PDCA-based maintenance effect evaluation method and related device

Abstract

The invention discloses a PDCA-based maintenance effect evaluation method and a related device, and belongs to the technical field of power plant maintenance. The method comprises the following steps: establishing a maintenance effect evaluation system, and setting a target threshold value of each index in the maintenance effect evaluation system based on historical maintenance data; implementing maintenance operation and collecting actual operation data to form an evaluation data set; according to the evaluation data set, calculating an actual maintenance effect score by adopting a fuzzy comprehensive evaluation method, and comparing the score with a target threshold value to generate a maintenance effect evaluation report; and making improvement measures based on the maintenance effect evaluation report, and bringing the improvement measures into the next round of maintenance effect evaluation. According to the method, the maintenance effect is comprehensively evaluated from multiple key dimensions, fuzziness and uncertainty existing in maintenance effect evaluation are fully considered, the actual situation can be reflected more accurately, the maintenance effect can be evaluated more scientifically, comprehensively and accurately, and the maintenance management level is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power plant maintenance and relates to a maintenance effect evaluation method and related device based on PDCA (Plan-Do-Check-Act). BACKGROUND

[0002] In the field of industrial production and equipment operation and maintenance, maintenance work is a key link to ensure normal operation of equipment, prolong service life of equipment and reduce operating costs of enterprises. Equipment maintenance management is directly related to production safety, operating costs and asset life. According to statistics, about 30% of unexpected shutdowns in manufacturing industry are caused by improper maintenance strategies. Traditional maintenance effect evaluation mainly depends on a single index (such as failure rate), which is difficult to comprehensively reflect the comprehensive benefits of maintenance activities.

[0003] Traditional methods mainly focus on whether the equipment can be restored to operation, but ignore the comprehensive consideration of equipment reliability, maintenance economy and maintenance efficiency and other multi-dimensional aspects in the maintenance process. Such single-index evaluation method is difficult to comprehensively reflect the actual effectiveness of maintenance work, and is prone to one-sidedness of maintenance strategies. Moreover, the traditional evaluation method is mainly one-time evaluation, lacking in-depth analysis of the evaluation results and continuous improvement mechanism. Even if problems in maintenance work are found, it is difficult to form effective improvement measures and track the implementation effect, resulting in difficulty in continuously improving the maintenance management level.

[0004] In summary, the existing technical evaluation method has many problems such as single index, strong subjectivity and inaccuracy. These problems seriously restrict the improvement of enterprise maintenance management level and affect the production efficiency and economic benefits of enterprises. Therefore, it is urgent to develop a more scientific, comprehensive and accurate maintenance effect evaluation method to improve the maintenance management level and ensure stable operation of equipment. SUMMARY

[0005] The purpose of the present application is to provide a maintenance effect evaluation method and related device based on PDCA to solve the technical problems of single index, strong subjectivity and inaccuracy of the existing technical evaluation method.

[0006] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a maintenance effect evaluation method based on PDCA, comprising the following steps:

[0008] Establishing a maintenance effect evaluation system and setting target thresholds of each index in the maintenance effect evaluation system based on historical maintenance data;

[0009] Implementing maintenance work and collecting actual operation data to form an evaluation data set;

[0010] According to the evaluation data set, the actual maintenance effect score is calculated by using the fuzzy comprehensive evaluation method, the score is compared with the target threshold value, and a maintenance effect evaluation report is generated;

[0011] Based on the maintenance effect evaluation report, improvement measures are formulated, and the improvement measures are included in the next round of maintenance effect evaluation.

[0012] Further, the maintenance effect evaluation system includes equipment reliability indicators, maintenance economy indicators and maintenance efficiency indicators.

[0013] Further, the equipment reliability indicators include at least mean time between failures, availability, mean time to failure and failure rate; the maintenance economy indicators are calculated by a maintenance cost model; and the maintenance efficiency indicators include at least ticket response time, average maintenance time and maintenance completion rate.

[0014] Further, the expression of the maintenance cost model is:

[0015]

[0016] In the formula, C(t) represents the total maintenance cost of the system in the interval (0, t); C α (t) represents the maintenance cost function of element a in the interval (0, t); f α (t) represents the failure probability density function of element a in the interval (0, t); c α (t) represents the cost density function of element a corresponding to C α (t) in the interval (0, t);

[0017]

[0018] In the formula, represents the failure cost density function of element a in the interval (0, t); represents the maintenance cost density function of element a in the interval (0, t); c α (t) represents the total maintenance cost of element a in a preset time period.

