Method, system and device for evaluating support capability of equipment maintenance of storage and transportation system and medium

Abstract

The application relates to the technical field of storage and transportation equipment maintenance support, in particular to a storage and transportation system equipment maintenance support capability evaluation method, system, equipment and medium, which comprises the following steps: constructing an evaluation index system of the storage and transportation system equipment maintenance support capability; defining a homologous index group and constructing a pairwise comparison matrix for each homologous index group; constructing a judgment influence factor matrix for the pairwise comparison matrix according to the storage and transportation scene of an evaluation object, performing Hadamard product operation to obtain a scene adaptation judgment matrix, and then performing analytic hierarchy process weight calculation to obtain a final index scene weight matrix; calculating the initial evaluation value of each final index, calculating the comprehensive evaluation value of the storage and transportation system maintenance support capability according to the initial evaluation value and the final index scene weight matrix, and further evaluating the equipment maintenance support capability of the evaluation object. The application can make the weights of various indexes match the actual demand in real time, overcome the unexplainable defects, and provide transparent basis for maintenance decision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of storage and transportation equipment maintenance support, in particular to a storage and transportation system equipment maintenance support capability evaluation method, system, device and medium. BACKGROUND

[0002] The maintenance support task of the storage and transportation system equipment is heavy, involves a large amount of consumption of maintenance equipment, and the system as a whole has strong correlation, and the equipment effectiveness is highly dependent on the maintenance support capability. Therefore, it is crucial to establish a scientific evaluation system to optimize resource allocation and improve support efficiency.

[0003] The existing technology mainly solves the maintenance support capability evaluation problem through a static model or a machine learning algorithm. For example, an analytic hierarchy process (AHP) is used to construct a multi-level index system, and a membership function is used to realize the comprehensive judgment of qualitative and quantitative indexes; or historical maintenance data are trained based on a neural network algorithm to generate a real-time evaluation index; another method uses principal component analysis combined with ideal point method to statically optimize the index weight and provide maintenance decision support.

[0004] However, the existing maintenance support capability evaluation methods based on static models or machine learning algorithms have obvious defects: the static evaluation mechanism cannot dynamically adjust the index weight according to the storage and transportation scene, lacks a real-time correction mechanism for the index weight, and is difficult to reflect the actual influence difference of human resources, material resources and other factors in different scenes, resulting in a disconnection between the evaluation results and actual needs; the neural network model is highly dependent on the quality and quantity of samples, and the evaluation reliability is low and the results are not interpretable when the samples are insufficient. SUMMARY

[0005] In view of the technical problems that the existing maintenance support capability evaluation methods based on static models or machine learning algorithms lack a real-time correction mechanism for the index weight, and the evaluation results are disconnected from the actual needs; the neural network model is highly dependent on the quality and quantity of samples, and the evaluation reliability is low and the results are not interpretable, the present application provides a storage and transportation system equipment maintenance support capability evaluation method, system, device and medium, which dynamically generates a scene adaptation judgment matrix to make each index weight real-time match the actual demand; based on the analytic hierarchy process, a scene weight matrix is output to overcome the uninterpretable defect and provide a transparent basis for maintenance decision.

[0006] In a first aspect, the present application provides a storage and transportation system equipment maintenance support capability evaluation method, comprising the following steps:

[0007] S1. Constructing an evaluation index system of the maintenance support capability of the storage and transportation system equipment, the evaluation index system comprising an index set having a hierarchical relationship;

[0008] In the evaluation index system, the last-level index is the bottommost index that cannot be further divided, and all the last-level indexes have the same level.

[0009] S2. Define the index set with the same direct superior index in the evaluation index system as a homologous index group, and construct a pairwise comparison matrix for each homologous index group ;

[0010] S3. According to the storage and transportation scene of the evaluation object, construct a judgment influence factor matrix for each pairwise comparison matrix The order of the judgment influence factor matrix , is the same as the corresponding ;

[0011] Wherein, the judgment influence factor matrix is dynamically generated based on scene parameters such as storage and transportation environment, cargo type, etc.

[0012] Perform Hadamard product operation on each and the corresponding to obtain the corresponding scene-adapted judgment matrix ;

[0013] Perform AHP weight calculation on all to obtain the scene-adapted weight matrix of the final-level index ;

[0014] The final-level index is a quantitative index or a qualitative index, and the value range of the quantitative index is [0, 1];

[0015] S4. Calculate the initial evaluation value of each final-level index of the evaluation object , calculate the comprehensive evaluation value of the storage and transportation system maintenance support capability according to and , and further evaluate the equipment maintenance support capability of the evaluation object.

