machine 5a or the processing machine 5b so that the characteristic value 31 of the product processed by either the processing machine 5a or the processing machine 5b is increased or decreased. Is to decide what to do.

  As described above, when a peak appears in two sections as described above, the value of the section in which the other peak appears is based on the peak section appearing in the vicinity of the center value M of the specified range α-β. This is performed depending on whether the change is made to become larger or smaller.

  In the present embodiment, it is assumed that the adjustment unit 18 determines to change the setting value of either the processing machine 5a or the processing machine 5b in the above-described determination so that the characteristic value 31 of the processed product is increased.

  Therefore, the adjustment unit 18 first changes the setting value of the processing machine 5a so that the characteristic value 31 measured from the product processed by the processing machine 5a is increased (S53). The change amount of the set value is an appropriate value, and may be at least a set value that increases the characteristic value of the product processed by the processing machine whose set value has been changed. That is, in the present embodiment, by repeating the change of the set value, it is configured so as to approach the shape of the histogram based on the characteristic value of the processed product that satisfies the specified quality as a result.

  Here, when the set value of the processing machine 5a is changed, the characteristic value 31 obtained after the change is naturally different from that before the setting change. Therefore, the adjustment unit 18 notifies the state change detection unit 20 of a state change indicating that the setting of the processing machine 5a has been changed (S54). In response to this notification, the state change detection unit 20 instructs the counting unit 13 to redo the counting of the characteristic values 31. And according to the instruction | indication from the state change detection part 20, the total part 13 totals the characteristic value 31 of the product processed after the setting change of the processing machine 5a.

  The state change detection unit 20 designates an instruction to the counting unit 13 by designating a time during which the product processed by the processing machine 5a after the setting change is measured by any one of the measuring devices 6a to 6c. It is supposed to be.

  That is, the production line system 100 according to the present embodiment is configured to be conveyed from the processing machine 5a to the measuring instruments 6a to 6c at a constant speed. For this reason, the measurement time of the characteristic value 31 of the product processed by the processing machine 5a after the setting change is calculated by calculating the time required for the processed product to be conveyed to the measuring devices 6a to 6c. I understand.

  Further, as described above, the characteristic value 31 measured by any one of the measuring instruments 6a to 6c is stored in the information storage unit 12 in association with the measured time. For this reason, the totalization part 13 can totalize the characteristic value 31 of the product processed by the processing machine 5a by which the setting value was changed.

  Thus, the totaling unit 13 totals the characteristic values 31 of the products processed by the processing machine 5a whose set values have been changed, and creates a histogram based on the characteristic values 31. Then, the adjustment unit 18 is notified of information on the created histogram.

  Based on the histogram information received from the totalization unit 13, the adjustment unit 18 determines whether or not there is one peak in the histogram (S55). That is, the adjustment unit 18 determines whether the frequency of the characteristic value increases in the value near the center value of the specified range α-β, and the frequency of the characteristic value gradually decreases in the sections before and after this section.

  If the adjustment unit 18 determines in step S55 that the number of peaks has become one (“YES” in S55), the adjustment process for the set value is terminated.

On the other hand, if “NO” in the step S55, it is determined whether or not the distance between two peaks appearing in the histogram in the received histogram information is smaller than before the setting of the processing machine 5a is changed (S56). ). Note that the peak-to-peak distance can be determined as an absolute value of the difference between the value of the section in which the peak A ₁ appears, the value of the section in which the peak A ₂ appears.

  That is, when changing the setting of the processing machine 5a, the adjustment unit 18 stores information of each section where the peak appears in the histogram based on the characteristic value 31 before the setting change although not particularly shown in FIG. Stored in the unit 12. Then, the adjustment unit 18 compares the distance in each peak value stored in the information storage unit 12 with the distance in each peak value in the histogram received after the setting of the processing machine 5a is changed.

  In this comparison, when the adjustment unit 18 determines that the distance between the peaks is small (“YES” in S56), the process returns to step S53 again to change the set value of the processing machine 5a. Then, the processing from step S53 to step S56 is repeated until there is one section where the peak appears.

  On the other hand, as a result of changing the set value of the processing machine 5a so that the characteristic value of the product processed by the processing machine 5a becomes larger, the set value is based on the characteristic value of the product processed by the processing machine 5a or the processing machine 5b. Assume that the distance between peaks in the histogram has not decreased. That is, in the case of “NO” in step S56, the adjustment unit 18 notifies the state change detection unit 20 of a state change indicating that the setting of the processing machine 5a is changed (S57).

  The change in state here means that the characteristic value measured is not good even if the set value of the processing machine 5a is changed, so that it is temporarily returned to the original set value. And the adjustment part 18 returns the changed setting value of the processing machine 5a to the original setting value with reference to the apparatus initial value 32 (S58).

  When the setting value of the processing machine 5a is returned to the original value as described above, the adjustment unit 18 obtains the setting value of the processing machine 5b from the characteristic value 31 measured from the product processed by the processing machine 5b. The set value is changed so as to increase (S59). In the subsequent processing, steps S60 to S62 are the same as the processing performed on the processing machine 5a, and thus the description thereof is omitted.