[0019] Further, the step of implementing maintenance work and collecting actual operation data to form an evaluation data set specifically includes:

[0020] Implementing maintenance work and collecting actual operation data;

[0021] Obtaining index raw data automatically through Internet of Things sensors and maintenance work order systems;

[0022] Standardizing the collected actual operation data and index raw data to form an evaluation data set.

[0023] Further, the step of generating the maintenance effect evaluation report by comparing the actual maintenance effect score with the target threshold value based on the evaluation data set, specifically comprises:

[0024] Based on the evaluation data set, a fuzzy evaluation factor set is obtained;

[0025] The fuzzy evaluation factor set is standardized, and the quantitative index is converted into a fuzzy evaluation matrix through a membership function;

[0026] The weight of each index is determined by using a combination weighting method combined with AHP (Analytic Hierarchy Process);

[0027] The actual maintenance effect score is calculated through the fuzzy evaluation matrix and the weight of each index;

[0028] The actual maintenance effect score is compared with the target threshold value to generate the maintenance effect evaluation report.

[0029] Further, the step of formulating improvement measures based on the maintenance effect evaluation report and incorporating the improvement measures into the next round of maintenance effect evaluation, specifically comprises:

[0030] Based on the maintenance effect evaluation report, root cause analysis is performed on the indexes that do not meet the standards to generate an improvement scheme library; the maintenance strategy is optimized and the evaluation index system is updated, and the unsolved problems are transferred to the next PDCA cycle.

[0031] In a second aspect, the present application provides a maintenance effect evaluation system based on PDCA, comprising:

[0032] An evaluation system establishment module is used to establish a maintenance effect evaluation system and set the target threshold value of each index in the maintenance effect evaluation system based on historical maintenance data;

[0033] A data acquisition module is used to implement maintenance work and collect actual operation data to form an evaluation data set;

[0034] An evaluation calculation module is used to calculate the actual maintenance effect score by using a fuzzy comprehensive evaluation method based on the evaluation data set, and generate a maintenance effect evaluation report by comparing the score with the target threshold value;

[0035] An improvement cycle module is used to formulate improvement measures based on the maintenance effect evaluation report and incorporate the improvement measures into the next round of maintenance effect evaluation.

[0036] In a third aspect, the present application provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the PDCA-based maintenance effect evaluation method when executing the computer program.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, wherein the computer program is executable on a processor to implement the steps of the PDCA-based maintenance effect evaluation method.

[0038] Compared with the prior art, the present application has the following beneficial effects:

[0039] The present application discloses a PDCA-based maintenance effect evaluation method and related device, which establishes a maintenance effect evaluation system containing equipment reliability indicators, maintenance economy indicators and maintenance efficiency indicators, comprehensively evaluates the maintenance effect from multiple key dimensions, avoids the one-sidedness of single indicator evaluation, and can more accurately reflect the comprehensive effectiveness of maintenance work. The target threshold of each indicator is set according to historical maintenance data, so that the evaluation standard is objective and targeted. The fuzzy comprehensive evaluation method is used to calculate the actual maintenance effect score, fully considering the fuzziness and uncertainty existing in the maintenance effect evaluation, which can more accurately reflect the actual situation, avoid the limitation of "either-or" in the traditional evaluation method, and make the evaluation result more in line with the actual situation. The method of the present application conforms to the management concept of PDCA cycle, and integrates the maintenance effect evaluation into a continuous improvement system. Through the method, problems and deficiencies existing in the maintenance process can be found in time. Based on the evaluation result, maintenance management personnel can optimize the maintenance strategy, adjust the maintenance plan, maintenance method and resource allocation, etc., improve the scientificity and effectiveness of maintenance work, reduce the maintenance cost, and improve the equipment reliability.

[0040] Further, the present application determines the weight of each indicator by combining the AHP hierarchical analysis method, comprehensively considers subjective experience and objective data, makes the weight distribution more scientific and reasonable, can accurately reflect the importance of each indicator in the maintenance effect evaluation, and improves the accuracy and reliability of the evaluation result.

