System and method for evaluating quality assurance of power equipment supplier

Abstract

The invention discloses a power equipment supplier quality assurance assessment system and method. The system comprises a hierarchical structure construction module used for obtaining a hierarchical structure model; the evaluation index scoring module is used for selecting a scoring method and formulating and executing a scoring rule of each evaluation index; the judgment matrix construction module is used for constructing each level of index judgment matrix; the weight calculation module is used for calculating the weight of each level of index judgment matrix; the comprehensive weight calculation module is used for evaluating the comprehensive weight of the index in the whole model; the consistency checking module is used for carrying out consistency ratio testing on the judgment matrix; the evaluation module is used for obtaining a final evaluation result. According to the method, on the basis of the analytic hierarchy process, the efficacy coefficient method, the accumulative score deduction method and the interval assignment method are combined, and accurate and scientific evaluation of the quality assurance of the power equipment supplier is achieved.

Description

Technical Field

[0001] The present invention relates to the field of material supplier evaluation, and in particular to a system and method for evaluating the quality assurance capability of power equipment suppliers. Background Art

[0002] With the development of China's economy and the advancement of technology, the power industry, as an important part of the national economy, has a direct impact on the safe and stable operation of the power system due to the quality of its equipment. In recent years, with the deepening of power system reform and the advancement of power marketization, power equipment suppliers are facing more intense market competition. In order to ensure the safety and reliability of power supply and improve service quality, it is an inevitable requirement to strengthen the quality assurance system construction of power equipment suppliers.

[0003] At present, in terms of quality management of power equipment suppliers, most companies have established a relatively complete quality management system. However, in actual operation, there are still some shortcomings in the quality assurance of suppliers. Traditional supplier evaluation methods are mostly focused on post-evaluation, that is, they mainly focus on the quality and performance of products after production and delivery, while ignoring pre-risk management and preventive measures. In addition, the evaluation of supplier quality assurance lacks systematicity and scientificity, resulting in the evaluation results often being inaccurate.

[0004] Therefore, it is urgent to establish a more scientific and reasonable quality assurance assessment method for power equipment suppliers in order to more effectively guarantee power supply, promote energy transformation, support grid construction and improve overall economic benefits. Summary of the invention

[0005] The purpose of the present invention is to provide a system and method for evaluating the quality assurance capability of power equipment suppliers. The present invention takes the key factors of the quality assurance capability of power equipment suppliers as the main line, and centers on the four key evaluation elements of basic capabilities, process control, finished product quality and service support. A method for evaluating the quality assurance capability of power equipment suppliers including multiple key evaluation elements and multiple evaluation indicators is proposed. At the same time, in view of the problems that the scoring method and weight distribution cannot accurately reflect the evaluation indicators, the weights are assigned through the hierarchical analysis method, and the evaluation indicators are scored by the efficiency coefficient method, the cumulative deduction method and the interval assignment method, which can realize the accurate and scientific evaluation of the quality assurance capability of power equipment suppliers.

[0006] To achieve this purpose, the present invention provides a system and method for evaluating the quality assurance capability of power equipment suppliers, including:

[0007] The hierarchical structure construction module is used to analyze the factors affecting the quality assurance of power equipment suppliers, obtain key evaluation factors and evaluation indicators, divide the evaluation indicators into different levels, take each key evaluation factor as the first-level indicator layer, and the evaluation indicators belong to each key evaluation factor. According to the level of the evaluation indicator, the evaluation indicators are composed of the remaining indicator layers at all levels. Each indicator layer in the remaining indicator layers is the indicator category of the next indicator layer. The power equipment supplier with the best quality assurance is selected as the target layer to form a hierarchical structure model together.