  However, when the set value of the processing machine 5b is changed in step S62 but the peak-to-peak distance is not reduced (“NO” in S62), an instruction is given to notify the instruction output unit 19 of a warning. To do.

  That is, although the set values of the processing machine 5a and the processing machine 5b are changed, the histogram based on the measured characteristic value approaches the histogram based on the characteristic value of the processed product that satisfies the specified quality. Absent. For this reason, it is determined that the cause of the abnormality in the measured characteristic value is not based on the mechanical error of the processing machine 5a or the processing machine 5b.

  Therefore, when the adjustment unit 18 instructs the instruction output unit 19 to notify the warning, the worker knows that the cause of the abnormality in the measured characteristic value is not the mechanical error of the processing machine 5a or the processing machine 5b. be able to.

  Therefore, the worker can efficiently investigate other factors such as whether wear has occurred in either the processing machine 5a or the processing machine 5b.

  As described above, when it is determined that the characteristic value measured from the processed product is not within the specified range, the adjustment device 7 according to the present embodiment can identify the abnormality factor based on the characteristic value. . That is, based on whether the characteristic value outside the specified range appears in 2 cycles, 3 cycles, or 11 cycles, whether the abnormality factor is any of the processing machines 5a to 5b or any of the measuring devices 6a to 6c. Or any one of the processing bases 3a to 3l.

  In particular, the adjusting device 7 can identify the cause of the abnormality while processing the product.

  Further, the adjusting device 7 can notify the worker of the abnormality factor specified by specifying to the instruction output unit 19.

  Furthermore, when it is specified as any of the processing machines 5a to 5b as an abnormality factor, the adjustment unit 18 measures the set value of the processing machines 5a to 5b from the processed product satisfying the specified quality. The characteristic value can be adjusted.

  In addition, in the manufacturing line system 100 which concerns on this Embodiment, although the processing bases 3a-3l, the processing machines 5a-5b, and the measuring devices 6a-6c were provided, the kind of apparatus provided is limited to this. Instead, other types of devices such as assembly machines may be provided. These types of devices are preferably provided as appropriate according to the products to be manufactured.

  Further, in the production line system 100 according to the present embodiment, twelve processing tables 3a to 3l, two processing machines 5a to 5b, and three measuring devices 6a to 6c are provided. The number of is not limited to this. Any number may be used as long as the numbers of the processing tables 3a to 3l, the two processing machines 5a to 5b, and the three measuring devices 6a to 6c are different from each other. The number of these devices can be appropriately determined according to the type and number of products to be processed.

  Moreover, in the above-described abnormality factor estimation processing, the estimation processing is performed in the order of the presence / absence of abnormality of the measuring instrument, the presence / absence of abnormality of the processing table, and the presence / absence of abnormality of the processing machine. It is not limited to.

  For example, the estimation processing may be performed in order from the device having the highest frequency of occurrence of a failure in each device. Alternatively, the order may be determined in accordance with how a failure occurs in each device or how a characteristic value changes when a failure occurs in each device.

  Examples of how this defect occurs include how a measurement error of a measuring instrument occurs, how a jig on a processing table is loosened, and how dust adheres.

  In addition, the method of changing the characteristic value is, for example, when the measurement error of the measuring instrument occurs, the characteristic value gradually changes. The characteristic value changes greatly in a short period of time.

  Moreover, the production line system 100 according to the present embodiment may be used in any process in the production process. Therefore, the processed product whose characteristic values are measured by the measuring instruments 6a to 6c may be a finished product or a product being manufactured in the production process.

  As described above, the periodic information detection unit 16 uses the above formulas (2) to (4) in order to detect the periodicity of the characteristic value 31 that is a value outside the specified range. It was. However, the calculation method by the period information detection part 16 is not limited to these, The structure which uses FFT may be sufficient.

  For example, the period information detection unit 16 relates the relationship between the conveyance order of products that are processed and the characteristic values are measured, and the characteristic values that are indicated for each conveyance order of the products (FIG. 3B to FIG. d)) as time series data. That is, the product conveyance order shown on each horizontal axis in FIGS. 3B to 3D is taken as a value on the time axis.

  The period information detection unit 16 may be configured to perform an operation by FFT (fast fourier transformation) on the time series data to detect the appearance period of the characteristic value that is outside the specified range.

  That is, by using the power spectrum obtained as the calculation result by the FFT, the periodicity can be examined similarly to the calculation results of the above formulas (2) to (4).

  For example, as described above, the relationship between the order of products transported by the transport belt 8 and the characteristic values measured from the products is time-series data, and the range of the order from 0th to 100th shown on the horizontal axis is 1. Consider as seconds. Considering each of FIGS. 3B to 3C as such time-series data, for example, as shown in FIG. 3B, there are 50 characteristic values outside the specified range between the 0th and the 100th. The case where it appears can be regarded as a frequency of 50 Hz.