[0041] Further, root cause analysis is performed on the indicators that do not meet the standard, and an improvement scheme library is generated, which helps to deeply excavate the root causes of problems existing in the maintenance process and develop targeted improvement measures, providing strong support for the optimization of subsequent maintenance work. Optimizing the maintenance strategy and updating the evaluation indicator system, transferring the unsolved problems to the next PDCA cycle, realizes the closed-loop management of maintenance effect evaluation, continuously plans, executes, checks and processes, continuously improves the maintenance work, improves the maintenance quality and efficiency, forms a virtuous cycle. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0043] Figure 1 The flow chart of the method of the present application;

[0044] Figure 2 The principle diagram of the system of the present application;

[0045] Figure 3 The structural schematic diagram of the computer device of the present application. DETAILED DESCRIPTION

[0046] The present application will be described in detail below with reference to the drawings and in combination with the embodiments. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0047] The following detailed description is exemplary description, which aims to provide further detailed description of the present application. Unless otherwise specified, all technical terms used in the present application have the same meaning as that generally understood by the general technical personnel in the field to which the present application belongs. The terms used in the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the exemplary embodiments according to the present application.

[0048] Referring to Figure 1 The embodiment of the present application discloses a maintenance effect evaluation method based on PDCA, comprising the following steps:

[0049] S1, planning (Plan); establishing a maintenance effect evaluation system, and setting target threshold values of each index in the maintenance effect evaluation system based on historical maintenance data;

[0050] The maintenance effect evaluation system comprises equipment reliability index, maintenance economy index and maintenance efficiency index. The equipment reliability index at least comprises mean time between failures, availability, mean time to failure and failure rate; the maintenance economy index is calculated by a maintenance cost model; and the maintenance efficiency index at least comprises work order response time, average maintenance time and maintenance completion rate.

[0051] The expression of the maintenance cost model is:

[0052]

[0053] In the formula, C(t) represents the total maintenance cost of the system in the interval (0, t); Cα (t) represents the repair cost function of the element a in the interval (0, t); f α (t) represents the failure probability density function of the element a in the interval (0, t); c α (t) represents the cost density function of the element a in the interval (0, t) corresponding to C α (t).

[0054]

[0055] In the formula, represents the failure cost density function of the element a in the interval (0, t); represents the repair cost density function of the element a in the interval (0, t); c α (t) represents the total repair cost of the element a in a predetermined time period.

[0056] The present application constructs a maintenance effect evaluation system containing equipment reliability indicators (mean time between failures, availability, mean time to failure and failure rate), maintenance economy indicators (calculated through maintenance cost model) and maintenance efficiency indicators (work order response time, average repair time, repair completion rate), which can comprehensively consider maintenance work from different angles. Avoid the one-sidedness of traditional single indicator evaluation, so that enterprises can fully understand the actual effectiveness of maintenance work in ensuring stable operation of equipment, controlling cost and improving efficiency, etc.

[0057] S2, implementation (Do); implement maintenance work and collect actual operation data to form an evaluation data set;

[0058] S201, implement maintenance work and collect actual operation data;

[0059] S202, automatically obtain index raw data through Internet of Things sensors and maintenance work order system;

[0060] S203, standardize the collected actual operation data and index raw data to form an evaluation data set.

[0061] The present application automatically obtains index raw data through Internet of Things sensors and maintenance work order system, which improves the accuracy and comprehensiveness of data collection. Internet of Things sensors can monitor the running state and parameters of equipment in real time, and maintenance work order system records the detailed information of maintenance work. The combination of the two can obtain rich and accurate actual operation data, providing a reliable data basis for subsequent evaluation work. Standardizing the collected actual operation data and index raw data can eliminate the dimensional differences between different indicators, making the data comparable. After forming the evaluation data set, it is convenient for subsequent analysis and processing, which improves the efficiency and accuracy of evaluation work.

[0062] S3, check; according to the evaluation data set, the actual maintenance effect score is calculated by using the fuzzy comprehensive evaluation method, and the score is compared with the target threshold to generate a maintenance effect evaluation report.

[0063] S301, based on the evaluation data set, a fuzzy evaluation factor set is obtained;

[0064] S302, the fuzzy evaluation factor set is standardized, and the quantitative index is converted into a fuzzy evaluation matrix through a membership function;

[0065] S303, the weight of each index is determined by using the combination weighting method combined with the AHP hierarchical analysis method;

[0066] S304, the actual maintenance effect score is calculated through the fuzzy evaluation matrix and the weight of each index;

[0067] S305, the actual maintenance effect score is compared with the target threshold to generate a maintenance effect evaluation report.

[0068] S4, processing (Act); based on the maintenance effect evaluation report, improvement measures are formulated, and the improvement measures are included in the next round of maintenance effect evaluation.

[0069] Based on the maintenance effect evaluation report, the root cause analysis of the non-standard index is carried out, and an improvement scheme library is generated; the maintenance strategy is optimized and the evaluation index system is updated, and the unsolved problems are transferred to the next PDCA cycle.