[0016] Further need to be explained is that the level of the evaluation index system of the maintenance support capability of the storage and transportation system equipment includes:

[0017] 1 primary index: maintenance support capability index;

[0018] The maintenance support capability index includes the following 4 secondary indexes: human resource support capability index U1, material resource support capability index U2, technical resource support capability index U3 and maintenance management support capability index U4;

[0019] Each secondary index is provided with at least one tertiary index, and each tertiary index is provided with at least one fourth index as a final-level index.

[0020] Further need to be explained is that the human resource support capability index U1 includes the following 1 tertiary index: maintenance personnel index U11;

[0021] The maintenance personnel index U11 includes the following four fourth-level indexes:

[0022] The average personnel delay time rate U111 is calculated by:

[0023]

[0024] Wherein, is the average personnel delay time rate;

[0025] is the time caused by personnel delay in the i-th maintenance task;

[0026] is the total time planned for the i-th maintenance task;

[0027] is the total number of maintenance tasks;

[0028] The personnel full staffing rate U112 is calculated by:

[0029]

[0030] Wherein, is the personnel full staffing rate;

[0031] is the actual number of personnel on duty;

[0032] is the total number of staffing requirements;

[0033] The personnel competence rate U113 is calculated by:

[0034]

[0035] Wherein, is the personnel competence rate;

[0036] is the number of personnel on duty who have the required ability to perform the job;

[0037] The personnel professional matching rate U114 is calculated by:

[0038]

[0039] Wherein, is the personnel professional matching rate;

[0040] is the number of personnel whose learned profession matches the job responsibilities.

[0041] ​​It should be further explained that the material resource guarantee capability index U2 includes the following three third-level indexes: maintenance facility index U21, maintenance equipment index U22 and equipment resource index U23;

[0042] The maintenance facility index U21 includes the following three fourth-level indexes:

[0043] The maintenance facility variety matching rate U211 is calculated by:

[0044]

[0045] Wherein, is the maintenance facility variety matching rate;

[0046] is the number of maintenance facility varieties that have been equipped;

[0047] is the number of maintenance facility varieties required;

[0048] The maintenance facility quantity matching rate U212 is calculated by:

[0049]

[0050] Wherein, is the maintenance facility quantity matching rate;

[0051] is the actual number of maintenance facilities equipped;

[0052] is the number of maintenance facilities required;

[0053] The maintenance facility intact rate U213 is calculated by:

[0054]

[0055] Wherein, is the maintenance facility intact rate;

[0056] is the number of maintenance facilities that are intact and can operate normally;

[0057] The maintenance equipment index U22 includes the following three fourth-level indexes:

[0058] The maintenance equipment quantity matching rate U221 is calculated by:

[0059]

[0060] Wherein, is the maintenance equipment quantity matching rate;

[0061] Number of maintenance equipment actually equipped

[0062] Number of maintenance equipment required

[0063] Maintenance equipment intact rate U222, the calculation method is:

[0064]

[0065] Wherein, Maintenance equipment intact rate

[0066] Number of maintenance equipment intact and normal operation

[0067] Maintenance equipment variety matching rate U223, the calculation method is:

[0068]

[0069] Wherein, Maintenance equipment variety matching rate

[0070] Number of maintenance equipment equipped

[0071] Number of maintenance equipment required

[0072] Average maintenance equipment delay time rate U224, the calculation method is:

[0073]

[0074] Wherein, Average maintenance equipment delay time rate

[0075] Maintenance equipment delay time in the first Maintenance task

[0076] Equipment resource index U23 includes the following three four-level indexes:

[0077] Equipment quantity matching rate U231, the calculation method is:

[0078]

[0079] Wherein, Equipment quantity matching rate

[0080] Number of equipment actually equipped

[0081] Number of equipment required

[0082] The equipment variety matching rate U232 is calculated as follows:

[0083]

[0084] in, To improve the matching rate of equipment varieties;

[0085] This refers to the actual types and quantities of equipment provided.

[0086] The required types and quantities of equipment;

[0087] The average spare parts delay rate U233 is calculated as follows:

[0088]

[0089] in, This represents the average spare parts delay rate.

[0090] To execute the first The time lost due to spare parts during the task.

