Method for graphically displaying process data, electronic device and storage medium

Abstract

A method for graphically displaying process data, an electronic device and a storage medium are applied to the electronic device, and the method comprises the following steps: collecting a plurality of test sample data by factory equipment; related parameters of the production process capability are analyzed and calculated; integrating a plurality of calculation formulas according to the calculation results of the related parameters and the quantity of the plurality of test sample data to draw a histogram distribution diagram so as to display the distribution state of the plurality of test sample data; and viewing the test sample data through Excel in the form of data and graphic display.

Description

Technical Field

[0001] The present invention relates to a graphical display method, and in particular to a method, an electronic device and a storage medium for graphically displaying process data. Background Art

[0002] With the rapid development of industry, the production scale of factories is expanding, and the production process is becoming more complex and refined. How to monitor the production process, discover production problems in a timely manner, improve the production process, and improve production efficiency, product quality and corporate competitiveness is one of the core needs of every enterprise.

[0003] Calculating production process capability is one of the methods to improve production processes and increase production efficiency. There are three methods for calculating production process capability. (1) Manual calculation based on the production process capability calculation formula. The disadvantages are as follows: the calculation formula is complicated, the calculation time is huge, and manual calculation is prone to errors. In addition, the calculation results are only numerical values, and there is no graphical display of the production process status, which cannot meet the current factory's hundreds of test items and thousands of test data calculation and analysis needs in a timely manner. (2) Applying the production process capability calculation formula and designing an Excel formula template for use. The disadvantages are as follows: Batch copying each test item data to the Excel formula template may cause errors. Excel's graphic display function is limited and cannot meet the detailed and complete display requirements. It is difficult to achieve convenient unified display and viewing of hundreds of test item data. (3) Using professional quality control calculation software (for example, Minitab). The disadvantages are as follows: the software fee is high, the software is complex to learn and use, and batch data import and batch display are not convenient for factory-side summary and unified viewing. Summary of the Invention

[0004] In view of the above, it is necessary to provide a method, electronic device and storage medium for graphically displaying process data. Test sample data is collected by factory equipment, and a Python program analyzes and calculates the production process capability. Different calculation formulas are integrated according to the number of test samples to draw a histogram to show the distribution status of the data, and then Excel is used to view the data and graphical display.

[0005] An embodiment of the present invention provides a method for graphically displaying process data, which is applied to an electronic device, comprising: collecting a plurality of test sample data from factory equipment; analyzing and calculating relevant parameters of the production process capability; integrating a plurality of calculation formulas based on the calculation results of the relevant parameters and the quantity of the plurality of test sample data to draw a histogram to display the distribution status of the plurality of test sample data; and viewing the test sample data in data and graphical display through Excel.

[0006] An embodiment of the present invention also provides an electronic device, comprising a memory, a processor, and a program for graphically displaying process data stored in the memory and runnable on the processor. The electronic device also comprises a data collection module, a data analysis module, a graphics drawing module, and an Excel management module. When the program for graphically displaying process data is executed by the processor, the following steps are implemented: collecting multiple test sample data from factory equipment; analyzing and calculating relevant parameters of production process capabilities; integrating multiple calculation formulas based on the calculation results of the relevant parameters and the number of the multiple test sample data to draw a histogram to display the distribution status of the multiple test sample data; and viewing the test sample data through Excel in the form of data and graphics.

[0007] An embodiment of the present invention further provides a storage medium having a computer program stored thereon. When the computer program is executed, the steps of the method for graphically displaying process data as described above are implemented.

[0008] The method, electronic device, and storage medium for graphically displaying process data in the embodiments of the present invention intuitively, systematically, conveniently, and accurately display the factory's production process capabilities, which is conducive to timely discovering production problems, improving production processes, and enhancing production efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a flowchart of the steps of a method for graphically displaying process data according to an embodiment of the present invention.

[0010] Figure 2 It is a histogram of a preferred process capability index (CPK) of the production process capability of an embodiment of the present invention.

[0011] Figure 3 FIG. 4 is a histogram of poor CPK of the production process capability of an embodiment of the present invention.

[0012] Figure 4 This is a histogram of test sample data calculated using a formula according to the first embodiment of the present invention.

[0013] Figure 5 This is a histogram of test sample data calculated using a formula according to the second embodiment of the present invention.

[0014] Figure 6 This is a histogram of test sample data calculated using a formula according to the third embodiment of the present invention.

[0015] Figure 7 FIG. 4 is a schematic diagram of the hardware architecture of an electronic device according to an embodiment of the present invention.