[0070] The present application obtains a fuzzy evaluation factor set based on the evaluation data set, and converts the quantitative index into a fuzzy evaluation matrix through a membership function, which can fully consider the fuzziness and uncertainty of the index. The weight of each index is determined by using the combination weighting method combined with the AHP hierarchical analysis method, which comprehensively considers subjective experience and objective data, so that the weight distribution is more reasonable. The actual maintenance effect score is calculated through the fuzzy evaluation matrix and the weight of each index, which can more objectively and accurately reflect the actual effect of maintenance work. And the actual maintenance effect score is compared with the target threshold to generate a maintenance effect evaluation report, so that the enterprise can timely understand the standard reaching situation and existing problems of the maintenance work. The evaluation report provides a decision basis for the enterprise, so that the enterprise can timely adjust the maintenance strategy and plan according to the evaluation result, take targeted improvement measures, and continuously improve the maintenance management level.

[0071] Referring to Figure 2 , the present application provides a maintenance effect evaluation system based on PDCA, which comprises an evaluation system establishment module, a data acquisition module, an evaluation calculation module and an improvement cycle module.

[0072] The evaluation system establishment module is configured to establish a maintenance effect evaluation system and set target thresholds of each index in the maintenance effect evaluation system based on historical maintenance data; the data collection module is configured to implement maintenance work and collect actual operation data to form an evaluation data set; the evaluation calculation module is configured to calculate an actual maintenance effect score according to the evaluation data set by using a fuzzy comprehensive evaluation method, compare the score with the target thresholds, and generate a maintenance effect evaluation report; and the improvement cycle module is configured to develop improvement measures based on the maintenance effect evaluation report and incorporate the improvement measures into the next round of maintenance effect evaluation. The embodiment establishes a maintenance effect evaluation system including equipment reliability indexes, maintenance economy indexes and maintenance efficiency indexes, comprehensively evaluates maintenance effect from multiple key dimensions, avoids one-sidedness of single-index evaluation, and can more accurately reflect comprehensive effectiveness of maintenance work. The target thresholds of each index are set according to historical maintenance data, so that the evaluation standard is objective and targeted. The fuzzy comprehensive evaluation method is used to calculate the actual maintenance effect score, fully considers fuzziness and uncertainty existing in maintenance effect evaluation, can more accurately reflect actual situations, avoids limitations of a traditional evaluation method that is "either this or that", and makes the evaluation result more in line with actual situations. The method conforms to the management concept of the PDCA cycle, incorporates maintenance effect evaluation into a continuous improvement system. Through the method, problems and deficiencies existing in the maintenance process can be found in a timely manner. Based on the evaluation result, maintenance management personnel can optimize maintenance strategies, adjust maintenance plans, maintenance methods and resource allocation, and the like, improve scientificity and effectiveness of maintenance work, reduce maintenance costs, and improve equipment reliability.

[0073] In one embodiment of the present application, referring to Figure 3The computer device comprises a processor and a memory, the memory is used for storing a computer program, the computer program comprises program instructions, and the processor is used for executing the program instructions stored in the computer storage medium. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor is the computing core and control core of the terminal, is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement a corresponding method process or a corresponding function. The processor in the embodiment of the present application can be used for the operation of the PDCA-based maintenance effect evaluation method.

[0074] The present application also provides a storage medium, specifically a computer readable storage medium (Memory), which is a memory device in the computer device and is used for storing programs and data. It can be understood that the computer readable storage medium herein can include the built-in storage medium in the computer device, and of course can also include the expansion storage medium supported by the computer device. The computer readable storage medium provides a storage space, and the storage space stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and the instructions can be one or more computer programs (including program codes). It should be noted that the computer readable storage medium herein can be a high-speed RAM memory or a non-volatile memory such as at least one disk memory. One or more instructions stored in the computer readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the PDCA-based maintenance effect evaluation method in the above embodiment.

[0075] It should be understood by those skilled in the art that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0076] The embodiments of methods, apparatuses (systems) and computer program products are described with reference to flowcharts and / or block diagrams illustrating the functions of the flowcharts and / or blocks. It should be understood that each flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or blocks. These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufacture product including an instruction means for implementing the functions specified in the flowcharts and / or blocks. Figure 1 one or more functions specified in the flowcharts and / or blocks. Figure 1 one or more functions specified in the flowcharts and / or blocks.