  For this reason, when a strong wavelength appears at a position of 50 Hz in the FFT result for the time series data, every other characteristic value is a value outside the specified range. That is, in this case, it can be estimated that an abnormality has occurred in either the processing machine 5a or the processing machine 5b.

  Similarly, considering FIG. 3C, when 33 characteristic values exceeding the specified range appear between 0th and 100th as shown in FIG. It can be taken as a frequency.

  For this reason, in the calculation result by FFT on the time series data, when a strong wavelength appears at a position of 33 Hz, every two characteristic values are outside the specified range. That is, in this case, it can be estimated that an abnormality has occurred in any one of the measuring instruments 6a to 6c.

  Similarly, when considering FIG. 3 (d), the case where eight characteristic values exceeding the specified range appear between the 0th and the 100th as shown in FIG. 3 (d). It can be regarded as a frequency of 8 Hz.

  For this reason, in the FFT result for the time-series data, when a strong wavelength appears at a position of 8 Hz, the characteristic value is a value outside the specified range every 11th. That is, in this case, it can be estimated that an abnormality has occurred in any one of the processing tables 3a to 3l.

  As described above, when the periodic information detection unit 24 detects the appearance periodicity of the characteristic value that is outside the specified range by the FFT calculation, it is more accurate than the calculation of the above formulas (2) to (4). There is an additional effect that the periodicity can be detected.

  However, as shown in the above formulas (2) to (4), the calculation of the sum of the magnitudes of differences from every other, every second, every eleventh characteristic value 31 is more than the use of FFT. The amount is small and it is excellent in terms of high-speed processing.

  The adjustment device 7 described above is configured to be able to estimate the device to be adjusted. However, the adjustment device 7 is configured to display a change state of variation in characteristic values obtained as a result of adjusting the device specified as the adjustment target. Is preferable.

  For example, it is assumed that an abnormality occurs in any one of the processing tables 3a to 3l, any one of the processing machines 5a to 5b, and any one of the measuring devices 6a to 6c. In this case, as a result of performing the calculation by FFT on the time series data, the power spectrum is as shown in FIG. That is, the amplitude of the wavelength at each frequency position of 8 Hz, 33 Hz, and 50 Hz is increased.

  However, when any one of the processing tables 3a to 3l is abnormal, when any one of the measuring instruments 6a to 6c is abnormal, when either the processing machine 5a or the processing machine 5b is abnormal, Depending on each case, the degree to which the characteristic value obtained from the product deviates from the value in the specified range varies. That is, the difference between the characteristic value within the specified range and the measured characteristic value varies depending on the device that causes the abnormality. For this reason, the magnitudes of amplitudes at 8 Hz, 33 Hz, and 50 Hz shown in FIG. 11 are different.

  Further, in the apparatus in which the abnormality factor is generated, the amplitude of the wavelength at the frequency positions of 8 Hz, 33 Hz, and 50 Hz varies depending on the type of abnormality factor occurring or the degree of abnormality.

  As described above, since the degree of deviation of the measured characteristic value from the specified range differs depending on the device causing the abnormality or the abnormality factor, the characteristics obtained before adjustment when adjusting the device causing the abnormality When the value is compared with the characteristic value obtained after adjustment, the former and the latter may not change so much.

  In such a case, in consideration of work efficiency of product processing and quality accuracy required for the product, the worker may determine that it is not necessary to adjust the apparatus in an abnormal state.

  Here, the adjustment device 107 that can display the change state of the variation degree in the characteristic value obtained as a result of adjusting the device specified as the abnormality factor will be described below.

  As shown in FIG. 10, the adjustment device 107 is different from the adjustment device 7 described above in that it further includes an influence calculation unit 23 in addition to the configuration of the adjustment device 7 described above. The influence calculation unit 23 is a characteristic value when the adjustment target is adjusted based on the adjustment target information notified from the abnormality estimation unit 25 and the power spectrum information received from the period information detection unit 24. This is to estimate the degree of change.

  The degree of influence of the characteristic value change is a predicted value of the degree of variation of the characteristic value obtained after the adjustment of the adjustment target is completed.

  Further, the adjusting device 7 and the adjusting device 107 described above differ in the following points.

  That is, the adjustment instruction of either the processing machine 5a or the processing machine 5b to the adjustment unit 26 is different from the adjustment device 7 described above in that the instruction output unit 19 performs the adjustment instruction.

  In addition, when the adjustment unit 26 receives an adjustment instruction for either the processing machine 5a or the processing machine 5b from the instruction output unit 19, the adjustment unit 26 instructs the abnormality estimation unit 17 to stop the abnormality estimation process. Different.

  Further, the adjustment unit 26 acquires the histogram information of the characteristic value 31 aggregated from the aggregation unit 13 and determines the setting change policy of the processing machine 5a or the processing machine 5b based on this information. 18 and different.

  Further, instead of using the above formulas (2) to (4) in order for the cycle information detection unit 24 to detect the periodicity of the characteristic value that is a value outside the specified range, the power obtained as the calculation result by FFT It differs from the period information detector 16 provided in the adjustment device 7 in that a spectrum is used.