[0091] It should be further noted that the technical resource support capability indicator U3 includes the following two tertiary indicators: technical data indicator U31 and computer hardware and software resource indicator U32;

[0092] Technical data indicator U31 includes the following two level-four indicators:

[0093] The completeness of technical data U311 is calculated as follows:

[0094]

[0095] in, For the completeness of technical data;

[0096] The actual quantity of technical documents provided;

[0097] The quantity of technical documents that should be provided;

[0098] The level of informatization of technical data (U312) is a quantitative indicator, and the evaluation elements include:

[0099] The electronic coverage of technical data, including the coverage of technical documents for storage, transportation, maintenance and assurance processes;

[0100] Convenience of information retrieval;

[0101] Whether the data is integrated into the business system;

[0102] The computer software and hardware resource index U32 includes the following four fourth-level indexes:

[0103] The software matching rate U321, the calculation method is:

[0104]

[0105] Wherein, is the software matching rate;

[0106] is the actual number of software resources equipped in place;

[0107] is the number of software resources that should be equipped in place;

[0108] The hardware matching rate U322, the calculation method is:

[0109]

[0110] Wherein, is the hardware matching rate;

[0111] is the actual number of hardware resources equipped in place;

[0112] is the number of hardware resources that should be equipped in place;

[0113] The software application rate U323, the calculation method is:

[0114]

[0115] Wherein, is the software application rate;

[0116] is the number of software resources effectively supporting storage and transportation maintenance tasks;

[0117] The hardware intact rate U324, the calculation method is:

[0118]

[0119] Wherein, is the hardware intact rate;

[0120] is the number of hardware resources in normal operation.

[0121] Further, the maintenance management support capability index U4 includes the following four third-level indexes: the fund management index U41, the quality management index U42, the maintenance support command capability index U43, and the maintenance support scheme development level index U44.

[0122] The fund management index U41 includes the following two fourth-level indexes:

[0123] The fund in-place rate U411 is calculated by the following formula:

[0124]

[0125] Wherein, is the fund in-place rate;

[0126] is the total amount of actual in-place funds;

[0127] is the total budget fund amount;

[0128] The fund use efficiency U412 is a qualitative index, and the evaluation indexes include:

[0129] The plan execution matching degree; whether the fund use conforms to the plan allocation and the progress is reasonable;

[0130] The cost use compliance; whether the first payment of the expenditure cost conforms to the financial system and the use range;

[0131] The audit compliance; whether there is an audit and rectification problem;

[0132] The task completion degree; the fund expenditure matches the actual task effect;

[0133] The quality management index U42 includes the following two fourth-level indexes:

[0134] The repair failure rate U421 is calculated by the following formula:

[0135]

[0136] Wherein, is the repair failure rate;

[0137] is the number of uncompleted maintenance projects;

[0138] is the total number of maintenance projects to be completed according to the requirements;

[0139] The repair rate U422 is calculated by the following formula:

[0140]

[0141] Wherein, For the repair rate;

[0142] For the total number of repairs;

[0143] For the total number of qualified after repair;

[0144] The maintenance support command capability index U43 includes 1 four-level index:

[0145] The maintenance support command capability U431 is a qualitative index, and the evaluation index includes:

[0146] The soundness of the command organization; whether a clear command organization is established, with clear responsibilities;

[0147] Information-based command capability; whether there is effective information-based support for command;

[0148] Cross-departmental coordination capability; whether there is a good coordination and communication mechanism;

[0149] Emergency command and disposal capability; whether there is strong response and disposal capability;

[0150] The maintenance support scheme development level index U44 includes 1 four-level index:

[0151] The maintenance support scheme development level U441 is a qualitative index, and the evaluation index includes:

[0152] The completeness of the scheme; whether it includes target tasks, task decomposition, personnel arrangement, material support, emergency measures, etc.;

[0153] The executability of the scheme; whether the process is smooth and the resource allocation is reasonable;

[0154] Emergency plan equipment; whether emergency plans for sudden failures, etc. are developed.

[0155] Further need to be explained is that in step S2, the pairwise comparison matrix is a matrix, n is the number of indexes included in the corresponding homologous index group; Each element in the matrix represents the importance scale value of index relative to index , which is a real number greater than 0, and are reciprocals of each other;

[0156] Further need to be explained is that in step S3, each element of the influence factor matrix is the importance scale value of index relative to index The importance scenario correction coefficient is a non-negative real number. The larger the value, the more significant the impact. .

