CN116114390A - Error cause estimation device and error cause estimation method - Google Patents

Abstract

The error cause estimation device is provided with a storage unit, a summation unit, and an extraction unit. The storage unit associates and stores in the storage device an evaluation object, which is at least one of a use device used in a substrate work of a substrate work machine that performs a predetermined substrate work on a substrate and use data used in the substrate work, with an error code indicating a work error of the substrate work for which the evaluation object is used. The totalizing unit totals the evaluation values of the error occurrence states of the plurality of evaluation targets stored in the storage device for each error code. The extraction unit extracts a specific object which is an evaluation object that is a cause of a work error, based on a difference in significance of evaluation values of error occurrence conditions between a plurality of kinds of evaluation objects that are aggregated for each error code.

Description

Error cause estimation device and error cause estimation method

Technical Field

The present specification discloses a technique related to an error cause estimation device and an error cause estimation method.

Background

The computing device described in patent document 1 includes a storage unit and a control unit. The storage unit stores device operation information and abnormality history information. The device operation information corresponds to each combination of the first element and the second element, and determines the number of operations of the first element and the second element used when the elements are assembled to the substrate. The abnormality history information determines the number of abnormality occurrences of abnormality in the first element and the second element when the element is assembled to the substrate, corresponding to each combination of the first element and the second element. The control unit compares the value of the dispersion of the first element having a high occurrence rate of the abnormality with the value of the dispersion of the second element having a high occurrence rate of the abnormality, and determines the type of the element having the smaller value as the cause of the abnormality.

Prior art literature

Patent literature

Patent document 1: japanese patent application laid-open No. 2010-238689

Disclosure of Invention

Problems to be solved by the invention

However, the abnormality history information described in patent document 1 is information indicating the number of abnormalities that occur for a combination of the first element and the second element. Thus, the history of abnormality generated by various causes is mixed with the abnormality history information. Therefore, the control unit may not be able to properly extract the element that is the cause of the abnormality.

In view of such a situation, the present specification discloses an error cause estimation device and an error cause estimation method that can extract a specific object that is a cause of a work error from among evaluation objects.

Means for solving the problems

Disclosed is an error cause estimation device provided with a storage unit, a summation unit, and an extraction unit. The storage unit associates and stores, in a storage device, an evaluation object that is at least one of a usage device used in a substrate alignment operation of a substrate alignment operation machine that performs a predetermined substrate alignment operation on a substrate and usage data used in the substrate alignment operation, and an error code that indicates an operation error of the substrate alignment operation in which the evaluation object is used. The totalizing unit totalizes, for each of the error codes, evaluation values concerning error occurrence statuses of the plurality of types of evaluation targets stored in the storage device. The extraction unit extracts a specific object, which is the evaluation object that is the cause of the work error, based on a significant difference in the evaluation value of the error occurrence status between the plurality of types of evaluation objects that are aggregated for each error code.

The present specification also discloses an error cause estimation method including a storage step, a summation step, and an extraction step. In the storing step, an evaluation object, which is at least one of a use device used in the substrate alignment operation of the substrate alignment machine that performs a predetermined substrate alignment operation on a substrate and use data used in the substrate alignment operation, is associated with an error code indicating an operation error of the substrate alignment operation using the evaluation object, and is stored in a storage device. In the aggregating step, the evaluation values of the error occurrence statuses of the plurality of types of evaluation targets stored in the storage device are aggregated for each error code. In the extracting step, a specific object, which is the evaluation object that causes the work error, is extracted based on a significant difference in the evaluation value of the error occurrence status between the plurality of types of evaluation objects that are aggregated for each error code.

Effects of the invention

According to the error cause estimating apparatus, the extracting unit is provided. The extraction unit extracts a specific object which is an evaluation object that is a cause of a work error, based on a difference in significance of evaluation values of error occurrence conditions between a plurality of kinds of evaluation objects that are aggregated for each error code. Therefore, the error cause estimation device can appropriately extract a specific object that is the cause of the operation error from among the evaluation objects, as compared with the case where the evaluation values are not summed up for each error code. The above-described content regarding the error cause estimation device is also the same as for the error cause estimation method.

Drawings

Fig. 1 is a block diagram showing an example of a structure of a substrate processing line.

Fig. 2 is a plan view showing a configuration example of the component mounter.

Fig. 3 is a schematic diagram showing an example of the usage device and usage data.

Fig. 4 is a block diagram showing an example of a control block of the error cause estimation device.

Fig. 5 is a flowchart showing an example of a control procedure by the error cause estimation device.

Fig. 6 is a schematic diagram showing an example of the state in which an error code, a usage device, and usage data are associated and stored in a storage device.

Fig. 7 is a schematic diagram showing an example of evaluation values regarding error occurrence conditions of the feeder as the first evaluation target and the holding member (nozzle) as the second evaluation target.

Fig. 8 is a schematic diagram showing an example of notification by the notification unit.

Detailed Description

1. Description of the embodiments

1-1. Structural example of substrate working line WL0

In the substrate alignment line WL0, a predetermined alignment operation is performed on the substrate 90. The type and number of the substrate working machines WM0 constituting the substrate working line WL0 are not limited. As shown in fig. 1, the substrate alignment machine WL0 of the present embodiment includes a plurality of (five) alignment machines WM0, i.e., a printer WM1, a printing inspection machine WM2, a component mounter WM3, a reflow oven WM4, and an appearance inspection machine WM5, and the substrates 90 are sequentially transported by a substrate transport device.

The printer WM1 prints solder at the mounting positions of the plurality of elements 91 of the substrate 90. The printing inspection machine WM2 inspects the printing state of the solder printed by the printer WM 1. As shown in fig. 2, the component mounter WM3 mounts a plurality of components 91 onto a substrate 90 on which solder is printed by the printer WM 1. The component mounter WM3 may be one or a plurality of. In the case where a plurality of component mounters WM3 are provided, the plurality of component mounters WM3 can share and mount the plurality of components 91.