  Moreover, the abnormality estimation part 25 differs from the abnormality estimation part 17 with which the adjustment apparatus 7 is provided by notifying the influence degree calculation part 23 of information indicating the estimated adjustment target.

  In the adjusting device 107, the same members as those of the adjusting device are denoted by the same reference numerals, and description of these members is omitted.

  Here, the flow of information relating to the calculation process of the predicted value of the variation degree based on the characteristic value obtained after the adjustment of the adjustment target in the influence calculation unit 23 will be described.

  First, the period information detection unit 24 performs an FFT calculation using time series data based on the characteristic value 31 stored in the information storage unit 12 and the processing order of the processed product whose characteristic value 31 is measured. Do. Then, the obtained power spectrum and the time series data are transmitted to the influence calculation unit 23.

  In addition, the abnormality estimation unit 25 notifies the influence degree calculation unit 23 of the result of the abnormality factor estimation process.

  The influence degree calculation unit 23 relates to a device estimated as an abnormality factor, that is, a device estimated as an adjustment target, using the power spectrum obtained from the period information detection unit 24, and a variation in characteristic values after adjustment of the adjustment target device. Calculate the change in degree.

  Then, the calculated change information of the variation degree is transmitted to the instruction output unit 19 and displayed.

  Here, the calculation process of the variation degree variation of the characteristic value after the adjustment of the adjustment target apparatus by the influence degree calculation unit 23 will be described below.

(Variation degree change calculation process after adjustment)
By the way, with respect to the time series data, the power spectrum obtained by the FFT is the square of the amplitude of the frequency component of each period when the frequency obtained by calculating the time series data by the FFT is considered as a sine wave. Equivalent to.

  Therefore, the sum of the FFT power spectrum excluding the average value component (offset component with respect to frequency 0) is the square of the standard deviation of the time series data (excluding the influence of the average value in the time series data) (that is, variance) ). That is, the sum of the entire FFT power spectrum (excluding the FFT power spectrum of frequency 0) before the correction of the abnormal object is “P_all”, the total standard deviation before the correction of the abnormal object is “σ_all”, and K is an arbitrary When expressed as a number, the following equation (5) holds.

P_all = K · (σ_all) ² (5)
The offset component with respect to the frequency 0 is the inverse Fourier transform of the value obtained by performing the FFT operation on the time-series data and representing the amplitude with 0 being the average value level. Thus, the value is necessary to reproduce the time series data.

  Here, it is assumed that any one of the measuring devices 6a to 6c is in an abnormal state and the measuring device in the abnormal state is corrected. By correcting the measuring instrument that is an abnormal factor in this way, the frequency component of the power spectrum appearing at 33 Hz indicated when any one of the measuring instruments 6a to 6c is in an abnormal state is substantially zero (white noise). It is assumed that the voltage is reduced to be close to (position) (see FIG. 12).

  In this case, the amount of decrease in the standard deviation of the time series data can be estimated approximately by subtracting the standard deviation after the reduction from the standard deviation before the frequency component of the 33 Hz power spectrum is reduced. it can. That is, the FFT power spectrum at 33 Hz before the abnormality correction of any one of the measuring instruments 6a to 6c is “P3”, and the amount of decrease in the standard deviation after the abnormality correction of any one of the measuring instruments 6a to 6c is “ If σ3 ”, the relationship shown in the following mathematical formula (6) is established.

P3 = K · (σ3) ² (6)
Therefore, the influence degree calculation unit 23 obtains before the correction of the abnormality factor by calculating the following expressions (7) and (8) derived from the relationship between the expressions (5) and (6). The difference between the value of the entire characteristic value obtained and the value of the entire characteristic value obtained after correction can be obtained.

  First, the amount of decrease in the standard deviation after any abnormality correction of any one of the measuring instruments 6a to 6c is expressed by the following formula (7) obtained using the relationship with the formula (5) and formula (6). Desired.

σ3 = σ_all * √ (P3 / P_all) (7)
σ3: Amount of decrease in standard deviation after correction of abnormal target (any one of measuring instruments 6a to 6c) σ_all: Overall standard deviation before correction of abnormal target (any one of measuring instruments 6a to 6c) P3 : FFT power spectrum of 33 Hz before correction of the abnormality target (any one of the measuring instruments 6a to 6c) P_all: Overall FFT power spectrum before correction of the abnormal target (any one of the measuring instruments 6a to 6c) ( Therefore, the standard deviation of the entire characteristic value measured after correcting the abnormality of any one of the measuring instruments 6a to 6c is expressed by the following equation (Equation (8)). be able to.

Standard deviation of the entire characteristic value measured after the abnormality correction = σ_all−σ3 (8)
Thus, by performing the above-described calculation, the influence degree calculation unit 23 calculates the degree of variation of the characteristic value before and after the correction of the abnormality factor with respect to the characteristic value in the specified range, and the calculated result is indicated in the instruction output unit. 19 to send.

  It should be noted that all the values related to the correction of the abnormal factor used in the above calculation can be obtained from the time series data. That is, the influence degree calculation unit 23 can obtain these values based on the power spectrum information received from the period information detection unit 24 and the time series data.