[0077] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufacture product including an instruction means for implementing the functions specified in the flowcharts and / or blocks. Figure 1 one or more functions specified in the flowcharts and / or blocks. Figure 1 one or more functions specified in the flowcharts and / or blocks.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a means for implementing the functions specified in the flowcharts and / or blocks. Figure 1 one or more functions specified in the flowcharts and / or blocks. Figure 1 one or more functions specified in the flowcharts and / or blocks.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit it. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application. Any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A maintenance effect evaluation method based on PDCA, characterized in that: The following steps are involved: Establish a maintenance effect evaluation system and set target thresholds for each indicator in the maintenance effect evaluation system based on historical maintenance data; Carry out maintenance operations and collect actual operation data to form evaluation data sets; Based on the evaluation data set, the fuzzy comprehensive evaluation method is used to calculate the actual maintenance effect score, and the score is compared with the target threshold to generate a maintenance effect evaluation report; Improvement measures are formulated based on the maintenance effect evaluation report and incorporated into the next round of maintenance effect evaluation.

2. A maintenance effect evaluation method based on PDCA according to claim 1, characterized in that: The maintenance effect evaluation system includes equipment reliability index, maintenance economy index and maintenance efficiency index.

3. A maintenance effect evaluation method based on PDCA according to claim 2, characterized in that: The equipment reliability index includes at least the mean time between failures, availability, mean time between failures and failure rate; the maintenance economy index is calculated through a maintenance cost model; the maintenance efficiency index includes at least the work order response time, average maintenance time and maintenance completion rate.

4. A maintenance effect evaluation method based on PDCA according to claim 3, characterized in that: The expression of the maintenance cost model is: Where C(t) represents the total maintenance cost of the system in the interval (0, t); C α (t) represents the maintenance cost function of element α in the interval (0, t); f α (t) represents the failure probability density function of element α in the interval (0, t); c α (t) indicates that the element α in the interval (0, t) corresponds to C α (t) cost density function; Where, represents the failure cost density function of element α in the interval (0, t); represents the maintenance cost density function of element α in the interval (0, t); c α (t) represents the total maintenance cost of element α within a preset time period.

5. The maintenance effect evaluation method based on PDCA according to claim 1 is characterized in that: The steps of performing maintenance work and collecting actual operation data to form an evaluation data set specifically include: Carry out maintenance work and collect actual operation data; Automatically obtain raw indicator data through IoT sensors and maintenance work order systems; The collected actual operation data and original indicator data are standardized to form an evaluation data set.

6. The maintenance effect evaluation method based on PDCA according to claim 1 is characterized in that: The steps of calculating the actual maintenance effect score using the fuzzy comprehensive evaluation method based on the evaluation data set and comparing the score with the target threshold to generate a maintenance effect evaluation report specifically include: Based on the evaluation data set, a fuzzy evaluation factor set is obtained; The fuzzy evaluation factor set is standardized and the quantitative indicators are transformed into a fuzzy evaluation matrix through the membership function; The combined weighting method is used in combination with AHP to determine the weight of each indicator; The actual maintenance effect score is obtained through the fuzzy evaluation matrix and the weight calculation of each indicator; Compare the actual maintenance effect score with the target threshold to generate a maintenance effect evaluation report.

7. The maintenance effect evaluation method based on PDCA according to claim 1 is characterized in that: The steps of formulating improvement measures based on the maintenance effect evaluation report and incorporating the improvement measures into the next round of maintenance effect evaluation specifically include: Based on the maintenance effect evaluation report, the root cause analysis of non-compliant indicators is carried out to generate an improvement plan library; the maintenance strategy is optimized and the evaluation indicator system is updated, and unresolved issues are transferred to the next PDCA cycle.

8. A maintenance effect evaluation system based on PDCA, characterized in that: include: Evaluation system establishment module, used to establish a maintenance effect evaluation system and set target thresholds for each indicator in the maintenance effect evaluation system based on historical maintenance data; Data acquisition module, used to implement maintenance operations and collect actual operation data to form an evaluation data set; The evaluation calculation module is used to calculate the actual maintenance effect score based on the evaluation data set using the fuzzy comprehensive evaluation method, and compare the score with the target threshold to generate a maintenance effect evaluation report; The improvement cycle module is used to formulate improvement measures based on the maintenance effect evaluation report and incorporate the improvement measures into the next round of maintenance effect evaluation.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the maintenance effect evaluation method based on PDCA as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the maintenance effect evaluation method based on PDCA as claimed in any one of claims 1 to 7 are implemented.

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