JP2001121367A - Fraction defective estimating method and storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method and a system for extracting the assembly fraction defective coefficient of a product in a stage prior to manufacture of such as a design stage. SOLUTION: In this fraction defective estimating method and a system, the assembly fraction defective estimate of high accuracy is computed by an assembly fraction defective estimating program with the input data of assembling action, the property condition of an assembled object part and the condition of an assembling workshop having large influence on liability to a failure in assembly work.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to a method and system for evaluating the quality of products manufactured by assembling parts, such as home electric appliances and OA products. A method and system thereof.

[0002]

2. Description of the Related Art In the prior art, a method of estimating a cause of occurrence from an actually occurring defect phenomenon or failure phenomenon is mainly used. A well-known example of a method of estimating the cause of a defect from the content of a defect phenomenon occurring in a manufacturing stage is disclosed in JP-A-1-16763.
No. 1 and JP-A-6-196900. These are used to accumulate data on conventional failure results and their causes to determine the degree of correlation between failure patterns and failure causes.
It is intended to estimate the cause of failure. An example in which a similar method is used for failure diagnosis is disclosed in Japanese Patent Application Laid-Open No. 7-1361.
7 and JP-A-7-271587.

[0003] All of the above-mentioned known examples are intended to promptly and accurately carry out repairs and repairs based on the contents of the phenomena actually occurring when a failure phenomenon or a failure phenomenon occurs. This is a technique for estimating the direct cause based on

On the other hand, as a method of evaluating the quality of a product to be manufactured before an actual defect or failure occurs, FMEA (Failure Mode Effect A) used mainly in a product design stage is used.
nalysis) is known. In this method, the evaluator estimates "a possible failure phenomenon of each component constituting the product" and summarizes the failure phenomenon for each component in a table format. As a result, the evaluator itself can estimate "what effect on the product, if it occurs," and quality design without omission can be achieved.

[0005] FMECA (Failure Mode, Effect
& Criticalty Analysis)
It gives the probability (failure rate) of the failure phenomenon of each part estimated by the evaluator, and gives the importance of product failure estimated to be caused by the failure of that individual part. There is also a method to estimate the degree.

[0006]

However, in each of these conventional methods, since it is necessary to grasp most of the failure phenomena that can actually occur, it is necessary to accurately estimate the potential of the product to be defective. Can not.

Therefore, at present, a large number of manufacturing failures occur due to insufficient consideration, which is a factor of quality deterioration.

It is an object of the present invention to provide a method and a system for estimating a defective assembly potential of a product at a pre-manufacturing stage such as a design stage or a manufacturing process planning stage.

[0009] In this specification, single parts and subassemblies are collectively referred to as "parts". Therefore, the part assembling operation includes both the part assembling operation and the component assembling operation.
Parts or subassemblies to be assembled are collectively described as "assembled parts".

[0010]

SUMMARY OF THE INVENTION In order to achieve the above object, the present invention provides information relating to a factor affecting a probability that a human cannot perform an assembling operation reliably (hereinafter referred to as uncertainty). Based on this, it was decided to calculate an estimated value of the defective assembly rate.

Specifically, information on the operation contents or work contents of the part assembling work, information on the properties of the assembled parts,
The estimated value of the defective assembly rate is calculated based on the information on the properties of the parts to be assembled. In order to achieve the above object, a defect rate estimating method for estimating a defective assembly rate of a product according to the present invention includes, for each component constituting a product, property information of the assembled part, and the assembled part being assembled. A step of calculating and outputting an assembly failure rate for the entire product and for each assembling operation of the parts based on the property information of the parts to be assembled and work content information for assembling the assembled parts. In order to achieve the above object, a defect rate estimating method for estimating a defective product rate of a product according to the present invention includes: assembling work information in an assembling process of the product; Inputting assembled part information representing the nature of the assembled part and assembled part information representing the nature of the assembled part with respect to the assembled part, and a storage device storing in advance a defect rate coefficient for each standard assembly operation A step of extracting a defect rate coefficient based on the assembly work information, and a first defect rate correction coefficient based on the assembled part information from a storage device storing a defect rate correction coefficient for each part in advance. Extracting a second defect rate correction coefficient based on the part to be assembled, and correcting the extracted defect rate coefficient for each of the assembling operations based on the first and second defect rate correction coefficients. By calculating, every assembly work or this Calculating a defect rate for each of the assembled parts related to the work. Further, in order to achieve the above object, a defect rate estimating method for estimating an assembly defect rate of a product according to the present invention includes:
Assembling operation information in the assembling process of the product, assembling component information indicating a property of an assembling component assembled by the assembling operation, and an assembling component indicating a property of an assembling component with respect to the assembling component Inputting information and a failure rate coefficient based on the assembled part information from a storage device in which a failure rate coefficient corresponding to the property of each of the assembled parts is stored in advance. Extracting a first defect rate correction coefficient based on the assembling operation information and a second defect rate correction coefficient based on the component to be assembled, from a storage device in which the defect rate correction coefficients are stored in advance. Calculating a defect rate for each of the assembled components by performing a correction operation on the extracted defect rate coefficient for each of the assembled components based on the first and second defect rate correction coefficients. Further, in order to achieve the above object, a defect rate estimating method for estimating a defective product rate of a product according to the present invention includes: assembling operation information in an assembling process of the product; Inputting assembled part information indicating the nature of the assembled part and the assembled part information indicating the nature of the assembled part with respect to the assembled part, and a storage device storing in advance a defect rate coefficient for each standard assembly operation Extracting a defect rate coefficient based on the assembling operation information; and storing a first defect rate coefficient based on the assembled part information from a storage device in which a defect rate correction coefficient for each part is stored in advance.
Extracting a defect rate correction coefficient for the first and second failure rates and a second failure rate correction coefficient based on the component to be assembled. A step of calculating a defect rate for each of the assembling operations or for each of the assembled components related to the operation by performing a correction operation based on the rate correction coefficient. In order to achieve the above object, a defect rate estimating method for estimating a defective assembly rate of a product according to the present invention includes, for each component constituting a product, property information of the assembled part, and the assembled part being assembled. A step of calculating and outputting an assembling failure rate for the entire product and each assembling operation of the parts based on the property information of the parts to be assembled, the work content information for assembling the assembled parts, and the condition information of the assembly workplace. Have. Also,
In order to achieve the above object, a defect rate estimating method for estimating a product defect rate of a product according to the present invention includes assembling operation information in an assembling process of the product and properties of an assembled part to be assembled by the assembling operation Inputting part information indicating the nature of the part to be assembled with respect to the part to be assembled and work information on work conditions for assembling the product; Extracting a defect rate coefficient based on the assembling operation information from a storage device storing the rate coefficient; and storing a defect rate coefficient based on the assembled component information from a storage device storing a defect rate correction coefficient for each component in advance. 1
Extracting a second defect rate correction coefficient based on the workplace information based on the workplace information from a storage device storing a defection rate correction coefficient corresponding to workplace conditions in advance. Extracting the third defective rate correction coefficient, and correcting the extracted defective rate coefficient for each of the assembling operations based on the first, second, and third defective rate correction coefficients. Calculating a failure rate for each assembly operation or each assembly part related to the operation, and also calculating a failure rate for the entire product.

Further, according to the present invention, an operation type required to express the operation content of the component assembling operation is determined (downward movement operation, lateral movement operation, etc .; referred to as a standard assembling operation), and the determined operation type is determined. For each standard assembling operation, if the standard assembling operation is performed under predetermined "a certain worker condition, a certain part condition, a certain workplace condition" (referred to as a reference condition), the standard assembling operation is ensured. A numerical value (referred to as a standard assembly operation failure rate coefficient) indicating the magnitude of the probability of failure to perform is set.

[0013] In addition, the usability of the user interface is improved by expressing the evaluation object by a combination of the preset standard assembly operation elements.