  Further, the amount of decrease in the standard deviation after correcting the abnormality factor can be obtained by virtually replacing the value of the power spectrum appearing at the specific frequency with the value of the white noise range.

  For this reason, the influence degree calculation part 23 in the said adjustment apparatus 7 can calculate the said dispersion | variation degree of the characteristic value after adjustment of an abnormal factor before adjustment of an abnormal factor.

  Further, since the adjusting device 7 can output the degree of variation of the calculated characteristic value of the abnormal factor after adjustment to the instruction output unit 19, the operator determines whether or not to adjust the abnormal factor. be able to.

  Further, the adjusting device 7 described above does not display the degree of variation of the characteristic value after adjustment as in the adjusting device 107 described above, but automatically according to the quality accuracy required for the product to be processed in advance. In other words, it is possible to determine whether or not there is a need to adjust the abnormality factor and output the determination result to the instruction output unit 19.

  In the following, the configuration of the adjusting device 207 that automatically determines whether or not adjustment for an abnormality factor is necessary according to quality accuracy required for a product to be processed in advance and outputs the determination result to the instruction output unit 19 will be described. To do.

  As shown in FIG. 13, the adjustment device 207 further includes a warning determination unit 27 in addition to the configuration of the adjustment device 7 described above, and the information storage unit 12 further stores variation tolerance information 33. Is different from the adjustment device 7 described above.

  The variation allowance information 33 is a reduction amount of the standard deviation after the abnormality estimation regarding the device that becomes an abnormality factor, and is a value that does not require adjustment of the abnormality factor at least when the amount is not equal to or greater than the reduction amount. This value is set in advance by an operator who operates the production line system 100.

  In addition, the warning determination unit 27 uses the adjustment target information notified from the abnormality estimation unit 25, the power spectrogram information received from the period information detection unit 24, and the allowable variation information stored in the information storage unit 12. Based on this, it is determined whether or not to adjust the abnormality factor. The warning determination unit 27 outputs information indicating a warning to the instruction output unit 19 when it is necessary to adjust the apparatus that is the cause of the abnormality as a result of the determination.

  Note that the determination processing regarding whether or not to adjust the cause of abnormality by the warning determination unit 27 will be described later.

  Further, the adjusting device 7 and the adjusting device 207 described above differ in the following points.

  That is, the adjustment instruction of either the processing machine 5a or the processing machine 5b to the adjustment unit 26 is different from the adjustment device 7 described above in that the instruction output unit 19 performs the adjustment instruction.

  In addition, when the adjustment unit 26 receives an adjustment instruction for either the processing machine 5a or the processing machine 5b from the instruction output unit 19, the adjustment unit 26 instructs the abnormality estimation unit 17 to stop the abnormality estimation process. Different.

  Further, the adjustment unit 26 acquires the histogram information of the characteristic value 31 aggregated from the aggregation unit 13 and determines the setting change policy of the processing machine 5a or the processing machine 5b based on this information. 18 and different.

  Further, instead of using the above formulas (2) to (4) in order for the cycle information detection unit 24 to detect the periodicity of the characteristic value that is a value outside the specified range, the power obtained as the calculation result by FFT It differs from the period information detector 16 provided in the adjustment device 7 in that a spectrum is used.

  Moreover, the abnormality estimation part 25 differs from the abnormality estimation part 17 with which the adjustment apparatus 7 is provided by notifying the influence degree calculation part 23 of information indicating the estimated adjustment target.

  In the adjusting device 107, the same members as those of the adjusting device are denoted by the same reference numerals, and description of these members is omitted.

  Here, the flow of the determination process related to whether or not to adjust the abnormality factor by the adjusting device 207 will be described.

  First, the period information detection unit 24 performs FFT calculation using time-series data based on the characteristic value 31 stored in the information storage unit 12 and the processing order of the processed product whose characteristic value is measured. . Then, the obtained power spectrum is transmitted to the influence calculation unit 23.

  In addition, the abnormality estimation unit 25 notifies the influence degree calculation unit 23 of the result of the abnormality factor estimation process.

  When the warning determination unit 27 receives the information on the device estimated as the abnormality factor from the abnormality estimation unit 25, the warning determination unit 27 receives time-series data based on the power spectrum information and the characteristic value 31 received from the period information detection unit 24.

  Further, the warning determination unit 27 acquires the variation allowable information 33 stored in the information storage unit 12.

  Then, the warning determination unit 27 includes a threshold value obtained based on the time series data, the power spectrum information, and the variation tolerance information 33, and a power spectrum obtained by the FFT operation on the time series data based on the measured characteristic value 31. Compare. Then, the warning determination unit 27 determines whether or not to output information indicating a warning to the instruction output unit 19.

  Here, a method of calculating a threshold value to be compared with the power spectrum obtained by the FFT operation on the time series data based on the measured characteristic value 31 will be described.

  First, the warning determination unit 27 performs the calculation of the following formula (9) in order to obtain the above threshold value. Here, as an example, it is assumed that the abnormality factor is in any one of the measuring devices 6a to 6c.