The reflow furnace WM4 heats the substrate 90 on which the plurality of components 91 are mounted by the component mounter WM3, and melts the solder to perform soldering. The appearance inspection machine WM5 inspects the mounting state and the like of the plurality of components 91 mounted by the component mounting machine WM 3. In this way, the substrate work line WL0 can sequentially convey the substrates 90 to the substrate work machine WM0 using a plurality of (five) pairs, and the substrate products 900 can be produced by performing the production process including the inspection process. The substrate work line WL0 may also include, for example, a function inspection machine, a buffer device, a substrate supply device, a substrate inverting device, a shield mounting device, an adhesive applying device, an ultraviolet irradiation device, and the like as necessary for the substrate work machine WM0.

A plurality of (five) pairs of substrate working machines WM0 and a line management device LC0 constituting the pair of substrate working lines WL0 are communicably connected by a communication unit. The production line management device LC0 and the management device HC0 are connected to be communicable via a communication unit. The communication unit can connect them to be communicable by wire or wireless, and various methods can be adopted as the communication method.

In the present embodiment, the plurality of (five) pairs of substrate work machines WM0, the line management device LC0, and the management device HC0 form an internal information communication network (LAN: local Area Network). Thus, the plurality of (five) pairs of substrate work machines WM0 can communicate with each other via the communication unit. The plurality (five) of pairs of substrate work machines WM0 can communicate with the line management device LC0 via the communication unit. Further, the production line management device LC0 and the management device HC0 can communicate with each other via the communication unit.

The line management device LC0 controls a plurality of (five) substrate working machines WM0 constituting the substrate working line WL0, and monitors the operation state of the substrate working line WL 0. Various control data for controlling a plurality (five) of pairs of substrate work machines WM0 are stored in the line management device LC 0. The line management device LC0 transmits control data to each of the plurality of (five) pairs of substrate work machines WM 0. The plurality of (five) pairs of substrate work machines WM0 each transmit an operation status and a production status to the line management device LC 0.

The management device HC0 manages at least one line management device LC0. For example, the operation status and the production status of the substrate work machine WM0 acquired by the line management device LC0 are transmitted to the management device HC0 as needed. The management device HC0 is provided with a storage device DS0. The storage device DS0 can store various acquired data acquired by the substrate work machine WM 0. For example, various image data captured by the substrate working machine WM0 is included in the acquired data. The acquired data includes a record (log data) of the operation state acquired by the substrate working machine WM 0. In addition, the storage device DS0 can store various production information related to the production of the substrate product 900.

1-2 construction example of component Assembly machine WM3

The component mounter WM3 mounts a plurality of components 91 onto the substrate 90. As shown in fig. 2, the component mounter WM3 includes a substrate transfer device 11, a component supply device 12, a component transfer device 13, a component camera 14, a substrate camera 15, and a control device 16.

The substrate conveying device 11 is configured by, for example, a belt conveyor or the like, and conveys the substrate 90 in a conveying direction (X-axis direction). The substrate 90 is a circuit substrate, and an electronic circuit, an electric circuit, a magnetic circuit, and the like are formed. The substrate transfer device 11 transfers the substrate 90 into the device mounter WM3, and positions the substrate 90 at a predetermined position in the device mounter. After the completion of the mounting process of the plurality of components 91 by the component mounter WM3, the substrate transfer device 11 transfers the substrate 90 to the outside of the component mounter WM 3.

The component supply device 12 supplies a plurality of components 91 mounted on the substrate 90. The component supply device 12 includes a plurality of feeders 121 provided along the transport direction (X-axis direction) of the substrate 90. As shown in fig. 3, a plurality of feeders 121 are each provided with a reel RL0. The carrier tape CT0 accommodating the plurality of components 91 is wound around the reel RL0. The feeder 121 conveys the carrier tape CT0 at a pitch, and the component 91 is fed to be able to pick up at a feeding position PU0 located at the front end side of the feeder 121. The component supply device 12 may supply electronic components (for example, lead components) larger than chip components or the like in a state of being placed on a tray.

The component transfer device 13 includes a head drive device 131 and a moving stage 132. The head driving device 131 is configured to be capable of moving the moving stage 132 in the X-axis direction and the Y-axis direction by a linear motion mechanism. The mounting head 20 is detachably (replaceably) provided to the mobile station 132 via a clamping member. The mounting head 20 picks up and holds the component 91 supplied by the component supply device 12 using at least one holding member 30, and mounts the component 91 on the substrate 90 positioned by the substrate conveying device 11. For example, a suction nozzle, a gripper, or the like can be used as the holding member 30.

The element camera 14 and the substrate camera 15 can use known imaging devices. The component camera 14 is fixed to the base of the component mounter WM3 so that the optical axis is oriented upward in the vertical direction (Z-axis direction). The element camera 14 can capture the element 91 held by the holding member 30 from below. The substrate camera 15 is provided on the moving stage 132 of the component transfer device 13 so that the optical axis is directed downward in the vertical direction (Z-axis direction). The substrate camera 15 can photograph the substrate 90 from above. The element camera 14 and the substrate camera 15 perform imaging based on a control signal sent from the control device 16. Image data of the captured image captured by the element camera 14 and the substrate camera 15 is sent to the control device 16.

The control device 16 includes a well-known arithmetic device and a storage device, and constitutes a control circuit. Information, image data, and the like output from various sensors provided in the component mounter WM3 are input to the control device 16. The control device 16 transmits control signals to the respective devices based on a control program, preset predetermined mounting conditions, and the like.

For example, the control device 16 causes the substrate camera 15 to capture the substrate 90 positioned by the substrate conveying device 11. The control device 16 performs image processing on an image captured by the substrate camera 15, and recognizes the positioning state of the substrate 90. The control device 16 causes the holding member 30 to pick up and hold the component 91 supplied from the component supply device 12, and causes the component camera 14 to capture the component 91 held by the holding member 30. As shown in fig. 3, the control device 16 performs image processing on an image captured by the element camera 14, and recognizes the holding posture of the element 91.

The control device 16 moves the holding member 30 upward of the predetermined position for assembly, which is set in advance by a control program or the like. The control device 16 corrects the mounting scheduled position based on the positioning state of the substrate 90, the holding posture of the component 91, and the like, and sets the mounting position of the component 91 to be actually mounted. The fitting predetermined position and the fitting position include a rotation angle in addition to the positions (X-axis coordinates and Y-axis coordinates).