[0008] The evaluation index scoring module is used to select the scoring method of the evaluation index from the efficacy coefficient method, the cumulative deduction method and the interval assignment method according to the data type and distribution, formulate and implement the scoring rules for different evaluation indicators according to the selected scoring method, and assign points to each evaluation indicator according to the corresponding scoring rules;

[0009] The judgment matrix construction module is used to use the expert matrix construction method to compare the importance of evaluation indicators in each level of indicator layer, and obtain the judgment matrix of indicators at each level;

[0010] The weight calculation module is used to calculate the maximum characteristic root of each indicator judgment matrix according to the indicator judgment matrix at each level, obtain the corresponding eigenvector according to the maximum characteristic root, and normalize the eigenvector to obtain the indicator weights of the indicator judgment matrix at each level;

[0011] The comprehensive weight calculation module is used to multiply the evaluation indicator weights of the indicator judgment matrix at each level to the indicator layer corresponding to the required evaluation indicator according to the corresponding level in the hierarchical structure model, so as to obtain the comprehensive weight of the required evaluation indicator in the entire hierarchical structure model;

[0012] The consistency test module is used to perform consistency ratio test on the indicator judgment matrix at each level according to the maximum characteristic root of the indicator judgment matrix at each level;

[0013] The evaluation module is used to evaluate the quality assurance ability of the target layer power equipment supplier according to the score of each evaluation indicator and the comprehensive weight of the required evaluation indicators in the entire hierarchical structure model when the consistency ratio test is passed.

[0014] The beneficial effects of the present invention are:

[0015] 1. The power equipment supplier quality assurance capability evaluation index with multiple dimensions and multiple evaluation indicators studied in this invention, combined with the principles of scientificity and operability, can accurately and comprehensively reflect the supplier's quality assurance capability and enhance the evaluability.

[0016] 2. The power equipment supplier quality assurance evaluation weight distribution system corresponding to the evaluation indicators studied in the present invention can objectively and scientifically reflect the importance of each evaluation indicator and enhance the credibility of the evaluation.

[0017] 3. Aiming at the problem of calculating specific indicators, the present invention proposes calculation methods such as the combined efficacy coefficient method, the cumulative deduction method, and the interval assignment method according to the characteristics of the indicators, constructs a supplier quality assurance capability evaluation model, and proposes an accurate calculation method for evaluating the supplier quality assurance capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A module workflow diagram of a quality assurance capability evaluation system for power equipment suppliers of the present invention;

[0019] Figure 2 A schematic diagram of a quality assurance capability evaluation system for power equipment suppliers of a quality assurance capability evaluation system for power equipment suppliers of the present invention;

[0020] Figure 3 A schematic diagram of a primary indicator judgment matrix of a power equipment supplier quality assurance capability evaluation system of the present invention;

[0021] Figure 4 A schematic diagram of a primary index judgment matrix in an embodiment of the present invention;

[0022] Figure 5 A schematic diagram of a secondary indicator judgment matrix of basic capabilities in an embodiment of the present invention;

[0023] Figure 6 A schematic diagram of a three-level indicator judgment matrix of financial strength in an embodiment of the present invention;

[0024] Figure 7 Schematic diagram of a three-level indicator judgment matrix for on-site service capability in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0026] Embodiment 1:

[0027] like Figures 1 to 7 A quality assurance assessment system for power equipment suppliers is shown, comprising:

[0028] The hierarchical structure construction module is used to analyze the factors affecting the quality assurance of power equipment suppliers. Through principal component analysis, according to the three-level system architecture, combined with KMO and Bartlett's test analysis method, the key evaluation factors and evaluation indicators that characterize the quality assurance are screened out, and the evaluation indicators are divided into different levels. Each key evaluation factor is used as the first-level indicator layer, and the evaluation indicators belong to each key evaluation factor. According to the level of the evaluation indicator, the evaluation indicators are constructed into the remaining indicator layers. Each indicator layer in the remaining indicator layers is the indicator category of the next indicator layer. The power equipment supplier with the best quality assurance is selected as the target layer, which together constitutes a hierarchical structure model.