Q3 = P_all * (γ3 / σ_all) ² (9)
Q3: Threshold for FFT power spectrum at 33 Hz before any abnormality correction of any one of the measuring instruments 6a to 6c P_all: Overall FFT power spectrum before any abnormality correction of any one of the measuring instruments 6a to 6c (with a frequency of 0) (Excluding FFT power spectrum)
σ_all: Overall standard deviation before any abnormality correction of any one of the measuring instruments 6a to 6c γ3: Value allowed as a decrease amount of the standard deviation after any abnormality correction of any one of the measuring instruments 6a to 6c (variation Tolerance information)
Here, as described above, the value of P_all can be obtained by performing an operation by FFT on the time series data based on the characteristic value 31 measured by the warning determination unit 27.

  Further, as described above, the value of σ_all can be obtained by the warning determination unit 27 based on the time series data.

  Further, the value of γ3 can be acquired from the information storage unit 12 by the warning determination unit 27 as variation allowable information.

  In addition, Q3 calculated | required by the said calculation is an FFT power spectrum in 33 Hz before abnormality correction in which the dispersion | variation degree of a characteristic value is accept | permitted, Let this power spectrum be a threshold value.

  The warning determination unit 27 then calculates the power spectrum (F3) obtained by FFT on time-series data based on the threshold value (Q3) obtained by the above-described calculation and the actually measured characteristic value 31 before adjusting the abnormality factor. Compare P3). If the former is smaller than the latter as a result of the comparison (Q3 <P3), the warning determination unit 27 outputs information indicating a warning to the instruction output unit.

  That is, when the relationship of “Q3 <P3” holds, the power spectrum obtained by the FFT calculation result for the time series data based on the actually measured characteristic value 31 is larger than the allowable power spectrum value. It can be said. In other words, when the relationship of “Q3 <P3” is established, the degree of variation of the actually measured characteristic value 31 with respect to the characteristic value within the specified range exceeds the allowable range.

  The variation allowable information (γ3) 33 can be determined in advance according to the quality accuracy required for the processed product. Therefore, when high quality accuracy is required, the value of the variation allowable information (γ3) 33 becomes small.

  Thus, since the adjustment device 207 includes the warning determination unit 27, it can be determined whether or not adjustment for an abnormality factor is necessary.

  Therefore, by adjusting the device that is estimated to be an abnormal factor, it is automatically determined whether or not to adjust the device that is estimated to be the abnormal factor in consideration of the change in the variation degree of the characteristic value. be able to.

  Note that the warning determination unit 27 performs the calculation according to Equation (9) to determine a threshold value and determines whether to output a warning. However, if emphasis is placed on easy understanding, the power determined by FFT A configuration may be adopted in which all the characteristic values 31 measured instead of the spectrum are converted into standard deviations, and then the threshold value is displayed on the instruction output unit 19 and the threshold value is set.

  Each unit included in each of adjustment device 7, adjustment device 107, and adjustment device 207 according to the present embodiment may be realized by hardware logic or may be realized by software.

  That is, when realized by software, each unit and each processing step of the adjustment device 7, the adjustment device 107, and the adjustment device 207 of the above-described embodiment are performed by a calculation unit such as a CPU (not shown) by a ROM (Read It can be realized by executing a program stored in a storage means such as a RAM (not shown) or a RAM (not shown) and controlling an input means such as a keyboard, an output means such as a display, or a communication means such as an interface circuit. it can.

  Therefore, the computer having these means can realize the various functions and the various processes of the adjusting device of the present embodiment simply by reading the recording medium storing the program and executing the program. In addition, by recording the program on a removable recording medium, the various functions and various processes described above can be realized on an arbitrary computer.

  As this recording medium, a program medium such as a memory (not shown) such as a ROM may be used for processing by the microcomputer, or a program reader is provided as an external storage device (not shown). It may be a program medium that can be read by inserting a recording medium therein.

  In any case, the stored program is preferably configured to be accessed and executed by the microprocessor. Furthermore, it is preferable that the program is read out, and the read program is downloaded to a program storage area of the microcomputer and the program is executed. It is assumed that this download program is stored in advance in the main unit.

  The program medium is a recording medium configured to be separable from the main body, such as a tape system such as a magnetic tape or a cassette tape, a magnetic disk such as a flexible disk or a hard disk, or a disk such as a CD / MO / MD / DVD. Fixed disk, IC card (including memory card), etc., or semiconductor ROM such as mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash ROM, etc. In particular, there are recording media that carry programs.

  In addition, if the system configuration is capable of connecting to a communication network including the Internet, the recording medium is preferably a recording medium that fluidly carries the program so as to download the program from the communication network.

  Further, when the program is downloaded from the communication network as described above, it is preferable that the download program is stored in the main device in advance or installed from another recording medium.

  In addition, this invention is not limited to embodiment mentioned above, A various change is possible in the range shown to the claim. That is, embodiments obtained by combining technical means appropriately modified within the scope of the claims are also included in the technical scope of the present invention.