Further, in order to further increase the accuracy of estimating the defective assembly rate, the present invention provides not only a standard assembling operation element expressing the assembling operation contents of the above-mentioned parts assembling work but also an assembling operation. The properties of the assembled parts and the parts to be assembled that affect the reliability are expressed by the following component condition correction factors, and an estimated value of the assembly failure rate is calculated based on the expressed component condition correction factors.
That is, a factor (hereinafter, referred to as a component condition correction factor) that affects the uncertainty of the assembly operation performed by a human among the properties of the assembled component and the component to be assembled is determined, and each of the determined factors is determined. A numerical value indicating the degree of influence of the influencing factor on the assembling operation (hereinafter referred to as a component condition correction coefficient) is determined for each influencing factor, and the assembling operation is performed with respect to the assembling operation for which the assembly defect rate is to be estimated. In addition to expressing the contents by the combination of the standard assembling operations, from among the preset component condition correction factors, those which correspond to the properties of the component to be assembled or the component to be assembled in the component assembling work are included. Select and express.

The present invention further provides a standard assembling operation element expressing the contents of the assembling operation of the parts assembling operation described above and an uncertainty in the assembling operation in order to further increase the estimation accuracy of the assembling defect rate. In addition to the component condition correction factors that affect the degree of failure, regarding the component assembly work for which the defect rate is to be estimated, a process to check whether the component The estimated value of the defective assembly rate is calculated by adding information on whether or not the assembly is provided.

The present invention further provides a standard assembling operation element expressing the contents of the assembling operation of the parts assembling work described above and an uncertainty of the assembling operation in order to further increase the accuracy of the estimation of the assembling defect rate. A component condition correction factor that affects the degree of failure, and a process of confirming whether or not the component assembling work has been correctly and appropriately performed in a post process of the component assembling work for which the defect rate is to be estimated is provided. In addition to the information as to whether or not there is a reflection of factors calculated in advance that affect the uncertainty of the assembling operation, such as the worker conditions of the assembly workplace where the parts are assembled, the conditions of the equipment, the environment, etc. An estimated value of the assembly failure rate is calculated based on a numerical value indicating the degree of influence of the workplace condition (hereinafter referred to as a workplace constant).

That is, according to the present invention, a failure rate coefficient for each standard assembly operation of an assembly part, a correction coefficient for each property of the assembly part, and a correction coefficient for each property of the part to be assembled are stored in advance. In advance, the information to be evaluated is expressed by a combination of predetermined standard assembly operations, and the combined information and the properties of the component to be evaluated and the component to be mounted are input. The corresponding defect rate coefficient of the standard assembling operation, the correction coefficient of the part to be assembled, and the correction coefficient of the part to be mounted are extracted, and the extracted defect rate coefficients are corrected for the correction coefficient of the part to be mounted and the correction coefficient of the part to be mounted. The assembly defect rate to be evaluated is calculated by adding the values corrected by the correction coefficient.

[0018] Alternatively, means for storing a defect rate coefficient for each standard assembly operation of an assembly part, a correction coefficient for each property of the assembly part, and a correction coefficient for each property of the part to be assembled, Is represented by a combination of predetermined standard assembly operations, and means for inputting the combined information and the properties of the component to be evaluated and the component to be mounted, and a corresponding standard assembly from the input information. The defect rate coefficient of the assembling operation, the correction coefficient of the assembling part, and the correction coefficient of the assembling part were extracted, and the extracted defect rate coefficients were corrected with the correction coefficient of the assembling part and the correction coefficient of the assembling part. Calculating means for calculating an assembly failure rate to be evaluated by adding the values.

Alternatively, the defect rate coefficient according to the standard assembling operation of the assembling part, the correction coefficient according to the property of the assembling part, the correction coefficient according to the property of the to-be-attached part, and the evaluation target are set to a predetermined standard assembly. When the combined information and the properties of the to-be-assembled part and the to-be-assembled part are input, the defect rate of the standard assembling operation is calculated from the input information. Extract the coefficient, the correction coefficient of the assembled part, and the correction coefficient of the part to be assembled, and add a value obtained by correcting each of the extracted defect rate coefficients with the correction coefficient of the part to be assembled and the correction coefficient of the part to be assembled. And a program for calculating an assembly defect rate to be evaluated.

In this case, a correction coefficient for each number of assemblies is stored in advance, and the defect rate coefficient is corrected by a correction coefficient corresponding to the number of assemblies to be evaluated to calculate an assembly defect rate, Correction coefficients corresponding to the presence / absence of a step of checking whether or not the processing has been properly completed are stored in advance, and if the evaluation target has a step of checking, the defect rate coefficient is corrected by the corresponding correction coefficient and assembled. It is preferable to calculate the defect rate.

[0021]

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram showing a process for estimating an assembly failure rate using a failure rate estimation system according to the present invention.

FIG. 1 shows the outline of a defect rate estimating system for estimating an assembly defect rate according to the present invention.

The calculation system shown in FIG. 1 stores a defect rate estimation system 10 of the present invention and information such as a part name, a part number, a material, a weight, and a unit price of a two-dimensional CAD system, a three-dimensional CAD system, and parts. And a design system 20 including a parts information database and the like.

The failure rate estimation system 10 includes a keyboard,
The input unit 1 includes a mouse, a pen input tablet, a storage medium, an input unit via a network, a display unit such as a display monitor, a printing unit, an output unit to another system via a network, and the like. Output means 2, calculation means 3 for performing the estimation processing of the present invention,
Storage means (external storage device) 4 for storing various information for calculating the defect rate. Calculation means 3
CPU 32, ROM 31 storing a predetermined program,
It comprises a RAM 33 for temporarily storing various data, an input / output interface unit 34, a bus line 35, and the like.

According to the present invention, the assembling work of the products and components to be evaluated is expressed by a combination of preset standard assembling operations, and the defect rate coefficients of each standard assembling operation are integrated to assemble. Calculate the likelihood of failure (failure rate).
Then, in order to improve the accuracy of estimating the defect rate, the number of assembling operations to complete an arbitrary assembling operation, and the conditions of assembling parts / assembled parts (for example, shape, dimensional accuracy, surface accuracy,
The likelihood of assembling failure (failure rate) is calculated by using the correction coefficient as a correction coefficient based on the size, weight, material, function, etc.), the conditions of the assembly workplace, and the presence or absence of a step for confirming the completion of assembly.

That is, the evaluation target is expressed by a combination of standard assembly operations, and the failure rate coefficient of each standard assembly operation is represented by the number of assembly operations, the conditions of the assembled parts and the parts to be assembled,
The defective rate is calculated by integrating the values corrected based on the conditions of the assembly workplace and the presence or absence of a process for confirming the completion of assembly.

As described above, the assembling failure rate of the part assembling work is checked by confirming the content of the operation of the assembling work, the properties of the assembling parts and the parts to be assembled, and whether or not the work is properly completed. The reason is determined by the presence or absence of the check process to be performed and the conditions of the workplace where the assembly work is performed.

If there is an assembling operation, there is naturally a potential (assembly failure rate coefficient) at which an assembling failure can occur.

As factors for increasing or decreasing the assembly failure rate coefficient of the assembling operation, there are the properties of the parts to be assembled and the parts to be assembled and the conditions of the workplace where the assembling work is performed.

With regard to the properties of the parts to be assembled and the parts to be assembled, for example, if the parts to be assembled or the parts to be assembled are difficult to assemble, the assembly failure rate coefficient of the assembling operation is amplified.

Similarly, the assembly failure rate coefficient of the assembling operation is affected by the conditions of the workplace where the assembling work is performed. For example, if the equipment used for the work is prone to failure, the failure rate coefficient of the assembling operation will be high even in the same assembling operation. Conversely, in the attaching operation, the defect rate coefficient of the assembling operation is also low.

In addition, as a defect finding potential, if there is a check step for confirming whether or not the assembling work has been properly completed after the assembling work step for which the assembling defect rate is to be estimated, if a defect occurs. Even if it does, the probability of eventually being defective is reduced by being discovered in the process and taking corrective measures.

From the above, in the present embodiment, the contents of the operation of the assembling work, which greatly affect the assembly failure,
Calculate the defect rate based on the properties of the parts to be assembled and the parts to be assembled, the presence or absence of a check process to confirm whether the work has been properly completed, and the conditions of the workplace where the assembly work is performed. And

For this reason, the storage means 4 stores a coefficient corresponding to the type of the assembling operation of the parts, a coefficient corresponding to the number of assembling operations (to be referred to as an assembling number) until an arbitrary assembling operation is completed, Coefficients corresponding to the properties (eg, shape, dimensional accuracy, surface accuracy, size, weight, material, function, etc.) of the parts to be mounted and the parts to be mounted, and confirming the completion of mounting in the post-process of mounting work A calculation program including a coefficient in the case where a process is provided, a coefficient corresponding to a condition of an assembly work site where the assembly work is performed, and an arithmetic expression for calculating the failure rate of the present system is stored.
Coefficients stored in these databases are set so as to be larger or smaller for items in which a defect is more likely to occur, and are preferably set based on actual data on the occurrence of assembly defects.