[0029] The above module constitutes a hierarchical result model together with the best power equipment supplier in the target layer by dividing the indicator layers at various levels. The specific composition of each indicator layer is as follows: the key evaluation factors are taken as the first-level indicator layer, and each key evaluation factor is respectively provided with multiple evaluation indicators, forming multiple second-level indicator layers. If the evaluation indicators can be further subdivided under each second-level indicator layer, these evaluation indicators constitute the third-level indicator layer.

[0030] The evaluation index scoring module is used to select the scoring method of the evaluation index from the efficacy coefficient method, the cumulative deduction method and the interval assignment method according to the data type and distribution, formulate and implement the scoring rules for different evaluation indicators according to the selected scoring method, and assign points to each evaluation indicator according to the corresponding scoring rules;

[0031] The judgment matrix construction module is used to use the expert matrix construction method to compare the importance of evaluation indicators in each level of indicator layer, and obtain the judgment matrix of indicators at each level;

[0032] The weight calculation module is used to calculate the maximum characteristic root of each indicator judgment matrix according to the indicator judgment matrix at each level, obtain the corresponding eigenvector according to the maximum characteristic root, and normalize the eigenvector to obtain the indicator weights of the indicator judgment matrix at each level;

[0033] The above module is a single sorting of the hierarchy, which refers to the indicator judgment matrix after comparing the importance of all elements in this layer pairwise for the key evaluation factors or evaluation indicators of the previous layer, calculating the weights, and performing hierarchical sorting.

[0034] The comprehensive weight calculation module is used to multiply the indicator weights of the indicator judgment matrix at each level to the indicator layer corresponding to the required evaluation indicator according to the corresponding level in the hierarchical structure model, so as to obtain the comprehensive weight of the required evaluation indicator in the entire hierarchical structure model;

[0035] The above module is the total ranking of the levels, which is the relative importance weight of the level where the required evaluation index is located to the highest level. It is multiplied step by step from the highest level to the required level. If the highest level is the first-level index level, the total ranking of its m key evaluation factors is a 1 ,…,a m , the required layer is the secondary indicator layer, and the n evaluation indicator layers are ranked as b 11 ,…,b 1n ,…,b 21 ,…,b 2n ,…,b m1 ,…,b mn ,but is the total order of the required layers, where a j is the weight of the jth key evaluation factor in the first-level indicator layer under the first-level indicator layer; b ij is the weight of the i-th evaluation indicator of the secondary indicator layer under the j-th key evaluation factor under the secondary indicator layer; b i is the weight of the i-th evaluation indicator of the secondary indicator layer at the highest level; m represents the number of key evaluation factors in the primary indicator layer; n represents the number of evaluation indicators in the secondary indicator layer (required layer) under a key scoring factor.

[0036] The consistency test module is used to perform consistency ratio test on the indicator judgment matrix at each level according to the maximum characteristic root of the indicator judgment matrix at each level.

[0037] The evaluation module is used to evaluate the quality assurance ability of the target layer power equipment supplier according to the score of each evaluation indicator and the comprehensive weight of the required evaluation indicators in the entire hierarchical structure model when the consistency ratio test is passed.

[0038] According to the required evaluation index scores obtained by the evaluation index scoring module, all the required evaluation indexes of each power equipment supplier are scored for quality. The comprehensive weights of the required evaluation indexes in the entire hierarchical structure model obtained by the comprehensive weight calculation module are multiplied and summed to obtain the evaluation score of the quality assurance ability of each power equipment supplier. The scores are sorted from small to large to select the best power equipment supplier.

[0039] The specific calculation formula is:

[0040]

[0041] Among them, F is the evaluation score of the quality assurance ability of the power equipment supplier, N is the number of evaluation indicators in the entire required layer, and w i′ is the comprehensive weight of the i′th evaluation index in the entire hierarchical structure model, s i′The quality score of the i′th required evaluation index of each power equipment supplier is assigned according to the evaluation index scoring module.