  The adjustment device 7 according to the present embodiment includes a plurality of types of devices, and a plurality of types of devices in a production line system in which a product is processed by any one of the types of devices. It is possible to determine which type of device has an abnormality. For this reason, it can be widely applied to a production line for mass production of various products.

1, showing an embodiment of the present invention, is a block diagram illustrating a main configuration of a production line system. FIG. An example of a histogram based on all the characteristic values measured by the measuring device is shown. FIG. 11A shows a histogram based on the characteristic values processed and measured in a normal state, and FIG. ) Shows a histogram based on characteristic values processed and measured in a state where an abnormality has occurred. It is a figure which shows the relationship between the order of the product which was processed and the characteristic value was measured, and the characteristic value which this product has. The figure (a) is processed in a normal state, and the characteristic value is measured. The relationship between the order of the products and the characteristic values of the products is shown. FIG. 5 (b) shows that the processing values were measured and the characteristic values were measured when any of the processing machines did not move normally. The relationship between the order of the products and the characteristic values of the products is shown. FIG. 10C shows the case where any one of the measuring instruments is not normally operated and processed and the characteristic values are measured. The relationship between the order of the products and the characteristic values of the products is shown. FIG. 4D shows that the processing values are measured and the characteristic values are measured when any one of the processing tables is not moving normally. The relationship between the order of the manufactured products and the characteristic values of the products is shown. When the characteristic value is within the specified range, every other characteristic value is outside the specified range, when every other characteristic value is out of the specified range, the characteristic value is specified every 11th It is a table | surface which shows the result of having calculated Numerical formula (2), Numerical formula (3), and Numerical formula (4) about each case when it comes out of the range of this. It is a figure explaining an example of the countermeasure with respect to the cause which becomes abnormal in a processing machine, a processing stand, and a measuring instrument, the phenomenon obtained from a characteristic value, and an abnormal condition. It is a flowchart which shows an example of the estimation process of the abnormality factor in the adjustment apparatus which concerns on this Embodiment. It is a figure which shows the histogram based on each characteristic value measured in each measuring device in case one of three measuring devices is in an abnormal state. It is a figure which shows an example of the process which adjusts the setting value of a processing machine. It is a flowchart which shows an example of the process which adjusts the setting value of a processing machine. It is a figure which shows the result of having performed the calculation by FFT with respect to the time series data when abnormality has arisen in any one of a processing stand, any one of a processing machine, and any one of a measuring device. . The other embodiment of this invention is shown and it is a block diagram which shows the principal part structure of a manufacturing line system. It is a figure which shows the state of the power spectrum of FFT in the case where abnormality has arisen in the measuring device, and the case where it is assumed that the measuring device in which abnormality has arisen was adjusted. The other embodiment of this invention is shown and it is a block diagram which shows the principal part structure of a manufacturing line system.

Explanation of symbols

3a Processing table (processing equipment)
3b Processing table (processing equipment)
3c Processing table (processing equipment)
3d processing table (processing equipment)
3e Processing table (processing equipment)
3f Processing table (processing equipment)
3g processing table (processing equipment)
3h Processing table (processing equipment)
3i Processing table (processing equipment)
3j Processing table (processing equipment)
3k processing table (processing equipment)
3l processing base (processing equipment)
3a Processing table (processing equipment)
5a Processing machine (processing equipment)
5b Processing machine (processing equipment)
6a Measuring instrument (measuring device)
6b Measuring instrument (measuring device)
6c Measuring instrument (measuring device)
7 Adjustment device (specific device)
12 Information storage (storage device)
14 Failure rate calculation unit (individual failure rate calculation means / calculation means)
15 Histogram feature detector (distribution feature calculator / calculator)
16 Period information detection unit (period detection means)
17 Abnormality estimation part (specifying means)
18 Adjustment unit (change instruction means)
19 Output instruction section (output means)
21 determination part (determination means)
22 Setting part (changing means)
31 characteristic value 23 influence calculation unit (variation degree calculation means)
24 Period information detection unit 25 Abnormality estimation unit (identification means)
26 Adjustment unit (change instruction means)
27 Warning determination unit (adjustment execution determination means)
33 Variation tolerance information

Claims (12)