The following assembly failure estimation formula is used for the calculation program stored in the storage means 4. Note that f1 (), f2
() Represents a function.

Estimated value of defective assembly rate of parts assembling work = f1 (contents of assembling operation, nature of parts, workplace conditions, presence / absence of check process) (Equation 1) = f2 (defective rate coefficient by assembling operation) , (Parts correction coefficient, workplace coefficient, check process correction coefficient) (Equation 2) Therefore, for example, the likelihood of an assembly failure of a work composed of three operations that are continuous in time series is as shown in FIG. 1 in
The second assembling operation, the second assembling operation, and the third assembling operation, each of which is calculated by adding a value corrected by a component correction coefficient, a workplace coefficient, and a check process correction coefficient to the magnitude of the defect rate coefficient of each. Will be done.

On the other hand, there are various methods for expressing the correction by the component correction coefficient, the work place coefficient, and the check process correction coefficient for correcting the respective operations on the equations. For example, there are various methods such as a method of multiplying a failure rate coefficient for each assembly operation by a component correction coefficient, a work place coefficient, a check process correction coefficient, a method of adding / subtracting, or an exponential correction.

In addition, when a plurality of component correction coefficients, workplace coefficients, and check process correction coefficients are provided for a single assembling operation, all of the assembling operation-specific defect rate coefficients of the assembling operation include all the correction factors. A method of multiplying the component correction coefficient, the workplace coefficient, and the check process correction coefficient, and adding (including subtracting) all the component correction coefficients, the workplace coefficient, and the check process correction coefficient to the assembling operation failure rate coefficient of the relevant assembling operation. Method, etc.

In the present invention, any of the methods may be selected.
What is necessary is just to correct with a check process correction coefficient.

Then, in the present system, the information (a to d) shown in FIG.

First, information (a) expressing the assembling operation in terms of the standard assembling operation types prepared in advance and their order is input. That is, a symbol indicating a preset standard assembly operation element is input according to the order of the assembly operation. FIG. 3A shows a standard assembling operation in this embodiment and a part of an example of a symbol indicating the operation. The standard assembling operation is performed by selecting and setting an operation considered to be necessary for expressing the operation of the component assembling operation. In the present embodiment, as shown in the figure, “downward movement”, “lateral movement” Several types of standard assembling operations such as "press-fit" are set. The operation in the part assembling operation for which the failure rate is to be estimated is expressed from the preset standard assembling operation. For example, if the assembling operation of a part is "moving downward, then moving laterally, and finally press-fitting", the information of the assembling operation of the assembling operation of the part to be input is , Down movement, lateral movement, and press-fit, which are represented by three standard assembling operation elements.
Becomes

Next, a condition (b) having a property that affects the uncertainty (probability of occurrence of a failure) of the assembling operation with respect to the assembling part and the assembling part in the assembling operation is input.
For example, a shape, dimensional accuracy, surface accuracy, size, weight, material, function, and the like are input. That is, factors that affect the uncertainty of the assembling work performed by a person are selected from the properties of the assembled parts and the parts to be assembled, and are input using a preset symbol indicating the factors. If necessary, information indicating the characteristics of the factor (for example, a weight value) may be input. FIG. 3B shows a part condition correction factor and a part of an example of a symbol indicating the factor in this embodiment. In the present embodiment, for example, as shown in the figure, "micro holes", "small holes",
"Assembly completion determination is difficult" (shape and properties of parts or parts to be assembled are visually, tactilely or audibly difficult to judge whether or not the parts have been assembled), "Contact impossible Several types of component condition correction factors are set, such as "there is a surface" (there is a portion that is not allowed to be in contact with the assembled component or the assembled product in terms of function and performance).

Next, information (c) as to whether or not there is a step for confirming whether or not the assembling work has been properly completed is input.
If there is a step of confirming, the likelihood of an assembly failure determined by the assembling operation and component conditions is reduced.

Next, regarding the assembled part and the part to be assembled in the part assembling operation, the uncertainty of the assembling operation such as the condition of the worker in the assembling work place, the condition of the equipment, the environment, etc., in which the part assembling operation is performed. Enter information (d) on factors affecting the degree. In this case, information indicating the characteristics of the factor (for example, the temperature and humidity of the workplace, the production lot, the speed of the production line, etc.) may be input as needed. In this embodiment, in order to simply calculate the estimated value of the assembly failure rate for each workplace, the calculation is performed using a numerical value (workplace constant) indicating the average likelihood of assembly failure in the workplace. Here, the workplace constant is a magnification value that indicates how many times the failure rate when a certain predetermined assembly work (referred to as a reference work) is performed in a reference workplace. is there. In this embodiment, the workplace constant is directly input. However, if the workplace constant for each workplace is stored in advance in the storage unit 241 (workplace constant database), information for specifying the workplace may be input. Good.

The order in which these pieces of information are input is not limited to the present embodiment, but may be any order.

In the present system, when these inputs are completed, the CPU 32 executes the calculation program stored in the storage means 4, and stores the coefficients corresponding to the input information from the storage means 4 into the RA.
The estimated value of the defective assembly rate of the part assembling work is output using the extracted information and the number (2).

The internal processing of this system will be described in more detail with reference to the functional block diagram shown in FIG.

In the defect rate estimation system 10 shown in FIG.
The calculation means 3 shown in FIG. 1 is a data fetching unit 34 for fetching design information and the like from the design system 20, a program execution unit 32 for executing an estimation process of the present invention, and a calculation program storage unit for storing a program for the estimation process of the present invention. 31, an information generating unit 36 for generating new information based on an instruction on the screen displayed on the display unit 2, and a calculating unit 3 comprising the storage unit 4 as various databases. . The information generating unit 36 may be executed by the program executing unit 32.

The contents of each database stored in the storage means 4 are as follows.

Failure rate coefficient database 2 for each standard assembly operation
Reference numeral 11 denotes a coefficient “standard assembling operation” which is set for each type of standard assembling operation such as “downward movement” and “lateral movement” and indicates the likelihood of a work failure of each assembling operation. Another defect rate coefficient "is stored. FIG. 4 shows a data example of the failure rate coefficient DB 211 according to the standard assembling operation in this embodiment. The failure rate coefficient for each standard assembling operation indicates the probability of the work operation becoming defective when the work of each single standard assembling operation is performed under the standard condition. Is set relatively based on the magnitude of the probability of the work failure. In the present embodiment, based on the “downward movement” which is considered to be the simplest operation that is unlikely to cause an assembly work defect,
The failure rate coefficient for each standard assembly operation is set. Specifically, as shown in FIG. 4, the failure rate coefficient for each of the assembling operations of “downward movement” is set as the reference value 1, and the other standard assembling operations are “downward movement”.
A standardized assembling operation-specific failure rate coefficient is set as a multiple that indicates how many times the failure is likely to occur. For example, the failure rate coefficient by assembling operation for “lateral movement” shown in FIG. 4 is 2, which means that “lateral movement” is likely to be twice as defective as “downward movement”.

The operation order correction coefficient database 221 stores, in the case of an assembly operation represented by a plurality of standard assembly operation elements,
As the number of operations increases, the complexity of the operation increases, and accordingly, the “basic coefficient of failure rate by assembly operation” of each operation is increased according to the order of the individual assembly operations constituting the assembly operation. Coefficient for operation "operation order correction coefficient" is stored. FIG. 5 shows an example of data in the database. FIG.
In this example, the operation order coefficient is set for each operation order, such as the operation order coefficient of the first operation is 1, the second is 1.1, and the third is 1.2. As another example, the coefficient calculation formula including the operation order is used as the database 221 with the operation order as a variable.
You may have it. For example, if the operation order is n, an expression such as an operation order correction coefficient = n × 1.1 (Equation 3) is stored in the database as data, and this expression is used to calculate an estimated value of the assembly defect rate. Is read out, the operation order coefficient is calculated, and used to calculate the estimated value of the assembly failure rate.