[0016] Figure 8is a functional block diagram of an electronic device according to an embodiment of the present invention.

[0017] Description of main component symbols

[0018] electronic devices 200 processor 210 Memory 220 System for graphically displaying process data 230 Data collection module 310 Data analysis module 320 Graphics drawing module 330 Excel Management Module 340 step S1~S4

[0019] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0020] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present application and the features therein may be combined with each other.

[0021] The following description sets forth numerous specific details to facilitate a thorough understanding of the present invention. The embodiments described are merely some, not all, of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are intended to fall within the scope of protection of the present invention.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0023] It should be noted that the descriptions of "first", "second", etc. in the present invention are for descriptive purposes only and should not be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the said features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0024] Figure 1 This is a flowchart of a method for graphically displaying process data according to an embodiment of the present invention, which is applied to an electronic device, such as a production process equipment. The order of the steps in the flowchart may be changed, and some steps may be omitted, depending on different requirements.

[0025] In step S1, a plurality of test sample data are collected by factory equipment.

[0026] In step S2, the Python program analyzes and calculates the production process capability, and calculates relevant parameters of the production process capability, including the process capability index (CPK), variance, mean, extreme value, etc.

[0027] In step S3 , different calculation formulas are integrated according to the calculation results of the relevant parameters of the production process capability and the number of test sample data to draw a histogram to show the distribution status of the test sample data.

[0028] The histogram distribution curve and the normal distribution curve of each test item are drawn on the same chart. Different calculation formulas are integrated according to different test sample data to draw the histogram distribution curve.

[0029] Figure 2 This is a histogram of the preferred process capability index (CPK) of the production process capability of an embodiment of the present invention, which displays the distribution status of the test sample data through the histogram and the within group (Within) and overall (Overall) normal distribution curves, wherein the x-axis is the numerical range of the test sample data and the y-axis is the frequency range of the histogram.

[0030] Figure 3 This is a histogram of the poor CPK of the production process capability of the embodiment of the present invention. The relevant parameters include CPK, CPM, variance, mean, extreme value, etc. The factory can compare Figure 2 and Figure 3 The histogram distribution status of the test project can be used to grasp the production process status of the test project.

[0031] There are three common histogram grouping calculation formulas based on the number of test samples: Rice Rule, Square-root Rule, and Sturges' Rule. The histogram grouping method of the present invention does not use a single calculation formula, but adopts different calculation formulas based on the number of different test samples, as shown in Table 1:

[0032] Table 1

[0033]

[0034] Figure 4 The first embodiment of the present invention is to calculate the histogram of the test sample data by formula. The calculation formula for calculating the histogram grouping is used with the number of test samples as the x-axis and the number of histogram groups as the y-axis, and the curve is drawn as follows: Figure 4As shown in the figure, the Rice Rule is the blue line, the Square-root Rule is the red line, and the Sturges' Rule is the green line. When the number of test samples is less than 64, to avoid having too few histogram groups and failing to highlight the data distribution, the Rice Rule with the largest number of groups (the first line from the top) is selected for grouping.

[0035] Figure 5 The second embodiment of the present invention is to calculate the histogram of the test sample data by formula. The calculation formula for calculating the histogram grouping is used with the number of test samples as the x-axis and the number of histogram groups as the y-axis, and the curve is drawn as follows: Figure 5 As shown in the figure, the Rice Rule is the blue line, the Square-root Rule is the red line, and the Sturges' Rule is the green line. When the number of test samples is greater than 64 and less than 900, to avoid too few histogram groups and the inability to present the data distribution, the Rice Rule with the largest number of groups (the first line from the top) is selected for grouping.

[0036] Figure 6 The third embodiment of the present invention is to calculate the histogram of the test sample data by formula. The calculation formula for calculating the histogram grouping is used with the number of test samples as the x-axis and the number of histogram groups as the y-axis, and the curve is drawn as follows: Figure 6 As shown in the figure, the Rice Rule is the blue line, the Square-root Rule is the red line, and the Sturges' Rule is the green line. When the number of test samples is greater than 900, if the Square-root Rule (the first line from the top) histogram distribution is used, the number of groups will exceed 30, and too many groups will not highlight the concentration of the data. To prevent the number of groups from exceeding 30 using the Rice Rule (the second line from the top), the Sturges' Rule (the third line from the top) is selected, as it has the slowest growth in the number of groups.