[0157] It should be further noted that, in one embodiment of the present invention, in step S3, and They are reciprocals of each other;

[0158] In another embodiment of the invention, in step S3:

[0159] When the indicator and indicators When it is effective in this storage and transportation scenario, and They are reciprocals of each other;

[0160] When the indicator In the event of failure in this storage and transportation scenario, .

[0161] It should be further noted that, in one embodiment of the present invention, The value can be 0 or 1.

[0162] It should be further noted that in step S3, the adaptation judgment matrix for all scenes is... The weight calculation for the analytic hierarchy process includes:

[0163] S301. Will Column-normalized matrix is ​​obtained by standardizing the columns. ;

[0164] S302. The matrix Adding rows together yields a one-dimensional matrix.

[0165] S303. Transform a one-dimensional matrix Standardization yields the partition weight matrix. ;

[0166] S304. Calculation

[0167]

[0168] in, For the first Contextualized weighting of each final-level indicator;

[0169] The level of the final indicator;

[0170] For the first The first level indicator belongs to the first The value of the first level indicator in the corresponding partition weight matrix ;

[0171] S305. All The total number of the final level indicators is summarized as the final level indicator scenario weight matrix , The total number of the final level indicators is summarized as the final level indicator scenario weight matrix

[0172] Further, after obtaining the partition weight matrix in S303, consistency test is performed, including:

[0173] S3031. According to the one-dimensional matrix , :

[0174]

[0175] is the maximum eigenvalue;

[0176] is the value of the first level indicator in the one-dimensional matrix ;

[0177] S3032. Calculate :

[0178]

[0179] is the consistency indicator;

[0180] S3033. Calculate the consistency ratio :

[0181]

[0182] is the average random consistency indicator corresponding to the matrix order;

[0183] S3034. Determine the matrix consistency:

[0184] When , it is determined that the partition weight matrix passes the consistency test, and the next step can be directly executed;

[0185] When , it is determined that the partition weight matrix does not pass the consistency test and needs to be corrected.

[0186] Further, in step S4, the method for calculating the initial evaluation value of each final level indicator of the evaluation object includes:​

[0187] When the final-level index is a quantitative index, the calculated value of the quantitative index is taken as the initial evaluation value of the final-level index;

[0188] When the final-level index is a qualitative index, the evaluation result of the final-level index is quantified by a membership function to obtain a qualitative quantification value, and the qualitative quantification value is taken as the initial evaluation value of the final-level index, and the value range of the qualitative quantification value is [0, 1].

[0189] It is further explained that the evaluation result of the final-level index includes excellent, good, medium, poor, and extremely poor;

[0190] Quantifying the evaluation result of the final-level index by the membership function includes: mapping the evaluation result of the final-level index to a numerical value, wherein excellent corresponds to (0.9, 1.0], good corresponds to (0.8, 0.9], medium corresponds to (0.6, 0.8], poor corresponds to (0.4, 0.6], and extremely poor corresponds to (0, 0.4].

[0191] It is further explained that in step S4, the step of calculating the comprehensive evaluation value of the maintenance support capability of the storage and transportation system according to the initial evaluation value and the scenario-based weight matrix of the final-level index includes:

[0192] The initial evaluation value is constructed into an evaluation matrix ;

[0193] The comprehensive evaluation value of the maintenance support capability of the storage and transportation system is calculated :

[0194]

[0195] The value range of the comprehensive evaluation value of the maintenance support capability of the storage and transportation system is [0, 1].

[0196] It is further explained that in step S4, the equipment maintenance support capability of the evaluation object is evaluated by one or more of the following methods:

[0197] A qualified threshold of the comprehensive evaluation value of the maintenance support capability of the storage and transportation system is set, and when the comprehensive evaluation value of the maintenance support capability of the storage and transportation system of the evaluation object is greater than or equal to the qualified threshold, it is determined that the maintenance support capability of the evaluation object is qualified, otherwise it is unqualified;

[0198] The comprehensive evaluation values of the maintenance support capabilities of the storage and transportation systems of multiple evaluation objects are calculated and sorted, and the evaluation object with a higher comprehensive evaluation value of the maintenance support capability of the storage and transportation system has a stronger maintenance support capability.