Further, the likelihood of occurrence of a work defect in each assembling operation is affected by the condition of the part to be assembled, the mating part to be assembled, and the peripheral part thereof. Therefore, the part condition correction coefficient database 231 is provided. . That is, the likelihood of a work defect occurring in each assembling operation varies depending on the conditions of the properties of the parts to be assembled, such as the size, weight, material, and number of parts to be assembled. In addition, it also changes depending on the property conditions of the assembled product. From the above, the assembly component condition correction coefficient database 231 and the assembly component condition correction coefficient database 232 have important factors for the assembly component property factor and the assembly An accessory property factor is set, and a component condition correction coefficient for correcting the failure rate coefficient for each standard assembly operation is stored for each factor. FIG. 6 shows an assembled component condition correction coefficient database 23.
1 shows an example of data of a component condition correction coefficient database 232. As shown in the figure, a correction coefficient value is set and stored for each correction factor. Further, similarly to the example in the operation order correction coefficient database 221 described above, instead of the correction coefficient value,
The coefficient calculation formula may be stored in the main database 231. When calculating the estimated value of the defective assembly rate, this formula is read out, the correction coefficient is calculated, and used for calculating the estimated value of the defective assembly rate. The structure of the assembled component condition correction coefficient database 231 and the assembled component condition correction coefficient database 232 may be different from each other.

In addition, in the present embodiment, the work probability of each assembly operation greatly varies depending on the conditions of the workplace where the assembly work is performed.
1 is provided. The workplace constant database 241 stores constants indicating the average likelihood of failures in the workplace. In this embodiment, in each workplace, a reference work (a downward movement work in this embodiment) is performed under a condition other than the workplace conditions under a reference condition.
The assembly failure rate in the case of performing the above is defined as the workplace constant. FIG. 7 shows an example of data in the workplace constant database. In this example, workplace A has a workplace constant of 5 (ppm) and workplace B has a workplace constant of 10 (p).
pm), which means that in each workplace, the failure rate of down-moving work is 5 (ppm) in workplace A and the workplace B 10 (ppm). That is, the workplace constant can also be said to be an index indicating the reliability of the assembly work in each workplace. This workplace constant is based on the conditions of the worker who performs the assembly work, the conditions of the tools and jigs used for the assembly work, the facilities such as the production line equipment, the temperature of the workplace of the assembly work,
It is a constant reflecting the influence of work environment conditions such as humidity, brightness, noise, etc., production conditions such as line speed, number of production lots, etc.

Check process correction coefficient database 25
If there is a process of checking whether or not the part assembling work is performed properly after performing the part assembling work for which the assembly defect rate is to be estimated, the defect rate is reduced because of this. A correction coefficient for reflection is stored. FIG. 8 shows a data example of the check process correction coefficient database 25. Check process correction coefficient coefficient value is 0.2
In the case of the above, this indicates that 80% of the failures in the assembling work caused by the checking process can be found in the checking process. If the defect extraction rate differs depending on the type of the check operation, a check process correction coefficient may be set for each different check process.

The constant database 26 stores coefficients and constants other than the above.

Input data / calculation result data storage unit 27
Stores the input data used for calculating the defect rate by the calculation program and the result calculated by the calculation program based on the input data.

By the way, as shown in FIG. 10, the correction coefficient stored in each database is set so that the correction coefficient value also changes according to the change of the characteristic value of the correction factor (for example, the weight value in the case of a weight factor). May be. That is, depending on the item of the correction factor, the correction coefficient may take a constant value regardless of the characteristic value of the correction factor as shown in Example 1 (e.g., difficult to determine the completion of assembly, non-contactable surface, etc.). .), The correction coefficient value is changed in a step function as in Example 2 (multipoint matching, etc.), or the correction coefficient value is changed in a linear manner as in Example 3 (weight, etc.). ) And other changes may be made. In this case, by inputting necessary characteristic values, coefficients are calculated based on the function shown in FIG.

FIG. 9 shows a failure rate estimation system 10 according to the present embodiment.
6 is a flowchart for calculating an estimated value of an assembly failure rate in a part assembling operation according to the first embodiment.

First, the work contents of the part assembling work for which the assembly failure rate is to be estimated are analyzed (step 5).

Next, the contents of the analysis performed in step 5 are expressed by a standard assembly operation element symbol and a component correction element symbol determined in the assembly failure rate estimation value calculation program of the failure rate estimation system 10 (step 6). ).

Next, in step 6, the contents of the part assembling work for which the assembly failure rate is to be estimated, which are represented by the standard assembling operation element symbols and the component correction element symbols, are input. Further, the presence or absence of the check process and the workplace constant are input (step 7).

That is, the failure rate estimating system 10 is started up, and the assembly failure rate estimation value calculation program stored in the calculation program storage unit 31 of the calculation means 3 is started.
The above-described input information shown in FIG. 1 is input using the keyboard 11, the mouse 12, the pen input tablet 13, and the like of the input unit 1. In this embodiment, in order to prompt easy input,
An input interface screen is displayed on the display device 21 of the output means 1, and the above information is input while watching the input interface screen. FIG.
2 and 13 show examples of the input interface screen. In this step, if there is a check process for confirming whether or not the assembling work has been properly performed, the information input of “check process exists” is input. Further, a workplace constant of a workplace that performs a part assembling work for which an assembly failure rate is to be estimated or information for specifying the workplace where the assembly is to be performed is input. If there is no need for component correction, there is no need to input a component correction element symbol.

On the other hand, the system according to the present embodiment can calculate the workplace constant as follows. As described above, the workplace constant is, in the present embodiment, the assembly failure rate when only the downward movement operation is performed in the workplace without any component correction condition to be corrected. All the failure rate coefficients for each operation are determined based on the likelihood of failure of the reference operation (downward movement operation) in the reference state as a reference (coefficient value 1). The same applies to the correction coefficient for correcting the failure rate coefficient for each operation. The likelihood of occurrence of a failure in the reference operation (downward movement operation) in the reference state is set as a reference (coefficient value 1).
Has been determined. From the above, it is possible to analyze the contents of assembly work in the assembly work with many assembly records in the past, and if there is actual defect rate data, the workplace constant of the workplace where the assembly work with the assembly record was performed Can be calculated. In the system according to the present embodiment, a menu screen is displayed on the display device 21 of the output means 1 after the assembly failure rate estimation value calculation program is started, and either "estimation of assembly failure rate" or "calculation / registration of workplace constant" is selected. You can choose. When "calculation / registration of workplace constant" is selected, an input interface screen (FIG. 13) is displayed on the display device 21 of the output means 1, and a code (such as a name) for specifying a workplace to be registered is entered there. Input, and then, on the input interface screen (FIG. 12), enter the contents of the assembly work that has been performed in the workplace using standard assembly operation element symbols and component correction element symbols, and confirm that the assembly work has been performed properly. If there is a check step for confirming whether or not there is a check step, the information of "check step exists" is input, and further, the actual failure rate of the work is input. Thereby, the workplace constant of the workplace is calculated. If there is more than one work that has a poor track record, enter the above data for all of the work to obtain a workplace constant for each work, and take a simple average of the calculated workplace constants. Calculate the workplace constant of In this embodiment, the workplace constant of the workplace is calculated by a simple average of the obtained workplace constants.

When the above input is completed, step 7
Based on the information input in step (1), an estimated value of the defective rate of the part assembling work is calculated by the assembly defective rate estimated value calculation program (step 9). That is, the processes (1) and (2) are performed.

(1) The following various coefficients and constants are read from various databases based on the input information.

The failure rate coefficient of each assembly operation is read out from the failure rate coefficient database 211 for each assembly operation based on the input standard assembly operation element symbols. Further, an operation order correction coefficient corresponding to the order of each operation is read from the operation order correction coefficient database 221.

The component condition correction coefficient of each correction element is read out from the component condition correction coefficient database 231 or the component correction coefficient database 232 based on the input component condition correction element symbol.

When the information of “with check process” is input, a check process correction coefficient corresponding to the information is read from the check process correction coefficient database 25.

If the information for specifying the assembly workplace is input as described above, the workplace constant of the corresponding workplace is read from the workplace constant database 241.