[0042] w i′ Different from the following W, W refers to the weight of all evaluation indicators in this layer, indicating the single-level ranking of the weights of all evaluation indicators at each level, while w i′ It represents the weight of the i′th evaluation indicator among all the evaluation indicators in the entire hierarchical structure model.

[0043] The present invention ensures the comprehensiveness and objectivity of the evaluation through a systematic hierarchical structure and a scientific scoring method. Normalization processing and consistency testing improve the reliability of the evaluation results and avoid the influence of subjective judgment. Through comprehensive weight calculation and comprehensive evaluation, a scientific basis is provided for decision makers to help select the best power equipment supplier, thereby improving the quality and efficiency of decision-making.

[0044] In the above technical solution, in the hierarchical structure construction module, the key evaluation factors include: basic capabilities, process control, finished product quality and service support.

[0045] Secondary evaluation indicators include:

[0046] Financial strength, research and innovation, production and capacity, and market competitiveness were selected as the evaluation indicators of basic capabilities;

[0047] Select raw material component management, key process control, and progress assurance as evaluation indicators for process control;

[0048] Select suppliers’ finished product quality control and operation quality as evaluation indicators of finished product quality;

[0049] On-site service capabilities and customer satisfaction are selected as evaluation indicators for service support.

[0050] In the above technical solution, in the evaluation index scoring module, the efficacy coefficient method is used for research innovation, market competitiveness, and operation quality; the cumulative deduction method is used for raw material component management and progress assurance; the interval assignment method is used for production and capacity, key process control, supplier finished product quality control, and on-site service capabilities;

[0051] Among them, the efficacy coefficient method first determines a pair of satisfactory values ​​and unacceptable values, with the satisfactory value as the upper limit and the unacceptable value as the lower limit, and calculates the degree to which each indicator of the evaluation object is close to the satisfactory value, and converts it into a corresponding efficacy score value; the cumulative deduction method uses the deduction event as the trigger condition and adopts a branch cumulative deduction calculation method; the interval assignment method divides the indicator value into several intervals, each interval corresponds to a specific score, and the score is directly assigned according to the indicator value corresponding to the interval.

[0052] Different quantitative indicator rules are set according to different evaluation indicators and their corresponding scoring methods.

[0053] Research innovation, market competitiveness, and operational quality use the efficacy coefficient method, with a satisfaction value of 100 points and a lower limit of 60 points; customer satisfaction also uses the efficacy coefficient method, with a satisfaction value of 100 points and a lower limit of 0 points; raw material component management and progress assurance use the cumulative deduction method, with 20 points deducted for each missing item based on the factory inspection situation, management document quality, control process execution, and key progress nodes; production and capacity, key process control, supplier finished product quality control, and on-site service capabilities use the interval assignment method, dividing 60 to 100 points into 8 intervals on average.

[0054] In the above technical solution, the secondary evaluation indicators are further divided into three levels, including:

[0055] Financial strength includes assets, liabilities, liquidity, income and returns, and is scored using the efficiency coefficient method;

[0056] On-site service capabilities include on-site service quality, on-site service timeliness and on-site service satisfaction, and are scored using the cumulative deduction method.

[0057] The financial strength is evaluated by five three-level indicators: assets, liabilities, liquidity, income and revenue, with weights of 20%, 30%, 15%, 20% and 15% of the financial strength respectively. Each indicator adopts the efficacy coefficient method, with a full score of 100 and a lower limit of 0. The field service capability is evaluated by three three-level indicators: field service quality, field service timeliness and field service satisfaction, with weights of 33.3%, 33.3% and 33.3% of the second-level indicators respectively. The cumulative deduction method is adopted, and 5 points will be deducted each time the expectations are not met.