[0199] In a second aspect, the application provides a storage and transportation system equipment maintenance support capability evaluation system for implementing the above-mentioned storage and transportation system equipment maintenance support capability evaluation method, which comprises:

[0200] The evaluation index system construction module is configured to construct an evaluation index system of the maintenance support capability of the storage and transportation system equipment;

[0201] The comparison matrix construction module is configured to define a set of indexes with the same direct superior index in the evaluation index system as a homologous index group, and construct a pairwise comparison matrix for each homologous index group;

[0202] The scene adaptation judgment matrix construction and weight calculation module is configured to construct a judgment influence factor matrix for each pairwise comparison matrix according to the storage and transportation scene of the evaluation object, perform Hadamard product operation to obtain a corresponding scene adaptation judgment matrix, and perform analytic hierarchy process weight calculation to obtain a scene-weighted matrix of the final-level indexes;

[0203] The evaluation value calculation and capability evaluation module is configured to calculate an initial evaluation value of each final-level index of the evaluation object, calculate a comprehensive evaluation value of the maintenance support capability of the storage and transportation system, and further evaluate the equipment maintenance support capability of the evaluation object.

[0204] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of the above-mentioned evaluation method for the maintenance support capability of the storage and transportation system equipment when executing the computer program.

[0205] In a fourth aspect, the present application provides a storage medium, wherein the storage medium stores a computer program, and the computer program is executable on a processor to implement the steps of the above-mentioned evaluation method for the maintenance support capability of the storage and transportation system equipment.

[0206] From the above technical solutions, the present application has the following advantages:

[0207] 1. The present application solves the problem that a static model cannot dynamically adapt to a scene by constructing an evaluation index system and defining a homologous index group, constructing a pairwise comparison matrix for each homologous index group, constructing a judgment influence factor matrix in combination with a storage and transportation scene, generating a scene adaptation judgment matrix through Hadamard product operation, and calculating a scene-weighted matrix of final-level indexes according to the scene adaptation judgment matrix, and assigns a weight to each final-level index through the scene-weighted matrix of the final-level indexes, thereby realizing real-time adjustment of the index weight with changes in the storage environment, making the evaluation result more in line with actual support needs.

[0208] 2. The present application ensures reasonable weight distribution by performing analytic hierarchy process weight calculation on the scene adaptation judgment matrix, thereby solving the problems of dependence on samples and uninterpretable results of a neural network model, and realizing a transparent and controllable evaluation process to provide a traceable basis for maintenance support decision-making.

[0209] 3. The application solves the problem of heterogeneous data fusion by uniformly calculating the initial evaluation values of quantitative indicators and qualitative indicators, combining with a scenario weight matrix to calculate a comprehensive evaluation value, and integrating the quantitative indicators and the qualitative indicators into the same evaluation framework, so that the real level of the support capability can be comprehensively reflected. BRIEF DESCRIPTION OF DRAWINGS

[0210] In order to more clearly illustrate the technical solutions of the present application, the drawings required to be used in the description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort.

[0211] Figure 1 is a flow chart of the support capability evaluation method of the storage and transportation system equipment in an embodiment of the present application.

[0212] Figure 2 is a schematic block diagram of the support capability evaluation system of the storage and transportation system equipment in an embodiment of the present application.

[0213] Figure 3 is a schematic diagram of the hardware structure of the electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0214] In order to make the application purposes, features and advantages of the present application more obvious and easy to understand, the technical solutions protected by the present application will be described clearly and completely by using specific embodiments and drawings. Obviously, the following described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present patent, all other embodiments obtained by those skilled in the art without any creative effort are within the scope of the present patent.

[0215] The support capability evaluation method of the storage and transportation system equipment related to the present application will be described in detail below. In order to illustrate but not to limit, specific details such as specific system structures and technologies are proposed to thoroughly understand the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details.

[0216] In the support capability evaluation method of the storage and transportation system equipment related to the present application, the term "comprising" indicates the existence of the described features, whole, steps, operations, elements and / or components, but does not exclude the existence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof. The terms "comprising", "including", "having" and their variants mean "including but not limited to", unless otherwise specifically emphasized.

[0217] In order to clearly describe the technical solutions of the present application, the terms "first", "second", etc. are used to distinguish the same or similar items or functions with basically the same function and role. Those skilled in the art can understand that the terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. also do not necessarily mean different.

[0218] The phrases "one embodiment", "some embodiments" and the like as used in the present disclosure mean that the particular feature, structure, or characteristic following the phrase is included in at least one embodiment of the present application. Thus, the appearances of "in one embodiment", "in some embodiments", "in other embodiments", "in additional embodiments", and the like in various places in the specification are not necessarily all referring to the same embodiment, unless otherwise specifically noted.