The control device 16 corrects the target position (X-axis coordinate and Y-axis coordinate) and the rotation angle of the holding member 30 according to the fitting position. The control device 16 lowers the holding member 30 at the corrected target position by the corrected rotation angle, and mounts the element 91 on the substrate 90. The control device 16 performs the mounting process of mounting the plurality of components 91 on the substrate 90 by repeating the above-described pick-and-place cycle.

1-3 structural examples of error cause estimating device 70

As shown in fig. 3, for example, various devices and data are used in the process of supplying the component 91 from the feeder 121 of the component supply device 12, causing the holding member 30 to pick up the component 91 supplied from the feeder 121, and mounting the component 91 on the substrate 90. When an error occurs in these jobs due to a failure of a specific device, it becomes more difficult to identify a device that is the cause of the job error as the number of participating devices increases. The same applies to data and other substrate operations.

For this reason, the error cause estimation device 70 is provided in the substrate processing line WL0 of the present embodiment. The error cause estimation device 70 extracts a specific object ST0 that is a cause of the operation error from among the evaluation objects ET 0. The error cause estimation device 70 can be provided in various arithmetic devices. For example, the error cause estimating device 70 may be provided in the analyzing device, the line management device LC0, the management device HC0, the control device 16 of the component mounter WM3, and the like. The error cause estimation device 70 may be formed on the cloud. As shown in fig. 4, the error cause estimation device 70 of the present embodiment is provided in the management device HC0.

The error cause estimation device 70, when understood as a control block, includes a storage unit 71, a summation unit 72, and an extraction unit 73. The error cause estimation device 70 may include a first determination unit 74 and a second determination unit 75. The error cause estimation device 70 may also include a notification unit 76. As shown in fig. 4, the error cause estimation device 70 of the present embodiment includes a storage unit 71, a summation unit 72, an extraction unit 73, a first determination unit 74, a second determination unit 75, and a notification unit 76.

The error cause estimation device 70 according to the present embodiment performs control according to the flowchart shown in fig. 5. The storage unit 71 performs the processing shown in step S11. The summation unit 72 performs the processing shown in step S12. The extraction unit 73, the first determination unit 74, and the second determination unit 75 perform the processing shown in step S13. The notification unit 76 performs the processing shown in step S14.

1-3-1. Storage portion 71

The storage unit 71 associates the evaluation target ET0 and the error code EC0 and stores the same in the storage device DS0 (step S11 shown in fig. 5). The evaluation target ET0 is at least one of the usage devices UM0 and the usage data UD 0. The usage equipment UM0 is equipment used for a substrate work performed on the substrate work machine WM 0. The use data UD0 is data used for a substrate work performed on the substrate work machine WM 0. The error code EC0 is a code indicating a work error of a work on the substrate using the evaluation target ET 0.

For example, the substrate work machine WM0 includes a component mounter WM3 that mounts components 91 onto a substrate 90. In this case, as described above, the work for the substrate includes at least one of the work for supplying the component 91 from the component supply device 12, the pick-up work for picking up the component 91 supplied from the component supply device 12, and the mounting work for mounting the component 91 on the substrate 90. As shown in fig. 3, for example, the usage equipment UM0 includes a reel RL0, a feeder 121, a mounting head 20, a holding member 30, a component camera 14, and the like. The reel RL0 and the feeder 121 participate in the feeding operation of the component 91. The mounting head 20, the holding member 30, and the component camera 14 participate in the pick-up operation and the mounting operation of the component 91.

The usage data UD0 includes element data including shape data, arrangement data, coordinate data, and the like. The element data defines the properties of the element 91 and the processing conditions. Specifically, the element data defines the packing method, storage conditions, and the like, in addition to the characteristics such as the electrical characteristic value, the error, and the use environment condition of the element 91. The component data defines the specifications of the reel RL0, the types of the feeder 121 and the holding member 30 used, the moving speed of the mounting head 20, the lifting speed of the holding member 30, and other processing conditions. Further, the element data includes shape data.

The shape data defines the shape of the element 91. Specifically, the shape data specifies, for example, the dimensions (longitudinal dimension, lateral dimension, and height dimension) of the element 91, allowable errors in the dimensions, the positions of the leads, the appearance color, and the like. In the shape data, imaging conditions, illumination conditions, and the like when the element camera 14 images the element 91 held by the holding member 30 may be specified. The component mounter WM3 performs image processing on the image data of the component 91 captured by the component camera 14, and compares the image data with the external shape defined by the shape data, thereby determining the presence or absence of the component 91 held by the holding member 30, the type of error, and the like. The component mounter WM3 similarly obtains a holding posture such as a position and a rotation angle of the component 91 with respect to the holding member 30.

The arrangement data defines the slot positions of the tray members for the arrangement of the plurality of feeders 121. The position of the substrate 90 on which the element 91 is mounted is specified in the coordinate data. These usage data UD0 are stored in the storage device DS0 shown in fig. 1 and 4. The control device 16 of the component mounter WM3 can acquire and use these data together with a control program, for example. The component data and the arrangement data participate in the supply job of the component 91. The component data and the coordinate data participate in the pick-up work and the assembly work of the component 91.

As described above, the job errors of the supply job and the pickup job of the component 91 are determined based on the image of the component 91 captured by the component camera 14. Similarly, an operation error in the mounting operation of the component 91 is determined based on the image of the substrate 90 captured by the substrate camera 15. In either case, the device mounter WM3 can determine whether or not the substrate is being worked based on whether or not the measured value of the object extracted from the image is included in the allowable range. The quality of the substrate work can be determined by the other substrate work machine WM 0. For example, the appearance inspection machine WM5 can determine whether or not the substrate work is performed by the component mounter WM 3.

The error code EC0 is assigned for each type of job error. The error code EC0 may be any code that can identify a work error in a substrate work, and may be used in various ways. As shown in fig. 6, the error code EC0 of the present embodiment is represented by a character string (alphanumeric), for example. The storage unit 71 associates the evaluation target ET0 with the error code EC0 and stores the same in the storage device DS0. Specifically, the storage unit 71 associates the error code EC0 with the identification code for identifying the evaluation target ET0, and stores the association in the storage device DS0.