[0037] Step S4, viewing the test sample data in data and graphic display through Excel, so that the factory can evaluate the production process in an intuitive, organized, convenient and accurate manner and optimize the production process.

[0038] Figure 7 Schematic diagram of the hardware architecture of an electronic device according to an embodiment of the present invention. The electronic device 200, for example, but not limited to, a production process server, can be interconnected via a system bus to communicate with a processor 210, a memory 220, and a system 230 for graphically displaying process data. Figure 7 The electronic device 200 is shown only with components 210 - 230 , but it is understood that implementing all of the illustrated components is not a requirement, and greater or fewer components may alternatively be implemented.

[0039] The memory 220 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 220 can be an internal storage unit of the electronic device 200, such as a hard disk or memory of the electronic device 200. In other embodiments, the memory can also be an external storage device of the electronic device 200, such as a plug-in hard disk equipped on the electronic device 200, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 220 can also include both the internal storage unit of the electronic device 200 and its external storage device. In this embodiment, the memory 220 is generally used to store the operating system and various application software installed in the electronic device 200, such as the program code of the system 230 for graphically displaying process data. In addition, the memory 220 can also be used to temporarily store various data that has been output or is about to be output.

[0040] In some embodiments, the processor 210 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 210 is generally used to control the overall operation of the electronic device 200. In this embodiment, the processor 210 is used to execute program code stored in the memory 220 or process data, for example, to execute the system 230 for graphically displaying process data.

[0041] It should be noted that Figure 7 The electronic device 200 is merely illustrated as an example. In other embodiments, the electronic device 200 may include more or fewer components, or have a different component configuration.

[0042] If the modules / units integrated in the electronic device 200 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal, and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media does not include electric carrier signals and telecommunication signals.

[0043] Figure 8 2 is a functional block diagram of an electronic device according to an embodiment of the present invention, which is configured to execute a method for graphically displaying process data. The method for graphically displaying process data according to the embodiment of the present invention can be implemented by a computer program stored in a storage medium, such as memory 220 in electronic device 200. When the computer program implementing the method according to the present invention is loaded into memory 220 by processor 210, processor 210 of electronic device 200 is driven to execute the method for graphically displaying process data according to the embodiment of the present invention.

[0044] The electronic device 200 according to the embodiment of the present invention, for example, a production process server, includes a data collection module 310 , a data analysis module 320 , a graphic drawing module 330 and an Excel management module 340 .

[0045] The data collection module 310 collects a plurality of test sample data from factory equipment.

[0046] The data analysis module 320 uses Python program to analyze and calculate the production process capability, and calculates relevant parameters of the production process capability, including process capability index (CPK), variance, mean, extreme value, etc.

[0047] The graph drawing module 330 integrates different calculation formulas according to the number of the plurality of test sample data to draw a histogram to display the distribution status of the test sample data.

[0048] The histogram distribution curve and the normal distribution curve of each test item are drawn on the same chart. Different calculation formulas are integrated according to different test sample data to draw the histogram distribution curve.

[0049] Figure 2 This is a histogram of the preferred process capability indicator (PK) of the production process capability of an embodiment of the present invention, which displays the distribution status of the test sample data through the histogram and the within group (Within) and overall (Overall) normal distribution curves, wherein the x-axis is the numerical range of the test sample data and the y-axis is the frequency range of the histogram.

[0050] Figure 3 This is a histogram of the poor CPK of the production process capability of the embodiment of the present invention. The relevant parameters include CPK, CPM, variance, mean, extreme value, etc. The factory can compare Figure 2 and Figure 3 The histogram distribution status of the test project can be used to grasp the production process status of the test project.

[0051] There are three common histogram grouping calculation formulas based on the number of test samples: Rice Rule, Square-root Rule, and Sturges' Rule. The histogram grouping method of the present invention does not use a single calculation formula, but adopts different calculation formulas based on the number of different test samples, as shown in Table 1:

[0052] Table 1

[0053]

[0054] Figure 4 The first embodiment of the present invention is to calculate the histogram of the test sample data by formula. The calculation formula for calculating the histogram grouping is used with the number of test samples as the x-axis and the number of histogram groups as the y-axis, and the curve is drawn as follows: Figure 4 As shown in the figure, the Rice Rule is the blue line, the Square-root Rule is the red line, and the Sturges' Rule is the green line. When the number of test samples is less than 64, to avoid having too few histogram groups and failing to highlight the data distribution, the Rice Rule with the largest number of groups (the first line from the top) is selected for grouping.