(2) Generate a calculation model. Based on the various coefficients and constants input or read, a calculation formula based on a calculation model as shown in FIG. 11 is generated. At this time, a correction method using various correction coefficients, for example, information on whether to multiply, add, or subtract correction coefficients may be registered in the various correction coefficient databases for each correction factor, or may be calculated by a calculation program. Above, it may be programmed to change the correction method according to the type of the correction factor. This embodiment is an example of the latter. For example, a program is created or a coefficient value is determined based on a rule that all correction coefficients are added. In this embodiment, for each operation order, the defect rate coefficient of the operation is corrected by the component condition correction coefficient for correcting the operation (when there is no correction factor, no correction is performed). Add all the defect rate coefficients, and if it is "check process", multiply by the check process correction coefficient to calculate the overall defect rate coefficient, multiply it by the workplace constant, and An estimate of the assembly failure rate at the workplace is calculated.

Next, the estimated value of the defective assembly rate calculated in step 8 is output to the display device 21 or the printing device 22 of the output means 2 or the output means 23 to another system (step 9). FIG. 14 shows an example of an output screen to the display device 21.

As described above, the system according to the present embodiment can calculate the estimated value of the defective assembly rate in the component assembling work. The above description is an example of calculating the estimated value of the defective assembly rate of the assembling work of the single assembling work process. By inputting the information of the assembling operation and the information of the component condition correction element, etc., as described above for the work of each of the constituent work steps, the estimated assembly defect rate of each of these work steps is reduced. It is possible to calculate the estimated value of the defective assembly rate for the entire assembling work of the product by summing them.

Information on the presence or absence of the check step is not always necessary, and a desired defect rate can be calculated without the information. Further, if the workplace constant is set in advance, the information becomes unnecessary.

Next, using a specific part assembling operation (connector cable assembling operation) shown in FIG. 15 as an example, a method of calculating an estimated value of an assembly defect rate in the part assembling operation will be described with reference to a flowchart shown in FIG. explain. The table shown in the lower part of FIG. 15 is an example of an input / output interface screen, and is an example in which items to be analyzed are displayed in an input column. In this example, it is possible to analyze the work to be evaluated and input the analysis result while viewing the input / output interface screen by activating the program for calculating the estimated value of the defective assembly rate.

First, when the parts assembling work is analyzed (Step 5), the following two works are performed for assembling the connector cable whose assembly failure rate is to be estimated in FIG.

(1) Connector insertion. However, the insertion force is large.

(2) Shaping of Cable Also, the conditions of the parts to be assembled and the conditions of the parts to be assembled during each operation are analyzed. The analysis is performed on the items in the input fields of the input / output interface screen. First, regarding the operation of (1) "Connector insertion, but insertion force is large."
It is also analyzed that "assembly completeness determination is difficult" because "the installation completion state cannot be visually confirmed due to obstacles". There is no component condition to be corrected for the next operation (2) “Cable shaping”.

Next, the work analyzed in step 5 is expressed using standard assembly operation element symbols and component correction element symbols (step 6). First, the assembling operation is represented by a standard assembling operation element symbol, and a necessary component condition correction element symbol is given to each of the operation elements. In the example of FIG. 15, the following is performed.

(1) “Connector insertion, but insertion force is large.” Is expressed as “move laterally (symbol: ←) and press-fit (symbol: C)” as a standard assembly operation element. In other words, the first operation is “lateral movement (symbol: ←)”
The second operation is “press-fit (symbol: C)”.

Next, as the component condition correction element, the first component condition correction element of "lateral movement (symbol: ←)" is expressed as "micro hole (symbol: ht)". In addition, since “the mounting completion state cannot be visually confirmed due to an obstacle”, the component condition correction element of “press-fitting (symbol: C)” is expressed as “mounting state confirmation is difficult (symbol:?)”. Although the second operation requires an operation order correction, the correction is automatically performed by the calculation program of the present embodiment as described above.

(2) “Cable shaping” is expressed as “shaping (symbol: d)” as a standard assembly operation element. Since the component condition correction element of this operation has no function other than the operation order correction, there is no need to particularly express it. Since this operation is the third operation, the operation order is automatically corrected by the calculation program.

Next, the element symbol expressed in step 6 is input to the program for calculating an estimated value of assembly defect rate (step 7). For example, as shown in FIG. 15, an assembly part name is entered in the part name column, and a standard assembly operation element and a component condition correction element are input, one line per operation order.

In the example shown in FIG. 15, first, a standard assembly operation element symbol “←” of the first operation in the operation order is input, and a component condition correction element “ht” of the operation is entered in the column of the condition of the product to be mounted. In the "Micro / Small Hole" field. Next, in the second line, the standard assembly operation element symbol “C” of the second operation in the operation order is input, and the component condition correction element “?” In the "Attachment completion judgment" field.

Next, on the third line, the standard assembly operation element symbol "d" for the third operation in the operation order is input. Since there is no component condition correction element to be corrected for this operation, no input is made for the component condition correction element.

In this example, there is no check step for confirming whether or not the assembling work has been properly performed, so that no information is input regarding the “check step”.

If the workplace constant of the workplace to be evaluated is stored in the database, the workplace to be evaluated is input. FIG. 15 shows an example in which the workplace name is input as “A”. Even if the workplace constant of the workplace to be evaluated is not stored in the database, the workplace may be entered if the workplace constant of the workplace considered to be similar to the workplace to be evaluated is stored in the database. If it is known, the workplace constant may be directly entered in the workplace constant input field.

Next, an automatic calculation is performed by an assembling defect rate estimated value calculation program (step 8). A coefficient value corresponding to each symbol input in the input field of the input / output interface screen of FIG. 15 is read out from various databases, and based on the coefficient value, a defect indicating the likelihood of occurrence of the operation failure for each operation. A rate factor is calculated. For example, the failure rate coefficient is calculated using Equations 4 and 5.

[0088]

(Equation 4)

[0089]

(Equation 5)

Then, as shown in the input / output interface screen of FIG. 15, the failure rate coefficients are calculated for each operation sequence, and the sum of the calculated failure rate coefficients is a failure rate coefficient indicating the likelihood of failure in the connector cable assembling work. The coefficient is 30. on the other hand,
The workplace constant of the workplace “A” is read from the workplace constant database 241 and multiplied by it to calculate an estimated value of the assembly failure rate of the work in the workplace. In this example, the workplace constant of the workplace “A” is 5 ppm, and the estimated failure rate of the work in the workplace “A” is 150 ppm.

The reading of the coefficient values from the various databases may be performed in advance at the time of starting up the assembling failure rate estimation value calculation program and may be stored in the RAM 33. In this case, each coefficient value is read out from the RAM 33 at the time of calculation, so that it is not necessary to access the external storage means 4 each time at the time of calculation, and the calculation time is shortened.

Next, the result of calculation of the estimated value of the assembly defect rate is output by the assembly defect rate estimation value calculation program of the defect rate estimation system 10 (step 9).

In the example of FIG. 15, a component type can be input as an assembly part condition and an assembly target condition as needed. This is for the following reason.

There are two major types of assembly failure: incomplete assembly and component damage / dirt.

"Incomplete assembly" is mainly caused by a deviation (variation in operation accuracy) or a mistake in a work operation of a human. As a failure example of this kind, in the case of connector insertion work, "incomplete insertion (rear) The connector is not completely inserted) or "reverse insertion of the connector".

On the other hand, "part damage / dirt" is mainly caused as a result of the above-mentioned fluctuation (variation in operation precision) of human work or mistakes, but is regarded as "part damage / dirt". Whether or not it occurs depends on the type of part even with the same degree of damage and dirt. For example, a design component exposed to the outside is a component type that can be defective even with a slight scratch or dirt, unlike other components inside the product, for example. In other words, depending on the component type, that is, the function of the component,
Even if the same external force (stress) acts on the part, it is not uniform whether it becomes defective.

Therefore, in this embodiment, a coefficient value indicating the strength (drag force) of each component type with respect to the external force of the component type is stored in the database, and the component type of the assembled component and the component to be assembled can be input. The strength of the component to be evaluated against external force (drag) is compared with the magnitude of the external force (stress) acting on the component during the assembling operation of the component. The defect rate was calculated. As described above, in the present embodiment, the failure rate is estimated in consideration of not only the failure of “incomplete assembly” but also the failure of “component damage / dirt” as the failure of assembly.

Next, another embodiment of the defect rate estimation system of the present invention will be described.