[0219] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0220] The method for evaluating the maintenance support capability of a storage and transportation system equipment provided in the embodiments of the present application is executed by a computer device, and accordingly, the evaluation system for the maintenance support capability of the storage and transportation system equipment runs in the computer device.

[0221] Figure 1 The flowchart of the method for evaluating the maintenance support capability of a storage and transportation system equipment is an embodiment of the present application. In the flowchart, Figure 1 The execution subject can be an evaluation system for the maintenance support capability of a storage and transportation system equipment. The order of the steps in the flowchart can be changed according to different requirements, and some steps can be omitted.

[0222] As Figure 1 shown, the method for evaluating the maintenance support capability of a storage and transportation system equipment includes:

[0223] In step S1, an evaluation index system for the maintenance support capability of a storage and transportation system equipment is constructed, and the evaluation index system includes a set of indexes with a hierarchical relationship.

[0224] In the evaluation index system, the last-level indexes are the bottom-layer indexes that cannot be further divided, and all the last-level indexes have the same level.

[0225] Through the hierarchical index design and the standardization of the last-level indexes, a systematic evaluation framework is constructed to solve the fragmentation problem of the evaluation dimensions and provide a structured basis for subsequent calculation.

[0226] In some specific embodiments, the level of the evaluation index system for the maintenance support capability of a storage and transportation system equipment includes:

[0227] 1 first-level index: maintenance support capability index;

[0228] The maintenance support capability indexes include the following four second-level indexes: a human resource support capability index U1, a material resource support capability index U2, a technical resource support capability index U3, and a maintenance management support capability index U4;

[0229] Each second-level index is provided with at least one third-level index, and each third-level index is provided with at least one fourth-level index as a final-level index.

[0230] The four-dimensional second-level index framework of "human resources-material resources-technical resources-maintenance management" and the downward expansion mechanism are used to build a complete capability evaluation dimension, and solve the problem of non-systematic evaluation coverage

[0231] In some specific embodiments, the human resource support capability index U1 includes the following one third-level index: a maintenance personnel index U11.

[0232] The maintenance personnel index U11 includes the following four fourth-level indexes:

[0233] The average personnel delay time rate U111 is calculated by:

[0234]

[0235] Wherein, is the average personnel delay time rate;

[0236] is the time of delay caused by personnel in the i-th maintenance task;

[0237] is the total time of the i-th maintenance task plan execution;

[0238] is the total number of maintenance tasks;

[0239] The personnel full staffing rate U112 is calculated by:

[0240]

[0241] Wherein, is the personnel full staffing rate;

[0242] is the actual number of personnel on duty;

[0243] is the total number of staffing requirements;

[0244] The personnel competence rate U113 is calculated by:

[0245] ​​

[0246] wherein, is the personnel competency rate;

[0247] is the number of personnel in the on-duty personnel number who can meet the requirements of the post;

[0248] The personnel professional matching rate U114 is calculated by the following formula:

[0249]

[0250] wherein, is the personnel professional matching rate;

[0251] is the number of personnel whose learned major matches the post duties.

[0252] The standardization and quantification system of human resources is established by the personnel delay rate / full staffing rate / competency rate / professional matching rate four four-level index calculation formulas, and the problem of missing evaluation dimensions of personnel support capacity is solved.

[0253] In some specific embodiments, the material resource support capacity index U2 includes the following three three-level indexes: maintenance facility index U21, maintenance equipment index U22, and equipment resource index U23;

[0254] The maintenance facility index U21 includes the following three four-level indexes:

[0255] The maintenance facility variety matching rate U211 is calculated by the following formula:

[0256]

[0257] wherein, is the maintenance facility variety matching rate;

[0258] is the number of types of maintenance facilities that have been equipped;

[0259] is the number of types of maintenance facilities required;

[0260] The maintenance facility quantity matching rate U212 is calculated by the following formula:

[0261]

[0262] wherein, is the maintenance facility quantity matching rate;

[0263] is the number of maintenance facilities actually equipped;

[0264] The number of maintenance facilities required;

[0265] The maintenance facility intact rate U213 is calculated by:

[0266]

[0267] Wherein, The maintenance facility intact rate;

[0268] The number of maintenance facilities in good condition and capable of normal operation;

[0269] The maintenance equipment index U22 includes the following three fourth-level indexes:

[0270] The maintenance equipment number matching rate U221 is calculated by:

[0271]

[0272] Wherein, The maintenance equipment number matching rate;