[0058] In the above technical solution, in the judgment matrix construction module, the organization experts compare the importance of evaluation indicators in pairs according to the scales 1, 3, 5, 7, and 9, which represent the standards of not very important, slightly important, relatively important, very important, and absolutely important to the target, and construct the judgment matrix of indicators at all levels. The details are shown in Table 1:

[0059] Table 1 Scaling method of judgment matrix

[0060]

[0061] In Table 1 above, factors represent key evaluation factors at the first-level indicator level and various evaluation indicators at other levels, among which a i″j″ Indicates the importance of the i'th element relative to the j'th element. If the i'th element is slightly more important than the j'th element, then ai″j″ =3. Taking the first-level indicator judgment matrix as an example, the first-level indicator judgment matrix is ​​as follows Figure 3 shown.

[0062] In the above technical solution, in the weight calculation module, after obtaining the index judgment matrix at each level, the maximum characteristic root λ of the index judgment matrix at each level is calculated max , and obtain its corresponding eigenvector, and normalize the eigenvector to obtain W, where W is the weight of all evaluation indicators at this level.

[0063] After forming the judgment matrix of indicators at all levels, for the maximum characteristic root λ of the judgment matrix max The eigenvector of is normalized (so that the sum of the elements in the vector is 1) and recorded as W. The elements of W are the ranking weights of the relative importance of the elements at the same level to a factor at the previous level. This process is called hierarchical single sorting.

[0064] In the above technical solution, in the consistency verification module, the maximum characteristic root of the indicator judgment matrix at each level in the weight calculation module and the comprehensive weight calculation module is input into the consistency verification module, the consistency index CI and the consistency ratio CR are calculated, the consistency ratio threshold is set, and compared with the consistency ratio CR. If the consistency ratio CR is less than the consistency ratio threshold, the consistency test is passed, otherwise, it returns to the judgment matrix construction module to reconstruct the judgment matrix of the corresponding level.

[0065] Defining consistency indicators If CI = 0, there is complete consistency; if CI is close to 0, there is satisfactory consistency; if the CI is larger, the inconsistency is more serious, and n′ represents the number of evaluation indicators (key scoring factors) contained in the indicator judgment matrix of this level.

[0066] In order to measure the size of CI, the random consistency index RI is introduced, as shown in Table 2 below:

[0067] Table 2 Random consistency index RI

[0068] n 1 2 3 4 5 6 7 8 9 10 11 RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51

[0069] Defining the consistency ratio It is generally believed that when the consistency ratio CR is less than 0.1, the inconsistency of the matrix is ​​considered to be within the allowable range, with satisfactory consistency and passing the consistency test.

[0070] Embodiment 2:

[0071] A method for evaluating the quality assurance of power equipment suppliers comprises the following steps: by analyzing the factors influencing the quality assurance of power equipment suppliers, key evaluation factors and evaluation indicators are obtained, the evaluation indicators are divided into different levels, each key evaluation factor is used as a first-level indicator layer, the evaluation indicators belong to each key evaluation factor, the evaluation indicators are formed into the remaining indicator layers according to the level of the evaluation indicators, each indicator layer in the remaining indicator layers is an indicator category of the next indicator layer, and the power equipment supplier with the best quality assurance is selected as the target layer, and together they form a hierarchical structure model;

[0072] According to the data type and distribution, select the scoring method of the evaluation indicators from the efficacy coefficient method, cumulative deduction method and interval assignment method; formulate and implement scoring rules for different evaluation indicators according to the selected scoring method, and assign points to each evaluation indicator according to the corresponding scoring rules;

[0073] The expert matrix construction method is used to compare the importance of evaluation indicators in each level of indicator layer, and the judgment matrix of indicators at each level is obtained;

[0074] According to the indicator judgment matrix at each level, the maximum characteristic root of each indicator judgment matrix is ​​calculated, the corresponding eigenvector is obtained according to the maximum characteristic root, and the eigenvector is normalized to obtain the indicator weights of the indicator judgment matrix at each level;

[0075] According to the corresponding levels in the hierarchical structure model, the indicator weights of the indicator judgment matrix at each level are multiplied level by level to the indicator layer corresponding to the required evaluation indicator, so as to obtain the comprehensive weight of the required evaluation indicator in the entire hierarchical structure model;

[0076] Set the consistency ratio threshold, and perform consistency ratio test based on the maximum characteristic root of the indicator judgment matrix at each level. If the consistency ratio test fails, reconstruct the indicator judgment matrix of the corresponding level;

[0077] When the consistency ratio test is passed, the quality assurance capability of the target layer power equipment supplier is evaluated according to the scores of each evaluation indicator and the comprehensive weights of the required evaluation indicators in the entire hierarchical structure model.