Basically, the work operation is considered to be a repetition of "positioning operation" and "operation after positioning". 17 in FIG.
The example of the assembling work "the downward moving insertion work into the circular hole of the cylinder" completed by the various kinds of assembling operations has been described. As shown in FIG. 17, this operation is a “downward movement operation”, and the contents are composed of a “positioning operation” and an “operation after positioning”. FIG. 18 shows an example of an assembling operation “cover attaching operation” completed by two types of assembling operations. This work consists of two standard operations, “moving diagonally downward” and “rotating moving”. Each standard operation consists of “positioning operation” and “operation after positioning”. I understand.

Among the standard operations, there are operations only for “positioning operation” such as an operation for holding parts and an operation for shaping an electric wire, but many operations are performed after “positioning” and then “positioning operation”. Of operation. FIG. 19 shows an example of the configuration of the work process. For example, the assembling work of the component 1 in the process 1 in FIG. 19 is composed of three operations. From the first operation to the third operation, "positioning" and "operation after positioning" are performed for each operation. repeat.

As described above, the work is composed of “positioning” and “operation after positioning”, and the work failure is large. The work is divided into two types: those that occur during the positioning and those that occur during the operation after the positioning. It became clear from our research.

First, a defect that occurs at the time of positioning is a defect that occurs due to a variation (inaccuracy) in the component position or component attitude during positioning. If the operation is shifted to this operation with insufficient positioning, a defect (incomplete work) that cannot be performed will occur. However, depending on the strength of the connecting parts of the assembled parts and the parts to be assembled and the operating force of this operation, Causes poor joint damage and poor deformation. Normally, the worker confirms that the positioning is sufficient and then moves to the operation after positioning.If the positioning is insufficient, correct the positioning before moving to this operation, and then Move to the operation of. The above-mentioned defects are particularly likely to occur when it is difficult to confirm the positioning, for example, when the work site is difficult to see, or when the operator forgets to confirm the positioning.

In addition, assembling defects caused by the operation after positioning include those caused by poor control of the trajectory of the operation after positioning, that is, those caused by the dispersion of the operation trajectory and those caused by insufficient operating force after the positioning. There is. The defective assembly caused by the poor control of the trajectory of the above-described operation after positioning is particularly frequent during long-distance operation. On the other hand, assembling failure that occurs due to insufficient operating force after positioning is when the operating force required for assembling cannot be exhibited, especially when the required operating force such as press-fitting operation is large, or due to the operation and the property conditions of parts etc. The occurrence frequency is high when the predetermined operating force cannot be exerted.

Thus, in a second embodiment, an example suitable for evaluating each of these defective potentials will be described.

This system has almost the same configuration as the failure rate estimation system (FIG. 1) shown in the first embodiment, but has a failure rate coefficient database 211 for standard assembly operation and a correction coefficient database 231 for assembly part condition. The information to be stored and the calculation program for handling the information are different.

FIG. 21 shows information stored in the standard assembling operation failure rate coefficient database 211 and has the following features.

The first feature is that, for one standard assembling operation, three types of defect rate coefficients are set, namely, the above-described defective defect rate coefficient of positioning error, defective coefficient of locus control defect, and defective coefficient of required operating force defect. On the point. The second feature is that, even in the same type of operation, an operation that requires a positioning accuracy higher than a certain reference and an operation that does not require a positioning accuracy are distinguished from each other to be the operation type of the standard assembly operation. For example, even in the same downward movement, the setting of the defective positioning defect rate coefficient is changed between the downward movement with high positioning accuracy and the downward movement with no positioning accuracy. Note that FIG.
In the example, each defect rate coefficient is set as "1" (reference) as the positioning defect rate coefficient in the case of "downward movement with high positioning accuracy". In other words, "downward movement with high positioning accuracy"
Is set to a multiple that indicates how many times the position is likely to be defective with respect to the potential of the positioning defect.

On the other hand, FIG. 22 shows information stored in the assembled component condition correction coefficient database 231 and the assembled component condition correction coefficient database 232. , Three types of correction coefficient values are set and stored.

In addition, a calculation program that handles such information has the following features. As described above, the potential of the trajectory control failure during the post-positioning operation and the potential of the insufficient operating force failure become particularly high under certain correction conditions. Therefore, the calculation program according to the present embodiment performs the following operations for configuring the work to be evaluated.
Only when a certain correction element is added, the trajectory control failure occurrence potential or the operating force shortage failure occurrence potential is calculated. Specifically, for an operation to which a correction element indicating a long section operation is added, a trajectory control failure occurrence potential is calculated in addition to a positioning failure potential. For the operation to which the correction element shown is added,
In addition to the positioning fault potential, the operating potential shortage fault occurrence potential was calculated. That is, based on the type of the correction element added to the assembling operation, it is determined whether or not the operation has a trajectory control failure occurrence potential or an operation force shortage failure occurrence potential in addition to the positioning failure potential, and positioning is performed as necessary. In addition to the fault occurrence potential, the trajectory control fault occurrence potential or the operating force shortage fault occurrence potential was calculated.

Next, a method of calculating an estimated value of the defective assembly rate in the part assembling work will be described with reference to the specific part assembling work shown in FIGS. (1) to (4) in FIGS.
This is the operation of inserting the cylindrical assembly part into the round hole, but changing the conditions of the parts to be assembled. (1) is a downward moving operation in which the diameter of the insertion guide portion (the outer diameter of the chamfered portion) of the round hole as the portion to be assembled is small, that is, high positioning accuracy is required. On the other hand, (2) has a large diameter of the insertion guide part (outer diameter of the chamfered part) of the round hole as the part to be assembled
That is, this is a downward moving operation that does not require high positioning accuracy and does not require care for positioning. (3) is a downward moving operation where the diameter of the insertion guide part (outer diameter of the chamfered part) of the round hole that is the part to be assembled is small and high positioning accuracy is required.
This is a downward moving operation in which the depth of the round hole is deeper and a long section inserting operation is required. (4) is a downward movement work in which the diameter of the insertion guide part (outer diameter of the chamfered part) of the round hole, which is the part to be assembled, is large, and high positioning accuracy is not required and there is no need to worry about positioning. This is a downward moving operation in which the clearance between the insertion diameter a and the hole diameter c is small, and an insertion force that is tighter than the normal one is required. First, FIGS.
A method of calculating the defect rate coefficient indicating the defect occurrence potential of each of the above (1) to (4) will be described.
It should be noted that there is no check step in the post-process for the work examples (1) to (4).

First, the work in FIG. 23 (1) is a downward movement requiring high positioning accuracy, and there is no correction element indicating a long section operation or an operation requiring a large operating force. (Symbol: ↓ '). When the work analysis result is input, the corresponding defective positioning defect rate coefficient is read out from the assembling operation defective rate coefficient database 211. In this case, "movement under positioning" (symbol: ↓ ')
Therefore, from FIG. 21, the defective positioning defect rate coefficient is “1”. Further, in this case, since the correction element indicating the long section operation or the operation requiring a large operation force is not input, the trajectory control failure rate coefficient and the operation force shortage failure rate coefficient are not calculated. As described above, the total defect rate coefficient of the operation in FIG. 23A is “1”. A specific failure rate is calculated by multiplying the failure rate coefficient “1” by a previously input workplace constant.

Next, the operation shown in FIG. 23 (2) is a downward movement which does not require positioning accuracy because the diameter of the insertion guide portion is large, and there is no correction element indicating a long section operation or an operation requiring a large operation force. The work analysis is simply a “downward movement” (symbol: ↓). When the work analysis result is input, the corresponding defective positioning defect rate coefficient is read out from the assembling operation defective rate coefficient database 211. In this case, "Move Down"
Since (symbol: ↓), the poor positioning defect rate coefficient is “0.1” from FIG. Further, in this case, since the correction element indicating the long section operation or the operation requiring a large operation force is not input, the trajectory control failure rate coefficient and the operation force shortage failure rate coefficient are not calculated. From the above, the total failure rate coefficient of the operation in FIG. 23 (2) is “0.1”. A specific failure rate is calculated by multiplying the failure rate coefficient “1” by a previously input workplace constant.