A specific device that accepts a characteristic value indicating the quality of a workpiece processed by any of the m processing devices from any of the n measuring devices and identifies an adjustment target,
M and n are natural numbers different from each other;
A storage device for storing the characteristic value received from the measuring device in association with the order in which the processing object having the characteristic value is processed;
By confirming whether or not the characteristic value stored in the storage device is within a range that can be taken by the characteristic value of the workpiece that satisfies the specified quality, the processed object to be processed has the specified quality. When it is determined that the processing object processed by the determining means and the determination means does not satisfy the specified quality, the processed object processed has the specified quality. If a characteristic value that falls outside the range of characteristic values that can be satisfied is defined as an abnormal characteristic value, an abnormal characteristic value that indicates whether the abnormal characteristic value appears in m cycles or n cycles a period detecting means for detecting periodicity, depending on the periodicity of the higher detected the abnormal characteristic value above Symbol period detecting means, an arithmetic unit and a specifying means for specifying the adjustment target, in that it comprises A specific device that features. The arithmetic unit is
Based on the characteristic value stored in the storage device, comprising a calculating means for calculating a statistical feature of the characteristic value related to the periodicity of the abnormal characteristic value,
Based on the statistical characteristics calculated by the calculating means, the period detecting means determines whether to detect the m periods or the n periods among the periodicity of the abnormal characteristic value to be detected. The identification device according to claim 1 , characterized in that: The characteristic value stored in the storage device is further stored in association with the measurement device number assigned to the measurement device that measured the characteristic value,
The calculation means divides a range of values that the characteristic value can take into predetermined sections based on the characteristic values stored in the storage device, and calculates the characteristics of the frequency distribution information of the characteristic values included in the respective ranges. Distribution feature calculation means for calculating distribution feature information to be shown;
An individual defect rate calculation means for calculating an individual defect rate that is a ratio of an abnormal characteristic value in each characteristic value measured for each measurement device with reference to the measurement device number. 2. The specific device according to 2 . The arithmetic unit is
If the processing apparatus is specified as the adjustment target by the specifying means, and changing means for changing the set value for defining the operation of the upper Symbol processing apparatus,
Change instruction means for instructing the change means to change the set value so that the frequency distribution information approaches the frequency distribution information based on the characteristic value of the processed object that satisfies the specified quality. ,
4. The specifying apparatus according to claim 3 , wherein the changing unit changes any set value of the m processing apparatuses in accordance with a change instruction from the change instructing unit. The change instructing means is a characteristic value obtained from a processing object whose frequency distribution information based on a post-change characteristic value of a processed object processed after the set value is changed by the changing means satisfies a specified quality. The specifying device according to claim 4 , wherein the change unit is instructed to change the set value until the frequency distribution information based on the method is approached. 6. The specifying apparatus according to claim 1, further comprising output means for outputting information indicating an adjustment target specified by the specifying means. The arithmetic unit is
Data indicating the relationship between the characteristic values measured by the measuring apparatus and the order in which the characteristic values are processed for each product corresponding to the characteristic values is regarded as time-series data, and the time-series data is the sum of spectral values in the case of frequency conversion, and a value indicating the variation of the entire upper Symbol characteristic value, based on the value of the spectrum in the frequency range corresponding to a particular period of non-normal characteristic values appear, to be adjusted It further comprises a variation degree calculating means for calculating a variation amount of the variation degree of the characteristic value before and after the adjustment,
The specifying device according to claim 6 , wherein the output unit outputs information indicating a variation amount of the variation degree calculated by the variation degree calculation unit. The storage device further stores variation tolerance information indicating the degree of variation of the characteristic value determined to be unnecessary for adjustment of the adjustment target with respect to the characteristic value measured by the measuring device,
The arithmetic unit is
The allowable variation information stored in the storage device, measuring a value indicating a characteristic value total variation degree measured by the constant unit, and beauty upper Symbol characteristic values Oyo, is processed for each product corresponding to each characteristic value Data indicating the relationship with the order in which the characteristic values are measured is regarded as time series data, and the adjustment target specified by the specifying means is based on the sum of spectrum values when the time series data is frequency-converted. obtains a threshold for determining whether it is necessary to adjust, compared to the magnitude of the spectrum at a specific frequency abnormal characteristic value appears in the case where the frequency converting the time-series data, and the threshold value, the specific particular claim 6, characterized in that it comprises an adjustment execution judgment hand stage determines whether to adjust the specified device as adjusted by means Location. The quality of the processing object processed by any one of the specific apparatus according to any one of claims 1 to 8 , m processing apparatuses for processing the processing object, and the processing apparatus. A processing system comprising: n measuring devices for measuring characteristic values indicating A method for controlling a specific device that receives a characteristic value indicating the quality of a workpiece processed by any of m processing devices from any of n measuring devices and specifies a correction target. ,
M and n are natural numbers different from each other;
A storage step in which the storage device stores the characteristic value received from the measuring device in association with the order in which the processing object having the characteristic value is processed;
The processing object processed by confirming whether or not the characteristic value stored in the storage step is within a range that the characteristic value of the processing object satisfying the specified quality can take . A determination step of determining whether or not satisfies a prescribed quality;
When the calculation unit determines that the processed object to be processed does not satisfy the specified quality by the determination step, it can be taken when the processed object to be processed satisfies the specified quality. If a characteristic value outside the range of the characteristic value is an abnormal characteristic value, a period for detecting the periodicity of the abnormal characteristic value indicating whether the abnormal characteristic value appears in m periods or n periods A detection step;
A control method for a specific device, wherein the calculation unit includes a specific step of specifying an adjustment target according to the periodicity of the abnormal characteristic value detected in the cycle detection step . A control program for operating the specific device according to any one of claims 1 to 8, wherein the control program for the specific device causes a computer to function as each of the means. The computer-readable recording medium which recorded the control program of the specific apparatus of Claim 11 .

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