[0078] The specific embodiments are as follows:

[0079] Four dimensions, namely basic capabilities, process control, finished product quality and service support, were selected as key evaluation factors and constitute the first-level indicator layer.

[0080] Financial strength, research and innovation, production and capacity, and market competitiveness were selected as evaluation indicators for basic capabilities; raw material component management, key process control, and progress assurance were selected as evaluation indicators for process control; supplier finished product quality control and operation quality were selected as evaluation indicators for finished product quality; on-site service capabilities and customer satisfaction were selected as evaluation indicators for service support, for a total of 11 evaluation indicators. The above 11 evaluation indicators are the secondary indicator layers under each key evaluation factor.

[0081] Assets, liabilities, liquidity, revenue and earnings were selected as evaluation indicators for financial strength; on-site service quality, on-site service timeliness and on-site service satisfaction were selected as evaluation indicators for on-site service capabilities.

[0082] Research and innovation, market competitiveness, and operational quality are evaluated using the efficacy coefficient method, with a satisfaction value of 100 points and a lower limit of 60 points. Customer satisfaction is also evaluated using the efficacy coefficient method, with a satisfaction value of 100 points and a lower limit of 0 points. Raw material component management and progress assurance use the cumulative deduction method, with 20 points deducted for each missing item based on the factory inspection situation, management document quality, control process execution, and key progress nodes. Production and capacity, key process control, supplier finished product quality control, and on-site service capabilities use the interval assignment method, dividing 60 to 100 points into 8 intervals on average, with 10 units in each interval.

[0083] The financial strength is evaluated by five three-level indicators: assets, liabilities, liquidity, income and revenue, with weights of 20%, 20%, 20%, 20% and 20% of the financial strength respectively. Each indicator adopts the efficacy coefficient method, with a full score of 100 and a lower limit of 0. The field service capability is evaluated by three three-level indicators: field service quality, field service timeliness and field service satisfaction, with weights of 43%, 30% and 30% of the second-level indicators respectively. The cumulative deduction method is adopted, and 5 points will be deducted each time the expectations are not met.

[0084] The organization experts were assigned to compare the importance of the evaluation indicators in pairs according to the scales of 1, 3, 5, 7, and 9, which respectively represent the standards of not very important, slightly important, relatively important, very important, and absolutely important to the goal. Using Table 1, a judgment matrix of indicators at all levels was established, such as Figure 4 , 5 , 6, and 7.

[0085] The maximum characteristic root of the first-level index judgment matrix calculated by the square root method is λ max =4.031. Calculate the first-level consistency index The random consistency index RI is taken as 0.89 by looking up the table, and finally the critical ratio is calculated. It can be determined that the matrix passes the consistency test.

[0086] Substitute the parameters of the judgment matrix into the square root method: Get an A 1 -A 4 They are: 0.841, 0.452, 2.2, 1.316 respectively, and then the weight results of the first-level judgment matrix are quoted and normalized, and the weight of basic capability in the first-level indicators accounts for 17.5%, the weight of process control accounts for 9.5%, the weight of finished product quality accounts for 45.75%, and the weight of service support accounts for 27.25%.

[0087] The calculation formula of the square root method is: A i″ Represents the geometric mean of the i″th column of the matrix.

[0088] Then, according to the calculation steps of the first-level indicator matrix weight, the second-level indicator matrix weight is calculated. Taking basic ability as an example, the corresponding second-level indicator judgment matrix is ​​obtained through expert scoring, such as Figure 5 shown.