Next, the operation shown in FIG. 24 (3) is a downward movement requiring a high positioning accuracy with a small diameter of the insertion guide portion and a long section insertion, so that the operation is "positioning downward movement" (symbol: ↓ '). ), The correction element is “Long section insertion” (symbol: l
h) and work analysis. When the work analysis result is input, the corresponding defective positioning defect rate coefficient is read out from the assembling operation defective rate coefficient database 211. In this case, since it is “movement under positioning” (symbol: ↓), FIG.
From 1, the poor positioning defect rate coefficient becomes “1”. Furthermore,
In this case, since the correction element for the long section insertion has been input, the assembling part condition correction coefficient database 232 indicates
The positioning failure correction factor coefficient “1” for long section insertion is read (see FIG. 22). Further, since it is a long section insertion, the trajectory control defect rate coefficient is calculated. The locus control defect rate coefficient “1” is read from the assembly-operation-specific defect rate coefficient database 211 (see FIG. 21). Next, the trajectory control failure correction coefficient “2” by the long section insertion correction is read from the assembled component condition correction coefficient database 232 (see FIG. 22).
In this case, since the correction element indicating the operation requiring a large operating force is not input, the calculation of the operating force shortage defect rate coefficient is not performed. From the above, the defect rate coefficient of the operation of FIG. 24 (3) is “1” when the positioning defect rate coefficient is 1 × 1 and “2” when the trajectory control defect rate coefficient is 1 × 2. 3 ". A specific failure rate is calculated by multiplying the failure rate coefficient “3” by a previously input workplace constant.

Finally, the operation shown in FIG. 24 (4) is a downward movement which does not require positioning accuracy because the diameter of the insertion guide is large and there is no correction element. ), The correction condition is “fit tight”, so that the operation is “downward movement” (symbol: ↓), and the correction element is analyzed as “fit tight” (symbol: th).
When the work analysis result is input, the corresponding defective positioning defect rate coefficient is read out from the assembling operation defective rate coefficient database 211. In this case, "downward" (symbol:
Since ↓), the defective positioning defect rate coefficient is “0.1” from FIG. Furthermore, in this case, since the correction element of “fit tight” is input, the “fit tight” is obtained from the assembled component condition correction coefficient database 232.
22 is read (FIG. 22).
reference). Further, since the operation is "fit tight", that is, the operation has a large operating force, the inferior defect rate coefficient of the operating force is calculated.
The failure rate coefficient "1" is read from the failure rate coefficient database 211 for each assembly operation (see FIG. 21). Next, from the assembled component condition correction coefficient database 232,
An operation force shortage defect correction coefficient “5” due to the “fit tight” correction is read (see FIG. 22). In this case,
Since the correction element indicating the long section operation has not been input, the calculation of the trajectory control defect rate coefficient is not performed. From the above, FIG.
4 (4), the defect rate coefficient of the positioning defect defect coefficient was 0.1 × 1 at 0.1 × 1 and “5” at 1 × 5 for the insufficient operating force defect coefficient. It becomes "5.1". The specific defect rate is calculated by adding the defect rate coefficient “5.1” to
It is calculated by multiplying a previously input workplace constant.

FIG. 20 shows an output example of the system shown in the second embodiment, in which the defect rate coefficient for each of the aforementioned positioning failure, trajectory control failure, and insufficient operating force is displayed.

According to the method of the second embodiment as described above, it is possible to finely estimate the defect rate by dividing the respective potentials of positioning failure, trajectory control failure, and operating force shortage. There is an effect of improving. In addition, since the generated potentials of positioning failure, trajectory control failure, and operating force shortage are output, it is possible to quantitatively know which operation has what kind of fault potential in the work to be evaluated. Also, at the design stage before the estimated production, it is possible to more accurately present points to be improved. In addition, it is possible to estimate a failure phenomenon by a combination of the magnitude of each generated potential and the type of component condition correction coefficient.

[0117]

According to the present invention, an estimated value of an assembly failure rate of an assembling operation of a product can be accurately estimated for each component assembling operation before the product is produced at a product designing stage, a manufacturing process planning stage, and the like. Therefore, parts assembling work having a high defect rate coefficient can be easily extracted, and by improving them, the defective assembly rate can be efficiently and effectively reduced. With the system of the present invention,
Reliable product design and manufacturing becomes possible.

[Brief description of the drawings]

FIG. 1 is a diagram showing a defect rate estimation system for estimating an assembly defect rate according to the present invention.

FIG. 2 is a functional block diagram of the present invention.

FIG. 3 is a diagram showing an example of a database according to the present invention.

FIG. 4 is a diagram showing an example of a database according to the present invention.

FIG. 5 is a diagram showing an example of a database according to the present invention.

FIG. 6 is a diagram showing an example of a database according to the present invention.

FIG. 7 is a diagram showing an example of a database according to the present invention.

FIG. 8 is a diagram showing an example of a database according to the present invention.

FIG. 9 is a flowchart for calculating an estimated value of an assembly defect rate according to the present invention;

FIG. 10 is a diagram showing an example of a correction coefficient pattern according to the present invention.

FIG. 11 is a diagram showing a calculation model of an estimated value of an assembly defect rate according to the present invention;

FIG. 12 is a diagram showing an example of an input screen according to the present invention.

FIG. 13 is a diagram showing an example of an input screen according to the present invention.

FIG. 14 is a diagram showing an example of an output screen according to the present invention.

FIG. 15 is a diagram showing an embodiment of the present invention.

FIG. 16 is a diagram showing a calculation model of an estimated value of an assembly defect rate according to the present invention;

FIG. 17 is a diagram showing a flow of an assembling operation.

FIG. 18 is a diagram showing a flow of an assembling operation.

FIG. 19 is a diagram showing a configuration example of an assembly operation process;

FIG. 20 is a diagram showing an example of an output screen according to the present invention.

FIG. 21 is a diagram showing an example of a database according to the present invention.

FIG. 22 is a diagram showing an example of a database according to the present invention.

FIG. 23 is a diagram showing an example of the processing of the present invention.

FIG. 24 is a diagram showing an example of the processing of the present invention.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Input means, 2 ... Output means, 3 ... Calculation means, 4 ... Storage means, 5 ... Steps for analyzing a part assembling work whose assembly defect rate is to be estimated, 6 ... Parts using standard assembling operation elements and part correction elements Step of expressing the assembling work, 7: Inputting the elements expressed in the defect rate estimation system, 8: Calculating the estimated value of the assembly defect rate by the program for calculating the defective rate of assembly of the defective rate estimation system of the present embodiment. Step 9: Outputting the calculation result of the estimated value of the assembly defect rate by the program for calculating the estimated value of the defective assembly rate of the defective rate estimation system. 10: System for estimating the defective rate, 11: Keyboard, 1
2 mouse, 13 pen input tablet, 20 design system, 21 display means, 22 printing means, 23 output means via network to other systems, 25 check factor correction coefficient database, 26 other Constant database, 27: input data / calculation result data storage unit, 30: calculation system, 31: ROM, 32: CP
U, program execution unit, 33 RAM, 34 input / output interface unit, 35 bus line, 36 information generation unit, 71 input information of assembly operation information for component assembly work, 72 assembly components and An input step of information on the properties of the parts to be assembled 73: an input step of information on the presence or absence of an assembling work completion confirmation step 74: an input step of correction information on assembly workplace conditions 211: a failure rate coefficient database by standard assembling operation
221, an operation order correction coefficient database; 231, an assembled part condition correction coefficient database; 232, an assembled part condition correction coefficient database; 241, a workplace constant database.