[0055] Figure 5 The second embodiment of the present invention is to calculate the histogram of the test sample data by formula. The calculation formula for calculating the histogram grouping is used with the number of test samples as the x-axis and the number of histogram groups as the y-axis, and the curve is drawn as follows: Figure 5As shown in the figure, the Rice Rule is the blue line, the Square-root Rule is the red line, and the Sturges' Rule is the green line. When the number of test samples is greater than 64 and less than 900, to avoid too few histogram groups and the inability to present the data distribution, the Rice Rule with the largest number of groups (the first line from the top) is selected for grouping.

[0056] Figure 6 The third embodiment of the present invention is to calculate the histogram of the test sample data by formula. The calculation formula for calculating the histogram grouping is used with the number of test samples as the x-axis and the number of histogram groups as the y-axis, and the curve is drawn as follows: Figure 6 As shown in the figure, the Rice Rule is the blue line, the Square-root Rule is the red line, and the Sturges' Rule is the green line. When the number of test samples is greater than 900, if the Square-root Rule (the first line from the top) histogram distribution is used, the number of groups will exceed 30, and too many groups will not highlight the concentration of the data. To prevent the number of groups from exceeding 30 using the Rice Rule (the second line from the top), the Sturges' Rule (the third line from the top) is selected, as it has the slowest growth in the number of groups.

[0057] The Excel management module 340 uses Excel to view the test sample data in data and graphic displays, so that the factory can evaluate the production process in an intuitive, organized, convenient and accurate manner and optimize the production process.

[0058] It is understood that the module division described above is only a logical functional division, and other division methods may be used in actual implementation. In addition, the functional modules in the various embodiments of the present application can be integrated into the same processing unit, or each module can exist physically separately, or two or more modules can be integrated into the same unit. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0059] For ordinary technicians in this field, they can make other corresponding changes or adjustments based on actual needs generated by combining the technical solutions and technical concepts provided by the embodiments of the present invention, and these changes and adjustments should fall within the scope of protection of the claims of the present invention.

Claims

1. A method for graphically displaying process data, applied to an electronic device, characterized in that: The method comprises: Collecting multiple test sample data by factory equipment; Analyze and calculate relevant parameters of production process capability; Integrating multiple calculation formulas according to the calculation results of the relevant parameters and the number of the multiple test sample data to draw a histogram to display the distribution status of the multiple test sample data; and The test sample data was viewed using Excel with numerical and graphical displays.

2. The method for graphically displaying process data according to claim 1, wherein: Also includes: The relevant parameters of the production process capability are analyzed and calculated by Python program.

3. The method for graphically displaying process data according to claim 1, wherein: The multiple calculation formulas include Rice Rule, Square-root Rule and Sturges' Rule, and also include: When the number of test samples is less than a first default value, selecting a distribution grouping number of the Rice Rule; When the number of test samples is greater than the first default value and less than the second default value, selecting the number of distribution groups of the Rice Rule; and When the number of test samples is greater than the second default value, the number of distribution groups of Sturges' Rule is selected.

4. An electronic device comprising a memory, a processor, and a program for graphically displaying process data stored in the memory and executable on the processor, the electronic device further comprising a data collection module, a data analysis module, a graph drawing module, and an Excel management module. When the program for graphically displaying process data is executed by the processor, the following steps are implemented: Collecting multiple test sample data by factory equipment; Analyze and calculate relevant parameters of production process capability; Integrating multiple calculation formulas according to the calculation results of the relevant parameters and the number of the multiple test sample data to draw a histogram to display the distribution status of the multiple test sample data; and The test sample data was viewed using Excel with numerical and graphical displays.

5. The electronic device according to claim 4, wherein: When the program for graphically displaying process data is executed by the processor, the following steps are further implemented: The relevant parameters of the production process capability are analyzed and calculated by Python program.

6. The electronic device according to claim 4, wherein: The plurality of calculation formulas include Rice Rule, Square-root Rule, and Sturges' Rule. When the program for graphically displaying process data is executed by the processor, the following steps are further implemented: When the number of test samples is less than a first default value, selecting a distribution grouping number of the Rice Rule; When the number of test samples is greater than the first default value and less than the second default value, selecting the number of distribution groups of the Rice Rule; and When the number of test samples is greater than the second default value, the number of distribution groups of Sturges' Rule is selected.

7. A storage medium having at least one computer instruction stored thereon, characterized in that: The instructions are loaded by a processor and executed by the method for graphically displaying process data according to any one of claims 1 to 3.

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