When a job error occurs, the storage unit 71 sequentially stores the evaluation target ET0 and the error code EC0 in the storage device DS0. Further, when a predetermined number of job errors occur, the storage unit 71 may store the evaluation target ET0 and the error code EC0 corresponding to the predetermined number of times in the storage device DS0. When the substrate work machine WM0 is operated on the substrate but no work error occurs, the storage unit 71 stores only the evaluation target ET0 in the storage device DS0.

Fig. 6 shows an example of the state in which the error code EC0, the usage device UM0, and the usage data UD0 are associated and stored in the storage device DS0. For example, a job error for a substrate job using the use device UM1, the use device UM2, and the use data UD1 is represented by an error code EC 0001. The same can be said for error code EC0170, error code EC0174, and error code EC 0728.

1-3-2. Summing portion 72

The totalizing unit 72 totalizes the evaluation values EV0 concerning the error occurrence statuses of the plurality of evaluation targets ET0 stored in the storage device DS0 for each error code EC0 (step S12 shown in fig. 5). The evaluation value EV0 is not limited as long as the error occurrence condition can be evaluated.

For example, the evaluation value EV0 of the error occurrence state can be represented by a combination of the number of times the evaluation target ET0 is used in the work on the substrate and the number of times the work error occurs. For example, the totaling unit 72 totalizes the number of uses used in the work on the substrate and the number of occurrence of work errors for the use device UM1, the use device UM2, and the use data UD1, respectively, for the error code EC0001 shown in fig. 6. When the same error code EC0001 is stored in the storage device DS0, the totaling unit 72 similarly totalizes the evaluation value EV0.

Further, the greater the number of error codes EC0 stored in the storage device DS0, the greater the occurrence of the job error. Therefore, the totaling unit 72 can also generate the rank of the error codes EC0 stored in the storage device DS 0. Thereby, the extraction unit 73 can extract the specific object ST0 from the error code EC0 in the front order.

In addition, for example, the error code EC0170 shown in fig. 6 is different from the error code EC0174 in the number of bits of only the lowest bit. The error codes EC0 are often assigned to the associated job errors in order, and if similar error codes EC0 (for example, if only the lowest bit number is different) are grouped, the total of the evaluation values EV0 and the like becomes easy. For this reason, the aggregation unit 72 may group similar error codes EC0 to aggregate the evaluation values EV0 of the error occurrence situation.

For example, when the error codes EC0170 and EC0174 shown in fig. 6 are grouped, a new error code EC017X is given. The totalizing unit 72 combines the evaluation target ET0 associated with the error code EC0170 and the evaluation target ET0 associated with the error code EC0174 to total the evaluation value EV0 of the error occurrence state.

In addition, if the error codes EC0, which are the same or similar to the countermeasures for improving the job error, are grouped, the countermeasures can be easily implemented. For this reason, the aggregation unit 72 may aggregate the evaluation value EV0 of the error occurrence state by grouping the error codes EC0 having the same or similar countermeasures for improving the job error.

Further, among the associated job errors to which similar error codes EC0 are assigned, countermeasures for improving the job errors are the same or similar in many cases. For this reason, the aggregation unit 72 may aggregate the evaluation value EV0 of the error occurrence status by grouping the error codes EC0 similarly and the error codes EC0 having the same or similar countermeasures for improving the work error.

1-3-3. Extraction unit 73, first determination unit 74, and second determination unit 75

The extraction unit 73 extracts the specific object ST0, which is the evaluation object ET0 that is the cause of the operation error, based on the difference in the significance of the evaluation value EV0 corresponding to the error occurrence status among the plurality of evaluation objects ET0 that are summed up for each error code EC0 (step S13 shown in fig. 5).

Here, one evaluation target ET0 selected from a plurality of evaluation targets ET0 stored in association with one error code EC0 is referred to as a first evaluation target ET1, and one evaluation target ET0 different from the first evaluation target ET1 is referred to as a second evaluation target ET2. At this time, the first determination unit 74 determines whether or not there is a significant difference in the evaluation value EV0 concerning the error occurrence status of the plurality of evaluation objects ET0 included in the second type of evaluation object ET2 based on the one evaluation object ET0 included in the first type of evaluation object ET1, for each of the plurality of evaluation objects ET0 included in the first type of evaluation object ET 1.

The second determination unit 75 determines whether or not there is a significant difference in the evaluation value EV0 concerning the error occurrence situation of the plurality of evaluation objects ET0 included in the first evaluation object ET1 based on the one evaluation object ET0 included in the second evaluation object ET2 for each of the plurality of evaluation objects ET0 included in the second evaluation object ET2. In this embodiment, the extracting unit 73 can extract the specific object ST0 based on the first determination result, which is the determination result determined by the first determining unit 74, and the second determination result, which is the determination result determined by the second determining unit 75.

Fig. 7 shows an example of the evaluation value EV0 regarding the error occurrence state of the feeder 121 as the first evaluation target ET1 and the holding member 30 (suction nozzle) as the second evaluation target ET 2. The figure schematically shows an evaluation value EV0 concerning the error occurrence state of one error code EC0001, and the description of other types of error codes EC0 is omitted. For convenience of explanation, the feeder 121 is assumed to be three of the feeder FD1, the feeder FD2, and the feeder FD 3. Similarly, for convenience of explanation, the holding member 30 (suction nozzle) is assumed to be three of the suction nozzle NZ1, suction nozzle NZ2, and suction nozzle NZ 3.

Further, the score marks of the figure show an example of the evaluation value EV0 of the error occurrence situation. The denominator shows the number of uses used in a work (e.g., a pick-up work) on a substrate. The numerator shows the number of occurrences of a job error (e.g., a pick-up error). For example, the combination of the feeder FD1 and the suction nozzle NZ1 shows that the number of occurrence of the operation error among the 100 times of use is four times.

First, as one evaluation object ET0 included in the first evaluation object ET1, the first determination unit 74 is based on the feeder FD 1. The first determination unit 74 determines whether or not the evaluation values EV0 of the error occurrence situation differ significantly for three evaluation targets ET0, i.e., the suction nozzle NZ1, the suction nozzle NZ2, and the suction nozzle NZ3, included in the second evaluation target ET2, based on the feeder FD 1.

Further, the evaluation value EV0 regarding the occurrence of the error in the suction nozzle NZ1 with respect to the feeder FD1 is expressed as the occurrence of the operation error four times among the 100 times of use. The evaluation value EV0 regarding the occurrence of the error in the suction nozzle NZ2 with respect to the feeder FD1 is expressed as a condition in which the number of occurrence of the work error is one out of the 100 times of use. The evaluation value EV0 regarding the occurrence of the error in the suction nozzle NZ3 with respect to the feeder FD1 is expressed as the occurrence of the work error 0 times out of the 100 times of use.

For example, in the determination of whether or not there is a significant difference in the evaluation value EV0 of the error occurrence situation, the first determination unit 74 may use a statistical verification method, specifically, a method called "verification of difference between mother ratios". In this verification method, statistical processing is performed using the number of times of use and the number of times of occurrence of a work error used for working on a substrate, and it is verified whether or not there is a significant difference between a plurality of events (evaluation values EV0 of error occurrence conditions). As a criterion for the difference in significance, the occurrence probability of 5% is exemplified.

For example, assume that the number of times a "one dot" occurs by shaking two dice six times is two events in the first die and two in the second die. The occurrence of "one point" corresponds to the occurrence of a job error. Here, a hypothesis is established that two dice have the same performance with a probability of "one dot" of 1/6. In contrast, in an actual event, the number of times that a "dot" appears by shaking two dice six times is once and twice. The difference in the number of times of occurrence of one "dot" is a range in which occurrence of chance is possible, and the occurrence probability thereof is larger than 5% of the criterion. Thus, the hypothesis was not discarded and it was verified that there was no significant difference in the performance of the two dice.

In contrast, assume that two dice are rolled 60 times and a "one point" occurs for two events, 10 times for the first die and 20 times for the second die. In this event, the probability of a "one point" appearing is the same as if the dice were shaken six times. However, in the same hypothesis, the occurrence probability of an event of 20 occurrences of a "dot" in the second die is less than 5% of the decision criterion. Thus, the hypothesis was discarded and the performance of the two dice was characterized as significantly different (biased). That is, it is known that the probability of "one dot" appearing in the second die is greater than (1/6). For example, it is assumed that two faces among six faces of the second dice are "one point".

As in the above example, in the "verification of the difference between the mother ratios", the verification accuracy improves as the number of times of use increases. From this point of view, the first determination unit 74 may select, as the first evaluation target ET1, an evaluation target ET0 having a number of uses equal to or greater than a predetermined number of times used in the substrate work. Similarly, the second determination unit 75 may select, as the second evaluation target ET2, an evaluation target ET0 whose number of uses in the substrate work is equal to or greater than a predetermined number.

For example, the error occurrence rate is calculated by dividing the number of occurrence of the work error by the number of use of the evaluation target ET0 in the work on the substrate. When the error occurrence rate is used as an index for extracting the specific object ST0, the first determination unit 74 may set the minimum number of uses, and select the evaluation object ET0 having the minimum number of uses or more as the first evaluation object ET1. Similarly, in the case where the error occurrence rate is used as an index for extracting the specific object ST0, the second determination unit 75 may set the lowest number of uses, and select the evaluation object ET0 having the lowest number of uses or more as the second evaluation object ET2.

Here, it is assumed that a significant difference in the evaluation value EV0 of the error occurrence state is confirmed for a plurality of evaluation targets ET0 included in the second evaluation target ET2 based on one evaluation target ET0 included in the first evaluation target ET 1. At this time, the first determination unit 74 determines that there is a possibility that the evaluation target ET0 whose reference evaluation target ET0 is not the specific target ST0 and that the evaluation target ET0 whose error occurrence condition included in the second evaluation target ET2 is defective in the evaluation value EV0 is the specific target ST0. For convenience of explanation, this determination is referred to as determination a.

Further, it is assumed that the difference in the significance of the evaluation value EV0 of the error occurrence situation is not confirmed for the plurality of evaluation targets ET0 included in the second evaluation target ET2 based on the one evaluation target ET0 included in the first evaluation target ET1, and the evaluation value EV0 of the error occurrence situation is good. At this time, the first determination unit 74 determines that the reference evaluation target ET0 is not the specific target ST0, and that the specific target ST0 is not included in the second evaluation target ET 2. For convenience of explanation, this determination is referred to as determination B.

Further, it is assumed that the difference in the significance of the evaluation value EV0 of the error occurrence situation is not confirmed for the plurality of evaluation targets ET0 included in the second evaluation target ET2 based on the one evaluation target ET0 included in the first evaluation target ET1, and the evaluation value EV0 of the error occurrence situation is defective. At this time, the first determination unit 74 determines that the evaluation target ET0 serving as the reference may be the specific target ST0. For convenience of explanation, this determination is referred to as determination C.

The second determination unit 75 performs determination that the first evaluation object ET1 and the second evaluation object ET2 are changed as compared with the first determination unit 74. That is, it is assumed that a significant difference in the evaluation value EV0 of the error occurrence state is confirmed for a plurality of evaluation targets ET0 included in the first type of evaluation target ET1 with respect to one evaluation target ET0 included in the second type of evaluation target ET 2. At this time, the second determination unit 75 determines that the reference evaluation target ET0 is not the specific target ST0, and that the evaluation target ET0 whose evaluation value EV0 of the error occurrence status included in the first evaluation target ET1 is poor may be the specific target ST0. For convenience of explanation, this determination is referred to as determination D.

Further, it is assumed that the difference in the significance of the evaluation value EV0 of the error occurrence situation is not confirmed for the plurality of evaluation targets ET0 included in the first type of evaluation target ET1 based on the one evaluation target ET0 included in the second type of evaluation target ET2, and the evaluation value EV0 of the error occurrence situation is good. At this time, the second determination unit 75 determines that the reference evaluation target ET0 is not the specific target ST0, and that the specific target ST0 is not included in the first evaluation target ET 1. For convenience of explanation, this determination is referred to as determination E.