[0273] The actual number of maintenance equipment;

[0274] The number of maintenance equipment required;

[0275] The maintenance equipment intact rate U222 is calculated by:

[0276]

[0277] Wherein, The maintenance equipment intact rate;

[0278] The number of maintenance equipment in good condition and capable of normal operation;

[0279] The maintenance equipment variety matching rate U223 is calculated by:

[0280]

[0281] Wherein, The maintenance equipment variety matching rate;

[0282] The number of maintenance equipment varieties equipped;

[0283] The number of maintenance equipment required;

[0284] The average maintenance equipment delay time rate U224 is calculated by:

[0285]

[0286] Wherein, is the average maintenance equipment delay time rate;

[0287] is the time of the maintenance equipment delay in the first maintenance task;

[0288] The equipment resource index U23 includes the following three fourth-level indexes:

[0289] The equipment quantity matching rate U231 is calculated by:

[0290]

[0291] Wherein, is the equipment quantity matching rate;

[0292] is the actual number of equipment;

[0293] is the required number of equipment;

[0294] The equipment variety matching rate U232 is calculated by:

[0295]

[0296] Wherein, is the equipment variety matching rate;

[0297] is the actual number of equipment varieties;

[0298] is the required number of equipment varieties;

[0299] The average spare parts delay time rate U233 is calculated by:

[0300]

[0301] Wherein, is the average spare parts delay time rate;

[0302] is the time of the first task due to spare parts delay.

[0303] Through the design of seven quantitative indicators in the fields of facilities, equipment and materials, the full-factor measurement of material resource support capacity is realized, and the problem of incomplete evaluation of resource allocation effectiveness is solved.

[0304] In some embodiments, the technical resource guarantee capability index U3 includes the following two third-level indexes: technical material index U31 and computer software and hardware resource index U32.

[0305] The technical material index U31 includes the following two fourth-level indexes:

[0306] The completeness of technical material U311, the calculation method is:

[0307]

[0308] Wherein, is the completeness of technical material;

[0309] is the number of actual equipped technical materials;

[0310] is the number of technical materials that should be equipped;

[0311] The informatization degree of technical material U312 is a quantitative index, and the evaluation elements include:

[0312] The electronic coverage rate of technical material, including the coverage degree of technical documents in storage, transportation and maintenance guarantee process;

[0313] The convenience of data query;

[0314] Whether the data is integrated into the business system;

[0315] The computer software and hardware resource index U32 includes the following four fourth-level indexes:

[0316] The software matching rate U321, the calculation method is:

[0317]

[0318] Wherein, is the software matching rate;

[0319] is the number of actual equipped software resources;

[0320] is the number of software resources that should be equipped;

[0321] The hardware matching rate U322, the calculation method is:

[0322]

[0323] Wherein, is the hardware matching rate;

[0324] is the number of actual equipped hardware resources;

[0325] the number of hardware resources that should be equipped in place;

[0326] a software applicability rate U323, the calculation method of which is:

[0327]

[0328] wherein, is the software applicability rate;

[0329] the number of software resources that effectively support storage, transportation and maintenance tasks;

[0330] a hardware integrity rate U324, the calculation method of which is:

[0331]

[0332] wherein, is the hardware integrity rate;

[0333] the number of hardware resources in normal operation.

[0334] Through the combination of technical data completeness / informationization degree and software and hardware matching rate / applicability rate, an evaluation standard of technical resource digitalization level is constructed to solve the problem that technical support capability is difficult to quantify.

[0335] In some specific embodiments, the maintenance management support capability index U4 includes the following 4 third-level indexes: a fund management index U41, a quality management index U42, a maintenance support command capability index U43 and a maintenance support scheme development level index U44;

[0336] The fund management index U41 includes the following 2 fourth-level indexes: a fund availability rate U411 and a fund use efficiency U412;

[0337] The fund availability rate U411, the calculation method of which is:

[0338]

[0339] wherein, is the fund availability rate;

[0340] the total amount of actual funds in place;

[0341] the total amount of budget funds;

[0342] The fund use efficiency U412 is a qualitative index, and the evaluation indexes include:

[0343] Plan implementation matching degree; whether the use of funds is in line with the plan allocation, and whether the progress is reasonable;

[0344] Cost use compliance; whether the payment of expenses is in line with the financial system and the scope of use;

[0345] Audit compliance; whether there are audit and rectification problems;