[0089] The maximum characteristic root is calculated to be 4.061, and the critical ratio CR = 0.023 < 0.1, passing the consistency check. It can be calculated that the weights of financial strength, research and innovation, production and capacity, and market competitiveness in basic capabilities are 20.9%, 24.8%, 24.8%, and 29.5%, respectively. The total weights of financial strength, research and innovation, production and capacity, and market competitiveness are 3.6575%, 4.34%, 4.34%, and 5.1625%, respectively.

[0090] The same steps are used to calculate the weights of the three secondary indicators of process control, finished product quality and service support, and the indicator weights are shown in Table 3 below.

[0091] Table 3 Index weights at each level

[0092]

[0093]

[0094] Finally, the scores assigned to the evaluation indicators are multiplied by the corresponding weights of the evaluation indicators, and the suppliers are scored and sorted from high to low to select the best supplier.

[0095] Embodiment 3:

[0096] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0097] Embodiment 4:

[0098] A computer program product comprises a computer program, wherein the computer program implements the steps of the above method when executed by a processor.

[0099] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

Claims

1. A quality assurance evaluation system for power equipment suppliers, characterized in that: include: The hierarchical structure construction module is used to analyze the factors affecting the quality assurance of power equipment suppliers, obtain key evaluation factors and evaluation indicators, divide the evaluation indicators into different levels, take each key evaluation factor as the first-level indicator layer, and the evaluation indicators belong to each key evaluation factor. According to the level of the evaluation indicator, the evaluation indicators are composed of the remaining indicator layers at all levels. Each indicator layer in the remaining indicator layers is the indicator category of the next indicator layer. The power equipment supplier with the best quality assurance is selected as the target layer to form a hierarchical structure model together. The evaluation index scoring module is used to select the scoring method of the evaluation index from the efficacy coefficient method, the cumulative deduction method and the interval assignment method according to the data type and distribution, formulate and implement the scoring rules for different evaluation indicators according to the selected scoring method, and assign points to each evaluation indicator according to the corresponding scoring rules; The judgment matrix construction module is used to use the expert matrix construction method to compare the importance of evaluation indicators in each level of indicator layer, and obtain the judgment matrix of indicators at each level; The weight calculation module is used to calculate the maximum characteristic root of each indicator judgment matrix according to the indicator judgment matrix at each level, obtain the corresponding eigenvector according to the maximum characteristic root, and normalize the eigenvector to obtain the indicator weights of the indicator judgment matrix at each level; The comprehensive weight calculation module is used to multiply the indicator weights of the indicator judgment matrix at each level to the indicator layer corresponding to the required evaluation indicator according to the corresponding level in the hierarchical structure model, so as to obtain the comprehensive weight of the required evaluation indicator in the entire hierarchical structure model; The consistency test module is used to perform consistency ratio test on the indicator judgment matrix at each level according to the maximum characteristic root of the indicator judgment matrix at each level; The evaluation module is used to evaluate the quality assurance ability of the power equipment supplier of the target layer according to the score of each evaluation indicator and the comprehensive weight of the required evaluation indicators in the entire hierarchical structure model when the consistency ratio test is passed.

2. A power equipment supplier quality assurance assessment system according to claim 1, characterized in that: In the hierarchical structure building module, key evaluation factors include: basic capabilities, process control, finished product quality and service support; Secondary evaluation indicators include: Financial strength, research and innovation, production and capacity, and market competitiveness were selected as the evaluation indicators of basic capabilities; Select raw material component management, key process control, and progress assurance as evaluation indicators for process control; Select suppliers’ finished product quality control and operation quality as evaluation indicators of finished product quality; On-site service capabilities and customer satisfaction are selected as evaluation indicators for service support.