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Masatake Miyagawa 292 Yoshida-cho, Totsuka-ku, Yokohama-shi, Kanagawa Prefecture Inside the Manufacturing Research Laboratory, Hitachi, Ltd. (72) Masaaki Asano 292 Yoshida-cho, Totsuka-ku, Yokohama-shi, Kanagawa Address Co., Ltd. Hitachi, Ltd. Visual Information Media Division (72) Inventor Kubota Takashi 4-6 Kanda Surugadai, Chiyoda-ku, Tokyo Hitachi, Ltd. Home Appliances and Information Media Business Unit

Claims (25)

[Claims] 1. A product failure rate estimating method for estimating a product assembly failure rate, comprising: for each component constituting a product, property information of the assembled part;
A step of calculating and outputting an assembly failure rate for the entire product and for each part assembling operation based on the property information of the part to be assembled to which the part to be assembled and work content information for assembling the part to be assembled; A defect rate estimating method characterized by having: 2. The method according to claim 1, further comprising the step of displaying, in descending order of the defect rate, the defect rate for each operation content of the product, which is calculated and output, or for each assembled part. A defect rate estimating method characterized by having: 3. The defect rate estimating method according to claim 1, wherein at least one of the defect cause and the improvement proposal for each work content is displayed as a specific cause of the defect for each standard work content. A failure rate estimating method, comprising extracting information and improvement proposal information from a database stored in advance. 4. The method of estimating a product defect rate according to claim 1, wherein at least one of a defect cause and an improvement proposal for each of the assembled components is displayed. A defect rate estimating method characterized by including a step of extracting cause information and improvement proposal information from a database stored in advance and performing the extraction. 5. A method for estimating a defect rate of a product assembled from a plurality of parts, the assembly work information in an assembly process of the product, and a property of an assembly part assembled by the assembly work. Inputting the assembled part information and assembled part information representing the property of the assembled part with respect to the assembled part; and storing the defect rate coefficient for each standard assembly operation in advance by the storage device. Extracting a defect rate coefficient based on the additional work information; and a storage device storing a defect rate correction coefficient for each component in advance.
Extracting a first defect rate correction coefficient based on the assembled part information and a second defect rate correction coefficient based on the assembled part; and a defect rate coefficient for each of the extracted assembly operations. Is corrected based on the first and second defect rate correction coefficients,
A failure rate estimating method comprising calculating a failure rate for each assembly work or each assembly part relating to the work. 6. The method for estimating a defective rate of a product according to claim 5, wherein the calculated defective rate for each assembly work or each assembled part of the product is displayed in descending order of the defective rate. A defect rate estimating method comprising steps. 7. The method for estimating a defect rate of a product according to claim 5, wherein at least one of a defect cause and an improvement proposal for each of the assembling operations is displayed. A defect rate estimating method characterized by comprising a step of extracting specific cause information and improvement proposal information from a database stored in advance and performing the extraction. 8. The method for estimating a defect rate of a product according to claim 5, wherein at least one of a defect cause and an improvement proposal for each of the assembled parts is displayed. A failure rate estimating method, comprising extracting and performing basic cause information and improvement proposal information from a database stored in advance. 9. A method for estimating a defect rate of a product assembled from a plurality of parts, the assembly operation information in an assembly process of the product, and a property of an assembly part assembled by the assembly operation. A step of inputting assembled part information and assembled part information indicating properties of the assembled parts with respect to the assembled parts; and a storage device storing in advance a defect rate coefficient corresponding to the properties of each of the assembled parts. Extracting a defect rate coefficient based on the assembled part information; and a first defect rate correction based on the assembled operation information from a storage device in which a defect rate correction coefficient for each assembly operation is stored in advance. Extracting a coefficient and a second defect rate correction coefficient based on the part to be assembled, and converting the extracted defect rate coefficient for each of the assembled parts into the first and second defect rate correction coefficients. By performing a correction operation based on
Calculating a defect rate for each of the assembled parts. 10. The method for estimating a defect rate of a product according to claim 9, further comprising the step of displaying the calculated product in descending order of a defect rate for each assembled part. Rate estimation method. 11. The method for estimating a defect rate of a product according to claim 9, wherein at least one of a defect cause and an improvement proposal for each of the assembled parts is displayed. A failure rate estimating method, comprising extracting and performing basic cause information and improvement proposal information from a database stored in advance. 12. A method for estimating a defect rate of a product assembled from a plurality of parts, the assembly operation information in an assembly process of the product and a property of an assembly part assembled by the assembly operation. Inputting the assembled part information and the assembled part information indicating the properties of the assembled part with respect to the assembled part; and storing the defect rate coefficient for each standard assembly operation in advance by the storage device. Extracting a defect rate coefficient based on the attached operation information; and a storage device storing a defect rate correction coefficient for each component in advance.
Extracting a first defect rate correction coefficient based on the assembled part information and a second defect rate correction coefficient based on the assembled part; and a defect rate coefficient for each of the extracted assembly operations. Is corrected based on the first and second defect rate correction coefficients,
A failure rate estimating method comprising calculating a failure rate for each assembly operation or each assembly part related to the operation. 13. A method for estimating a defective rate of a product according to claim 12, wherein the calculated defective rate for each assembly operation or each assembled component is displayed in descending order of the defective rate. A defect rate estimating method comprising steps. 14. A method for estimating a defect rate of a product according to claim 12, wherein at least one of a defect cause and an improvement proposal for each of the assembling operations is displayed. A defect rate estimating method characterized by comprising a step of extracting specific cause information and improvement proposal information from a database stored in advance and performing the extraction. 15. The method for estimating a defect rate of a product according to claim 12, wherein at least one of the defect cause and the improvement proposal for each of the assembled parts is displayed. A failure rate estimating method, comprising extracting and performing basic cause information and improvement proposal information from a database stored in advance. 16. A product failure rate estimating method for estimating a product assembly failure rate, comprising: for each part constituting a product, property information of the assembled part;
Based on the property information of the part to be assembled to which the assembled part is to be assembled, the work content information for assembling the assembled part, and the condition information of the assembling workplace, assembling defects for the entire product and for each part assembling operation. A defect rate estimating method, comprising a step of calculating and outputting a rate. 17. A method of estimating a product defect rate according to claim 16, further comprising the step of displaying, in descending order of the defect rate, a defect rate for each operation content of the product calculated or output, or for each assembled part. A defect rate estimating method characterized by having: 18. The method for estimating a product defect rate according to claim 16, wherein at least one of the defect cause and the improvement proposal for each work content is displayed as a specific cause of the defect for each standard work content. A failure rate estimating method, comprising extracting information and improvement proposal information from a database stored in advance. 19. The method for estimating a product defect rate according to claim 16, wherein at least one of the defect cause and the improvement proposal for each of the assembled parts is displayed as a specific information of the defect for each of the assembled parts. A defect rate estimating method characterized by including a step of extracting cause information and improvement proposal information from a database stored in advance and performing the extraction. 20. The product defect rate estimation method according to claim 16, wherein at least one of a defect cause and an improvement proposal from the viewpoint of work conditions for each of the assembled parts is displayed. A method of estimating a product defect rate, comprising extracting specific cause information and improvement suggestion information of each defect from a database stored in advance. 21. A method for estimating a defect rate of a product assembled from a plurality of parts, comprising: assembling operation information in an assembling step of the product; and properties of an assembled part to be assembled by the assembling operation. Assembling part information, assembling part information representing the properties of the assembling part with respect to the assembling part, and inputting workplace information regarding workplace conditions for assembling the product; and a defect rate coefficient for each standard assembling operation in advance. Extracting a defect rate coefficient based on the assembling operation information from a storage device storing the component operation information; and a storage device storing a defect rate correction coefficient for each component in advance.
Extracting a first defect rate correction coefficient based on the assembled part information and a second defect rate correction coefficient based on the assembled part; and storing a defect rate correction coefficient corresponding to workplace conditions in advance. Extracting a third defect rate correction coefficient based on the workplace information from the stored storage device; and extracting the extracted defect rate coefficient for each assembly operation from the first,
Calculating a correction rate based on the second and third defect rate correction coefficients to calculate a defect rate for each assembling operation or each of the assembled components related to the operation, and also calculating a defect rate for the entire product;
A defect rate estimating method characterized by having: 22. The method of estimating a product defect rate according to claim 21, wherein the step of displaying the defective rate for each of the operation of assembling the product or for each of the parts to be assembled which is calculated and output is performed in descending order of the defective rate. A defect rate estimating method characterized by having: 23. The method of estimating a product defect rate according to claim 21, wherein at least one of a defect cause and an improvement proposal from the viewpoint of workplace conditions for each of the assembling operations is displayed by standard assembling. A defect rate estimating method comprising extracting specific cause information and improvement proposal information of a defect for each operation from a database stored in advance and performing the extraction. 24. The method according to claim 21, wherein at least one of a defect cause and an improvement proposal from the viewpoint of work conditions for each of the assembled parts is displayed. A defect rate estimating method, comprising extracting specific cause information and improvement proposal information of each defect from a database stored in advance and performing the extraction. 25. A recording medium storing a program having the steps of the failure rate estimation method according to claim 1. Description: