JP2006252342A - Quality analysis method, quality analysis device, computer program, and computer-readable storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately estimate a cause process through simple processing in occurrence of quality defect in a product produced through treatments in a plurality of processes. <P>SOLUTION: For the product having quality defect, data related to the quality of a plurality of products treated for each process before and after this product is arranged for a fixed products, according to the treatment order, and the similarity between a quality defect of each product to be analyzed and the quality detect of this product is evaluated and calculated. The process where products with high defect similarity are produced with the highest continuity is estimated as a cause process. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a quality analysis method, a quality analysis apparatus, a computer program, and a computer-readable storage medium in a manufacturing factory, and relates to a quality defect of a product produced through processing in a plurality of processes, particularly a thin plate that is a steel product. The present invention relates to a technique suitable for use in estimating a cause process when a surface defect occurs in a coil.

  For example, it is often very difficult to identify the causal process when a surface defect occurs in a steel product such as a thin coil, because the number of process steps that pass through the process is large. Processing can be performed by changing the manufacturing parameters of the suspicious process, and it can be judged from the presence or absence of improvement of the defect occurrence status as a result, but it is very laborious because there are many manufacturing parameters for each process. End up.

  On the other hand, Patent Document 1 collects manufacturing performance data and quality data of products with similar defect occurrence forms, and examines the processes through which these products have passed in common. A technique for presuming that is is disclosed.

  Patent Document 2 discloses a method of investigating actual manufacturing parameter values for each process and determining the presence or absence of abnormality by comparison with management reference data.

Japanese Patent Laid-Open No. 10-326816 Japanese Patent Laid-Open No. 9-50949

  However, in the method disclosed in Patent Document 1, when the total number of processing steps is large, there are often a plurality of steps that have passed in common, and it is difficult to estimate the cause step.

  Further, in the method disclosed in Patent Document 2, a defect may occur due to a synergistic action of a plurality of manufacturing parameters even if the actual values of the individual manufacturing parameters are not greatly deviated from the normal range. It was difficult to estimate the cause process of the occurrence.

  Therefore, an object of the present invention is to provide a technique for accurately estimating a cause process by a simple process when a defect in quality occurs in a product produced through a process in a plurality of processes.

The quality analysis method of the present invention is a quality analysis method for estimating a cause process for a quality defect of a product produced through processing in a plurality of processes at a manufacturing factory, and the product (standard) Data input step for inputting data on the quality of a plurality of products processed before and after the reference product for each process, and data storage for storing and storing the data on the quality input in the data input step A data sorting step for obtaining data to be analyzed by arranging data relating to the quality of the plurality of products processed before and / or after a reference product for each step by a predetermined number of products according to a processing order; and A defect similarity calculation step that evaluates and calculates the similarity between the quality defect of each product and the quality defect of the reference product for the analysis target data. A cause process estimation step for estimating that the product having the highest defect similarity is generated with the highest continuity as a cause process, and an output / display step for outputting and displaying the estimation result. It has the feature in having.
The quality analysis apparatus of the present invention is a quality analysis apparatus for estimating a cause process for a quality defect of a product produced through processing in a plurality of processes in a manufacturing factory, and a product (standard) in which a quality defect has occurred. A data input unit that inputs data related to the quality of a plurality of products processed before and after the reference product for each process, and a data storage unit that stores and stores the data related to the quality input to the data input unit And a data sorting unit that obtains data to be analyzed by arranging data relating to the quality of the plurality of products processed before and / or after the reference product for each process by a predetermined number of products according to the processing order, and the analysis A defect similarity calculation unit that evaluates and calculates the similarity between the defect in quality of each product and the defect in quality of the reference product with respect to the target data, and the product having the high defect similarity And cause process estimator that estimates to be responsible step highest step with a continuity has occurred, and outputs the estimation result has a feature in that an output-display unit for displaying.
The computer program of the present invention is a computer program for causing a computer to execute a quality analysis process for estimating a cause process for a quality defect of a product produced through a process in a plurality of processes in a manufacturing factory. Data storage process for storing and storing data related to the quality of multiple products processed before and after the reference product for each process for the product (reference product) in which the occurrence occurred, and before and / or before the reference product for each process A data sorting process for obtaining data to be analyzed by arranging data relating to the quality of the plurality of products processed later by a predetermined number of products according to a processing order; and for the analysis target data, quality defects and standards of each product Defect similarity calculation processing for evaluating and calculating the similarity to defects in product quality,
The cause process estimation process that estimates that the process with the highest continuity of the product with the highest degree of defect similarity is the cause process, and the output / display process that outputs and displays the estimation result are executed on a computer. It is characterized in that
The computer-readable storage medium of the present invention is characterized in that the computer program of the present invention is stored.

  ADVANTAGE OF THE INVENTION According to this invention, when a quality defect generate | occur | produces in the product produced through the process in a several process, a cause process can be estimated with a simple process with sufficient precision.

Preferred embodiments of the present invention will be described below with reference to the accompanying drawings.
(First embodiment)
FIG. 1 is a diagram showing a schematic configuration of a quality analysis apparatus according to the first embodiment of the present invention. FIG. 2 is a flowchart showing an example of a quality analysis method executed using the quality analysis apparatus of FIG. Hereinafter, a cause process estimation that causes surface defects as the quality of a thin coil (hereinafter referred to as “coil”) as a product in a steel product manufacturing factory will be described as an example with reference to FIGS. 1 and 2.

  As shown in FIG. 1, a quality data storage server is installed outside the quality analysis apparatus of the present embodiment. In the quality data storage server, data related to surface defects measured by a defect inspection device or the like is stored for a long period (for example, in the order of coil numbers (numbers uniquely assigned to the coils), for each process and each processing day) Half a year) Accumulated and stored. When a surface flaw is generated in a coil that has been manufactured in a final process after a plurality of processes, a reference coil is generated for each process in which the coil (hereinafter referred to as “reference coil”) is processed. The processing date in the relevant process is retrieved from the coil number and data on the surface defects of all the coils processed on the same day are input to the data input unit (101) to be analyzed (data in FIG. 2). Corresponding to the input step 201). In the following data sorting step, when more coils are targeted, data on the surface defects of the coil processed for a plurality of days before and after the reference coil processing date is input.

  Next, the input data is stored and stored in the data storage unit (102) for subsequent processing (corresponding to the data storage step 202 in FIG. 2).

  Next, in the data sorting unit (103), the data on the surface defects of the plurality of coils processed before and after the reference coil for each process are arranged by a series of a predetermined number of products according to the processing order (data in FIG. 2). Corresponding to sort step 203). This is analysis target data used for the subsequent analysis. A simple example shown in FIG. 3 will be described. As for the surface defects, the surface defect types (5 types of A, B, C, D, and E), the surface defect grades (three grades 1, 2, and 3), the process from step 1 It is an example of the analysis object data which made the 3 process of process 3 and selected and sorted the coil processed before and after the reference coil by 5 coils before and after each in the processing order.

  As a sorting method, in addition to selecting a certain number of continuous coils before and after the reference coil in accordance with the processing order, it is possible to select only before or after the reference coil. It goes without saying that it is possible to select by thinning out every other line.

  When multiple surface defects occur in one coil, for example, the number of defects is tabulated for each type and grade, and the type and grade of the surface defect with the largest number of occurrences are sorted as the representative surface defects of the reference coil. It ’s fine. However, it goes without saying that the method for selecting representative surface defects from a plurality of surface defects present in one coil is not limited to this method.

  Based on the analysis target data, the defect similarity calculation unit (104) calculates the defect similarity between each coil and the reference coil (corresponding to the defect similarity calculation step 204 in FIG. 2). For example, it can be calculated as 2 points if both the species and grade match, 1 point if either one matches, and 0 point if neither match. However, it goes without saying that the method of calculating the defect similarity is not limited to this method. The calculation results are shown in the row of “Defect similarity” in FIG.

  The cause process estimation unit (105) first evaluates the continuity of the defect similarity from the series data of the defect similarity of each coil for each process calculated by the above method (cause process estimation step of FIG. 2). 205). Specifically, the coil having the maximum defect similarity of 2 is assumed to be a coil having a high defect similarity, and the coil having a high defect similarity with respect to 11 analysis target coils including the reference coil is selected. The number is used as an index of continuity of defect similarity.

This value is as follows.
Step 1: 2
Process 2: 5
Process 3: 4
In this case, the continuity of the defect similarity in the process 2 is the highest, and it is estimated that this is the causal process of the surface defect (species A) of the reference coil.

  Finally, the output / display unit (106) outputs the estimation result that the process 2 is the causal process to the outside and displays it on the screen (corresponding to the output / display step 206 in FIG. 2).

(Second Embodiment)
Further, as a method for evaluating the continuity of defect similarity in the causal process estimation unit (105) of FIG. 1, the defect calculated by the defect similarity calculation unit (104) of FIG. A total value of 11 similarities of the analysis target coils may be obtained, and the value may be used as an index of continuity of the defect similarity.

The values calculated in this way are as follows.
Step 1: 6
Process 2:12
Process 3:10
From this result, it is estimated that the process 2 is a causal process.

(Third embodiment)
Further, as a method for evaluating the continuity of the defect similarity in the causal process estimation unit (105) in FIG. 1, the defect similarity calculated in the defect similarity calculation unit (104) in FIG. Any two of the coils are selected, and proportional to the product of the defect similarity of both coils, the processing interval of both coils (for example, 1 when one is processed continuously, one separate coil between them) A value that is inversely proportional to (if defined as 2) is calculated, and is calculated for all two coils to obtain a total value, which may be used as an index of continuity of the defect similarity. The calculation formula is shown in Formula (1) and Formula (2).

The values calculated in this way are as follows.
Step 1: 9.2
Step 2: 62.1
Step 3: 34.6
From this result, it is estimated that the process 2 is a causal process.

  Note that the above calculation is a value calculated for the coils of all defect similarity values larger than 0 in the equations (1) and (2), but in order to simplify the calculation, The continuity index may be calculated only for the coil having the maximum similarity (2 in the example shown in FIG. 3).

  FIG. 4 is a block diagram illustrating an example of a computer system that can configure the above-described quality analysis apparatus. In FIG. 4, reference numeral 400 denotes a computer PC. The PC 400 includes a CPU 401, executes device control software stored in the ROM 402 or the hard disk (HD) 411, or supplied from the flexible disk drive (FD) 412, and collectively controls each device connected to the system bus 404. To control. Each function unit of the present embodiment is configured by a program stored in the CPU 401, the ROM 402, or the hard disk (HD) 411 of the PC 400.

  Reference numeral 403 denotes a RAM which functions as a main memory, work area, and the like for the CPU 401. Reference numeral 405 denotes a keyboard controller (KBC) which controls to input a signal input from the keyboard (KB) 409 into the system main body. A display controller (CRTC) 406 performs display control on the display device (CRT) 410. A disk controller (DKC) 407 is a hard disk (boot program (startup program: a program that starts execution (operation) of personal computer hardware and software)), a plurality of applications, editing files, user files, a network management program, and the like. HD) 411 and flexible disk (FD) 412 are controlled.

  Reference numeral 408 denotes a network interface card (NIC) that exchanges data bidirectionally with a network printer, another network device, or another PC via the LAN 413.

(Example)
The cause process estimation of the surface flaw generated in the manufacturing process of the thin coil was performed. The surface wrinkle data of the 43 coils processed before and the 49 coils processed after that in the three steps from Step 1 to Step 3 are input to the coil in which the surface wrinkles occurred, and the data is sorted. FIG. 5 shows the result of the defect similarity calculation. Here, as the data on the surface wrinkles, in addition to the wrinkle type and wrinkle grade, 4 points of the longitudinal position and the width direction position of the wrinkles are input, and whether or not each matches the surface wrinkles of the reference coil, from 0 point A defect similarity of 4 points was calculated. In addition, about the longitudinal direction position and the width direction position of the ridge, it was determined that the lengths and the width direction of the coil were equally divided when they were equally divided into 10 corresponding to the same section. As the continuity index, the method described in the third embodiment described above was adopted.

The evaluation results are as follows.
Step 1: 1,763
Process 2: 1,903
Process 3: 1,341
From the above results, it was estimated that step 2 was the causal step. In addition, as a result of detailed investigation after this analysis, it was found that surface flaws occurred due to the equipment failure in step 2.

  The present invention may be applied to a system composed of a plurality of devices or an apparatus composed of a single device.

  Another object of the present invention is to supply a storage medium storing software program codes for realizing the functions of the above-described embodiments to a system or apparatus, and store the computer (CPU or MPU) of the system or apparatus in the storage medium. Needless to say, this can also be achieved by reading and executing the programmed program code.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present invention. As a storage medium for supplying the program code, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) or the like running on the computer based on the instruction of the program code. It goes without saying that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion is performed based on the instruction of the program code. It goes without saying that the CPU or the like provided in the board or function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

It is a figure which shows schematic structure of the quality analysis apparatus of 1st Embodiment. It is a flowchart of the quality analysis method of 1st Embodiment. It is a figure for demonstrating the method of data sorting. It is a block diagram which shows an example of the computer system which can comprise a quality analysis apparatus. It is a figure which shows the result of having performed the data sort and defect similarity calculation in embodiment of this invention.

Explanation of symbols

101: Data input unit 102: Data storage unit 103: Data sorting unit 104: Defect similarity calculation unit 105: Cause process estimation unit 106: Output / display unit

Claims (10)

A quality analysis method for estimating a cause process for a defect in quality of a product produced through processing in a plurality of processes in a manufacturing factory,
A data input step for inputting data relating to the quality of a plurality of products processed before and after the reference product for each process for the product (reference product) in which quality defects have occurred,
A data accumulation step for accumulating and storing the data relating to the quality input in the data input step;
A data sorting step for obtaining data to be analyzed by arranging data relating to the quality of the plurality of products processed before and / or after a reference product for each process by a predetermined number of products according to a processing order;
A defect similarity calculation step for evaluating and calculating the similarity between the quality defect of each product and the quality defect of the reference product for the analysis target data;
A causal process estimation step for estimating that the process in which the product having a high degree of defect similarity is generated with the highest continuity is a causal process;
A quality analysis method comprising: an output / display step for outputting and displaying the estimation result.   The quality analysis method according to claim 1, wherein the product is a steel product.   The quality analysis method according to claim 2, wherein the defect is a surface defect.   The causal process estimation step estimates the causal process using the number of products having high defect similarity in the analysis target data for each process as an index of defect similarity continuity of the process. 4. The quality analysis method according to any one of 3 above.   The causal process estimation step estimates a causal process using the sum or partial sum of defect similarities in the analysis target data for each process as an index of defect similarity continuity of the process. 4. The quality analysis method according to any one of 3 above.   The cause process estimation step has an index indicating a higher value as the number of products having a high defect similarity in the analysis target data for each process is larger and a processing interval between the products having a higher defect similarity is narrower. The quality analysis method according to claim 1, wherein the quality analysis method is used as an index of defect similarity continuity in the process.   The causal process estimation step has an index indicating a higher value as the total value of defect similarities of products existing in the analysis target data for each process is larger and as the processing interval between the products is narrower. The quality analysis method according to claim 1, wherein the quality analysis method is an index of continuity. A quality analysis device that estimates a causal process for a defect in quality of a product produced through processing in a plurality of processes in a manufacturing factory,
A data input unit that inputs data on the quality of multiple products processed before and after the reference product for each process for the product in which a defect in quality occurs (reference product),
A data storage unit for storing and storing data relating to the quality input to the data input unit;
A data sorting unit that obtains data to be analyzed by arranging data related to the quality of the plurality of products processed before and / or after a reference product for each process by a predetermined number of products according to a processing order;
For the analysis target data, a defect similarity calculation unit that evaluates and calculates the similarity between the defect in quality of each product and the defect in quality of the reference product,
A cause process estimation unit that estimates that a process in which the product having a high degree of defect similarity is generated with the highest continuity is a cause process;
A quality analysis apparatus comprising: an output / display unit that outputs and displays the estimation result. A computer program for causing a computer to execute a quality analysis process for estimating a cause process for a defect in quality of a product produced through processing in a plurality of processes in a manufacturing factory,
Data accumulation processing for accumulating and storing data related to the quality of multiple products processed before and after the standard product for each product (standard product) with defective quality,
A data sorting process for obtaining data to be analyzed by arranging data related to the quality of the plurality of products processed before and / or after a reference product for each process by a predetermined number of products according to a processing order;
For the analysis target data, a defect similarity calculation process for evaluating and calculating the similarity between the defect in quality of each product and the defect in quality of the reference product;
Cause process estimation process for estimating that the product having a high degree of defect similarity has the highest continuity and is a cause process;
A computer program for causing a computer to execute output / display processing for outputting and displaying the estimation result. A computer-readable storage medium storing the computer program according to claim 9.

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