3. The power equipment supplier quality assurance assessment system according to claim 2, characterized in that: In the evaluation index scoring module, the efficacy coefficient method is used for research innovation, market competitiveness, and operation quality; the cumulative deduction method is used for raw material component management and progress assurance; the interval assignment method is used for production and capacity, key process control, supplier finished product quality control, and on-site service capabilities; Different quantitative indicator rules are set according to different evaluation indicators and their corresponding scoring methods.

4. The power equipment supplier quality assurance assessment system according to claim 3, characterized in that: The secondary evaluation indicators are further divided into three levels, including: Financial strength includes assets, liabilities, liquidity, income and returns, and is scored using the efficiency coefficient method; On-site service capabilities include on-site service quality, on-site service timeliness and on-site service satisfaction, and are scored using the cumulative deduction method.

5. The power equipment supplier quality assurance assessment system according to claim 1, characterized in that: In the judgment matrix construction module, the importance of evaluation indicators is compared pairwise according to the five set scales set by organizational experts, representing the standards of not very important, slightly important, relatively important, very important and absolutely important to the goal, and the judgment matrix of indicators at all levels is constructed.

6. The power equipment supplier quality assurance assessment system according to claim 1, characterized in that: In the weight calculation module, after obtaining the judgment matrix of indicators at all levels, the maximum characteristic root λ of the judgment matrix of indicators at all levels is calculated max , and obtain its corresponding eigenvector, and normalize the eigenvector to obtain W, where W is the weight of all evaluation indicators at this level.

7. The power equipment supplier quality assurance assessment system according to claim 1, characterized in that: In the consistency check module, the maximum characteristic root of the judgment matrix of each level of indicators in the weight calculation module and the comprehensive weight calculation module is input into the consistency check module, the consistency index CI and the consistency ratio CR are calculated, the consistency ratio threshold is set, and compared with the consistency ratio CR. If the consistency ratio CR is less than the consistency ratio threshold, the consistency check is passed. Otherwise, it returns to the judgment matrix construction module to reconstruct the judgment matrix of the corresponding level.

8. A method for evaluating the quality assurance capability of a power equipment supplier, characterized in that: The steps include: Analyze the factors affecting the quality assurance of power equipment suppliers, obtain key evaluation factors and evaluation indicators, divide the evaluation indicators into different levels, take each key evaluation factor as the first-level indicator layer, and the evaluation indicators belong to each key evaluation factor. According to the level of the evaluation indicators, the evaluation indicators are composed of the remaining indicator layers. Each indicator layer in the remaining indicator layers is the indicator category of the next indicator layer. Select the power equipment supplier with the best quality assurance as the target layer, and together form a hierarchical structure model; According to the data type and distribution, select the scoring method of the evaluation indicators from the efficacy coefficient method, cumulative deduction method and interval assignment method; formulate and implement scoring rules for different evaluation indicators according to the selected scoring method, and assign points to each evaluation indicator according to the corresponding scoring rules; The expert matrix construction method is used to compare the importance of evaluation indicators in each level of indicator layer, and the judgment matrix of indicators at each level is obtained; According to the indicator judgment matrix at each level, the maximum characteristic root of each indicator judgment matrix is ​​calculated, the corresponding eigenvector is obtained according to the maximum characteristic root, and the eigenvector is normalized to obtain the indicator weights of the indicator judgment matrix at each level; According to the corresponding levels in the hierarchical structure model, the indicator weights of the indicator judgment matrix at each level are multiplied level by level to the indicator layer corresponding to the required evaluation indicator, so as to obtain the comprehensive weight of the required evaluation indicator in the entire hierarchical structure model; The consistency test module is used to perform consistency ratio test on the indicator judgment matrix at each level according to the maximum characteristic root of the indicator judgment matrix at each level; When the consistency ratio test is passed, the quality assurance capability of the power equipment supplier at the target layer is evaluated according to the scores of each evaluation indicator and the comprehensive weights of the required evaluation indicators in the entire hierarchical structure model.

9. 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 method according to claim 8 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method described in claim 8 are implemented.

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