Further, it is assumed that the difference in the significance of the evaluation value EV0 of the error occurrence situation is not confirmed for the plurality of evaluation targets ET0 included in the first type of evaluation target ET1 based on the one evaluation target ET0 included in the second type of evaluation target ET2, and the evaluation value EV0 of the error occurrence situation is defective. At this time, the second determination unit 75 determines that the evaluation target ET0 serving as the reference may be the specific target ST0. For convenience of explanation, this determination is referred to as determination F.

As described above, when a significant difference in the evaluation value EV0 of the error occurrence condition is confirmed for the plurality of evaluation objects ET0 included in the second type of evaluation object ET2 based on the one evaluation object ET0 included in the first type of evaluation object ET1, and a significant difference in the evaluation value EV0 of the error occurrence condition is not confirmed for the plurality of evaluation objects ET0 included in the first type of evaluation object ET1 based on the one evaluation object ET0 included in the second type of evaluation object ET2, and the evaluation value EV0 of the error occurrence condition is defective, the extraction unit 73 may be able to extract the specific object ST0.

In addition, when a significant difference in the evaluation value EV0 of the error occurrence condition is confirmed for a plurality of evaluation objects ET0 included in the first type of evaluation object ET1 based on one evaluation object ET0 included in the second type of evaluation object ET2, and a significant difference in the evaluation value EV0 of the error occurrence condition is not confirmed for a plurality of evaluation objects ET0 included in the second type of evaluation object ET2 based on one evaluation object ET0 included in the first type of evaluation object ET1, and the evaluation value EV0 of the error occurrence condition is poor, the extraction unit 73 may be able to extract the specific object ST0.

In the example shown in fig. 7, no significant difference in the evaluation value EV0 of the error occurrence situation is confirmed for the suction nozzle NZ2 and suction nozzle NZ3 with respect to the feeder FD 1. However, the evaluation value EV0 of the error occurrence status of the nozzle NZ1 with respect to the feeder FD1 is inferior to the evaluation values EV 2 and NZ3, and a significant difference is confirmed in the evaluation value EV0 of the error occurrence status. Further, since the significant difference is confirmed in the evaluation value EV0 of the error occurrence situation with respect to the suction nozzles NZ1, NZ2, and NZ3 with respect to the feeder FD1, the first determination unit 74 determines that the feeder FD1 as a reference is not the specific object ST0 (determination a). The nozzle NZ1 having determined that the evaluation value EV0 of the error occurrence situation is poor may be the specific object ST0 (determination a) and may be the first determination result.

Similarly, since the significant difference is confirmed in the evaluation value EV0 of the error occurrence situation with respect to the suction nozzles NZ1, NZ2, and NZ3 with respect to the feeder FD2, the first determination unit 74 determines that the feeder FD2 as a reference is not the specific object ST0 (determination a). The nozzle NZ1 having determined that the evaluation value EV0 of the error occurrence situation is poor may be the specific object ST0 (determination a) by the first determination unit 74, and may be the second first determination result.

Further, since the significant difference is confirmed in the evaluation value EV0 of the error occurrence situation with respect to the suction nozzles NZ1, NZ2, and NZ3 with respect to the feeder FD3, the first determination unit 74 determines that the feeder FD3 as a reference is not the specific object ST0 (determination a). The nozzle NZ1 having determined that the evaluation value EV0 of the error occurrence situation is poor may be the specific object ST0 (determination a) and may be the third first determination result.

In contrast, no significant difference was confirmed in the evaluation value EV0 of the error occurrence state with respect to the feeders FD1, FD2, and FD3 based on the suction nozzle NZ 1. The evaluation values EV0 of the error occurrence states of the feeder FD1, the feeder FD2, and the feeder FD3 based on the suction nozzle NZ1 are inferior to those of the suction nozzles NZ2 and NZ 3. Thus, the second determination unit 75 determines that the reference nozzle NZ1 is likely to be the specific object ST0 (determination F), and makes the first and second determination results.

Similarly, no significant difference was confirmed in the evaluation value EV0 of the error occurrence state with respect to the feeders FD1, FD2, and FD3 based on the suction nozzle NZ 2. The evaluation value EV0 of the error occurrence status of the feeder FD1, the feeder FD2, and the feeder FD3 based on the suction nozzle NZ2 is better than the suction nozzle NZ 1. As a result, the second determination unit 75 determines that the reference nozzle NZ2 is not the specific object ST0, and the specific object ST0 is not included in the first evaluation objects ET1 (the feeders FD1, FD2, and FD 3) (determination E), and the second determination result is the second determination result.

In addition, no significant difference was confirmed in the evaluation value EV0 of the error occurrence state with respect to the feeders FD1, FD2, and FD3 with respect to the suction nozzle NZ 3. Further, the evaluation value EV0 of the error occurrence status of the feeder FD1, the feeder FD2, and the feeder FD3 based on the suction nozzle NZ3 is better than the suction nozzle NZ 1. As a result, the second determination unit 75 determines that the reference nozzle NZ3 is not the specific object ST0, and the specific object ST0 is not included in the first evaluation objects ET1 (the feeders FD1, FD2, and FD 3) (determination E), and the third second determination result is obtained.

The extracting unit 73 extracts the specific object ST0 based on the first determination result, which is the determination result determined by the first determining unit 74, and the second determination result, which is the determination result determined by the second determining unit 75. In the example shown in fig. 7, the extracting unit 73 extracts the specific object ST0 based on the first to third first determination results determined by the first determining unit 74 and the first to third second determination results determined by the second determining unit 75.

When the first determination result and the second determination result do not contradict each other, the extraction unit 73 extracts the evaluation target ET0 satisfying the first determination result and the second determination result as the specific target ST0. The extraction unit 73 can extract the evaluation target ET0 satisfying the first determination result and the second determination result as the specific target ST0 without contradiction between the above six determination results. Specifically, the extraction unit 73 extracts the suction nozzle NZ1 as the specific object ST0. The extracting unit 73 estimates that the feeder FD1, the feeder FD2, and the feeder FD3 are not specific objects ST0. Further, the extracting unit 73 estimates that the suction nozzles NZ2 and NZ3 are not specific objects ST0.

1-3-4 notification portion 76

The notification unit 76 notifies the specific object ST0 extracted by the extraction unit 73 (step S14 shown in fig. 5). For example, the notification unit 76 can display the specific object ST0 on the display device 80 to notify the specific object ST0. The display device 80 can be a known display device. The display device 80 can be provided in the analyzer, the management device HC0, the line management device LC0, the component mounter WM3, and the like. As shown in fig. 1 and 4, the display device 80 of the present embodiment is provided in the management device HC0.

Fig. 8 shows an example of notification by the notification unit 76. In the example shown in the figure, the notification unit 76 notifies that the specific object ST0 that is the cause of the work error is the suction nozzle NZ 1. Thus, the operator can know the specific object ST0. However, when notifying only the specific object ST0, the operator needs to confirm the work error additionally. For this purpose, the notification unit 76 may notify the error code EC0 associated with the specific object ST0 together with the specific object ST0.

In the example shown in the figure, the notification unit 76 notifies an error code EC0 (in this example, an error code EC 0001) associated with the suction nozzle NZ1 as the specific object ST0. The notification unit 76 may also notify that the error code EC0001 shows, for example, an abnormality in component elevation (an abnormal state in which the component 91 is raised due to the suction nozzle NZ1 sucking the corner of the component 91 or the like). Further, the notification unit 76 may notify the type of the substrate work as the pickup work.

By notifying the error code EC0 together with the specific object ST0 by the notification unit 76, the experienced operator can easily take measures for improving the work error of the substrate work using the specific object ST0 based on the accumulated knowledge. However, a less experienced operator may have difficulty in implementing countermeasures. For this reason, the notification unit 76 may notify the countermeasure information EI0 for improving the work error of the substrate work using the specific object ST0 together with the specific object ST 0. Thus, even a less experienced operator can take measures to improve the work error of the substrate work using the specific object ST 0.

In the example shown in the figure, the notification unit 76 notifies the skip of the suction nozzle NZ1, which is the specific object ST0, as countermeasure information EI0 for improving the work error. The skip of the suction nozzle NZ1 shows a case where the suction nozzle NZ1 is not used and another suction nozzle is used when the mounting head 20 is provided with a plurality of suction nozzles. Further, as countermeasure information EI0 for improving the work error, the notification unit 76 notifies the replacement of the suction nozzle NZ1 as the specific object ST 0.

In addition, a comparison table in which the preferable countermeasure candidates (countermeasure information EI 0) are described may be stored in the storage device DS0 for the combination of the error code EC0 and the evaluation target ET0 in advance. In this case, the notification unit 76 can acquire countermeasure candidates (countermeasure information EI 0) for the combination of the error code EC0 and the specific object ST0 by referring to the lookup table stored in the storage device DS0, and notify the countermeasure information EI0.

The notification unit 76 can notify various countermeasure information EI0 according to the type of the specific object ST0 and the error code EC 0. For example, when the specific object ST0 is the mounting head 20 and the error code EC0 indicates an abnormality related to the internal structure of the mounting head 20, the notification unit 76 can notify maintenance of the mounting head 20 as the countermeasure information EI 0. When the specific object ST0 is the holding member 30 (suction nozzle), and the error code EC0 is the normal/reverse determination abnormality, the mounting load abnormality, the suction load abnormality, or the like of the component 91, the notification unit 76 can notify the correction of the shape data or the like as the countermeasure information EI 0.

The work for the substrate is not limited to the supply work, the pickup work, and the mounting work of the component 91. For example, the substrate handling operation may be a conveying operation in which the substrate 90 is carried into the machine and positioned at a predetermined position, and the substrate 90 is carried out of the machine after the predetermined substrate handling operation. For example, it is assumed that the specific object ST0 is the substrate conveying device 11, and the error code EC0 indicates a reading error of the positioning reference portion provided on the substrate 90, a detection error of a plurality of positioning reference portions, or the like. At this time, the notification unit 76 may notify, as the countermeasure information EI0, correction of data related to the positioning reference unit defined in the production process, or the like.

Further, it is assumed that the specific object ST0 is the substrate transport device 11, and the error code EC0 indicates an error associated with the loading/unloading of the substrate 90 in the specific pair substrate work machine WM 0. At this time, the notification unit 76 can notify the cleaning, calibration, and the like of the substrate conveyance device 11 as the countermeasure information EI 0. Further, the substrate working machine WM0 is not limited to the component mounter WM3, and may be, for example, a printer WM1, a printing inspection machine WM2, an appearance inspection machine WM5, or the like.

2. Error cause estimation method

The same applies to the error cause estimation method as already described for the error cause estimation device 70. Specifically, the error cause estimation method includes a storage step, a summation step, and an extraction step. The storage step corresponds to control by the storage unit 71. The summation step corresponds to the control performed by the summation unit 72. The extraction process corresponds to control by the extraction unit 73. The error cause estimation method may further include a first determination step and a second determination step. The first determination step corresponds to control by the first determination unit 74. The second determination step corresponds to control by the second determination unit 75. The error cause estimation method may further include a notification step. The notification step corresponds to control by the notification unit 76.

3. One example of the effects of the embodiment

The error cause estimating device 70 includes an extracting unit 73. The extraction unit 73 extracts the specific object ST0, which is the evaluation object ET0 that is the cause of the operation error, based on the difference in the significance of the evaluation value EV0 corresponding to the error occurrence status between the plurality of evaluation objects ET0 that are summed up for each error code EC 0. Therefore, the error cause estimating device 70 can appropriately extract the specific object ST0 that is the cause of the operation error from the evaluation object ET0, as compared with the case where the evaluation value EV0 is not summed up for each error code EC 0. The above description of the error cause estimation device 70 is also the same as for the error cause estimation method.

Description of the reference numerals

12: component supply device 70: error cause estimation device 71: the storage unit 72: summation unit 73: extraction unit 74: the first determination unit 75: the second determination unit 76: the notification unit 90: the substrate 91: element DS0: storage UM0: using device UD0: using data ET0: evaluation object EC0: error code EV0: evaluation value ST0: specific object EI0: countermeasure information ET1: first evaluation object ET2: second evaluation object WM0: for the substrate working machine WM3: component assembling machine

Claims (10)

1. An error cause estimation device is provided with:

a storage unit that associates and stores, in a storage device, an evaluation object that is at least one of a usage device used in a substrate alignment operation of a substrate alignment operation machine that performs a predetermined substrate alignment operation on a substrate and usage data used in the substrate alignment operation, and an error code that indicates an operation error of the substrate alignment operation in which the evaluation object is used;

a totalizing unit that totalizes, for each of the error codes, evaluation values concerning error occurrence statuses of the plurality of types of evaluation targets stored in the storage device; and

an extraction unit that extracts a specific object that is the evaluation object that is the cause of the work error, based on a significant difference in the evaluation value of the error occurrence status between the plurality of types of evaluation objects that are summed up for each error code.

2. The error cause estimation apparatus according to claim 1, wherein,

the error cause estimation device includes a notification unit that notifies the specific object extracted by the extraction unit,

the notification unit notifies the specific object of the error code associated with the specific object.

3. The error cause estimation apparatus according to claim 1 or 2, wherein,

the error cause estimation device includes a notification unit that notifies the specific object extracted by the extraction unit,

the notifying unit notifies countermeasure information for improving the work error of the substrate work using the specific object, together with the specific object.

4. The error cause estimation apparatus according to any one of claims 1 to 3, wherein,

the aggregation unit groups the error codes that are similar to each other, and aggregates the evaluation values of the error occurrence status.

5. The error cause estimation apparatus according to any one of claims 1 to 4, wherein,

the aggregating unit groups the error codes having the same or similar countermeasures for improving the job error, and aggregates the evaluation values of the error occurrence status.

6. The error cause estimation apparatus according to any one of claims 1 to 5, wherein,

one evaluation object selected from a plurality of evaluation objects associated with and stored in association with one error code is set as a first evaluation object, one evaluation object different from the first evaluation object is set as a second evaluation object,

The error cause estimation device is provided with:

a first determination unit configured to determine, for each of a plurality of evaluation objects included in the first type of evaluation object, whether or not there is a significant difference in the evaluation values of the error occurrence statuses of a plurality of evaluation objects included in the second type of evaluation object based on one of the evaluation objects included in the first type of evaluation object; and

a second determination unit configured to determine, for each of a plurality of evaluation objects included in the second type of evaluation object, whether or not there is a significant difference in the evaluation values of the error occurrence statuses of the plurality of evaluation objects included in the first type of evaluation object based on one of the evaluation objects included in the second type of evaluation object,

the extraction unit extracts the specific object based on a first determination result, which is a determination result determined by the first determination unit, and a second determination result, which is a determination result determined by the second determination unit.

7. The error cause estimation apparatus according to claim 6, wherein,

the first determination unit is configured to determine, based on the first determination unit,

when a significant difference in the evaluation value of the error occurrence status is confirmed for a plurality of the evaluation objects included in the second type of evaluation object based on one of the first type of evaluation objects, it is determined that the evaluation object based on the first type of evaluation object is not the specific object and that the evaluation object of the error occurrence status included in the second type of evaluation object is likely to be the specific object,

When a significant difference in the evaluation value of the error occurrence state is not confirmed among a plurality of the evaluation objects included in the second type of evaluation object based on one of the first type of evaluation objects and the evaluation value of the error occurrence state is good, it is determined that the evaluation object serving as a reference is not the specific object and the specific object is not included in the second type of evaluation object,

when a significant difference in the evaluation value of the error occurrence state is not confirmed among a plurality of evaluation objects included in the second type of evaluation object based on one of the first type of evaluation objects, and the evaluation value of the error occurrence state is poor, it is determined that the evaluation object to be the reference is likely to be the specific object,

the second determination unit is configured to determine, based on the first determination unit,

when a significant difference in the evaluation value of the error occurrence status is confirmed for a plurality of the first type of evaluation objects included in the second type of evaluation objects based on one of the first type of evaluation objects, it is determined that the reference evaluation object is not the specific object and that the evaluation object of the error occurrence status included in the first type of evaluation object is likely to be the specific object,

When a significant difference in the evaluation value of the error occurrence state is not confirmed among a plurality of the first type of evaluation objects included in the first type of evaluation objects based on one of the second type of evaluation objects and the evaluation value of the error occurrence state is good, it is determined that the reference evaluation object is not the specific object and the specific object is not included in the first type of evaluation object,

when a significant difference in the evaluation value of the error occurrence state is not confirmed among a plurality of evaluation objects included in the first type of evaluation object based on one of the second type of evaluation objects, and the evaluation value of the error occurrence state is poor, the evaluation object to be the reference is determined to be the specific object.

8. The error cause estimation apparatus according to claim 6 or 7, wherein,

when the first determination result and the second determination result do not contradict each other, the extraction unit extracts the evaluation object satisfying the first determination result and the second determination result as the specific object.

9. The error cause estimation apparatus according to any one of claims 1 to 8, wherein,

the substrate alignment machine is a component mounting machine for mounting components on the substrate,

the work for the substrate is at least one of a work for supplying the component from a component supply device, a work for picking up the component supplied from the component supply device, and a work for assembling the component to the substrate.

10. An error cause estimation method is provided with:

a storage step of associating an evaluation object, which is at least one of a use device used in a substrate alignment operation of a substrate alignment operation machine that performs a predetermined substrate alignment operation on a substrate and use data used in the substrate alignment operation, with an error code indicating an operation error of the alignment operation using the evaluation object, with an error code and storing the evaluation object in a storage device;

an aggregation step of aggregating, for each of the error codes, evaluation values concerning error occurrence statuses of the plurality of types of evaluation targets stored in the storage device; and

and an extraction step of extracting a specific object, which is the evaluation object that is the cause of the work error, based on a significant difference in the evaluation value of the error occurrence status between the plurality of types of evaluation objects that are aggregated for each error code.

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