[0346] Task completion degree; whether the expenditure of funds matches the actual task effect;

[0347] The quality management index U42 includes the following two fourth-level indexes:

[0348] The repair failure rate U421 is calculated as follows:

[0349]

[0350] Wherein, is the repair failure rate;

[0351] is the number of uncompleted repair projects;

[0352] is the total number of repair projects that should be completed according to the requirements;

[0353] The repair return rate U422 is calculated as follows:

[0354]

[0355] Wherein, is the repair return rate;

[0356] is the total number of repairs;

[0357] is the total number of qualified after repair;

[0358] The maintenance support command capability index U43 includes one fourth-level index:

[0359] The maintenance support command capability U431 is a qualitative index, and the evaluation indexes include:

[0360] The soundness of the command organization; whether a clear command organization is established, and the responsibilities are clear;

[0361] Informationized command capability; whether there is effective informationized support command;

[0362] Cross-department coordination capability; whether there is a good coordination and communication mechanism;

[0363] Emergency command and disposal capability; whether there is strong response and disposal capability;

[0364] The maintenance support scheme formulation level indicator U44 includes one fourth-level indicator:

[0365] The maintenance support scheme formulation level U441 is a qualitative indicator, and the evaluation indicators include:

[0366] The completeness of the scheme; whether it includes target tasks, task decomposition, personnel arrangement, material support, emergency measures, etc.

[0367] The executability of the scheme; whether the process is smooth and the resource allocation is reasonable.

[0368] Emergency plan equipment; whether emergency plans for sudden failures are formulated.

[0369] Through the qualitative and quantitative mixed design of the four types of management indicators of funds / quality / command / scheme, a comprehensive evaluation mechanism of management efficiency is established to solve the problem of difficult inclusion of soft indicators in the evaluation system.

[0370] Step S2, define the set of indicators with the same direct superior indicator in the evaluation index system as a homologous indicator group, and construct a pairwise comparison matrix for each homologous indicator group .

[0371] By defining the homologous indicator group and constructing the pairwise comparison matrix, a mathematical expression model of the relative importance between indicators is established to solve the randomness of subjective weight allocation.

[0372] In some specific embodiments, the pairwise comparison matrix is a matrix, n where n is the number of indicators included in the corresponding homologous indicator group; Each element in the matrix represents the importance scale value of indicator relative to indicator , which is a real number greater than 0, and .

[0373] Through the reciprocal constraint design of the pairwise comparison matrix, the mathematical rigor of the scene correction operation is guaranteed, and the logical conflict risk of the pairwise comparison matrix is solved.

[0374] Step S3, according to the storage and transportation scene of the evaluation object, construct a judgment influence factor matrix for each pairwise comparison matrix , where the order of the matrix is the same as the corresponding ;

[0375] For each and the corresponding Perform the Hadamard product operation to obtain the corresponding scene adaptation judgment matrix. ;

[0376] For all Perform weight calculation using the analytic hierarchy process (AHP) to obtain the scenario-based weight matrix for the final-level indicators. ;

[0377] The final level indicators are either quantitative or qualitative, with the value range of quantitative indicators being [0,1].

[0378] By generating a scenario adaptation judgment matrix through the product operation of the influencing factor matrix and Hadamard, and combining it with the analytic hierarchy process to calculate the scenario-based weight matrix of the final-level indicators, the problem of rigid evaluation standards under different environmental conditions can be solved.

[0379] In some specific embodiments, the influencing factor matrix is ​​determined. Each element As an indicator relative to indicators The importance scenario correction coefficient is a non-negative real number; a larger value indicates a more significant impact. .

[0380] By clarifying the physical meaning and mathematical properties of matrix elements, abstract scene influences are transformed into quantifiable correction coefficients, ensuring the feasibility of the calculation; by specifying... This establishes a benchmark for comparing the indicators themselves, providing a logical starting point and numerical stability for the entire evaluation model.

[0381] In some specific embodiments, and They are reciprocals of each other.

[0382] By regulations and The reciprocals of each other ensure that the matrix satisfies the positive reciprocity property, strictly adhering to the theoretical foundation of the analytic hierarchy process and guaranteeing the logical consistency of the importance judgment among different indicators.

[0383] In some specific embodiments, when the index and indicators When it is effective in this storage and transportation scenario, and They are reciprocals of each other;

[0384] When the indicator In the event of failure in this storage and transportation scenario, .

[0385] By distinguishing the effective and ineffective states of the indicators and adopting different assignment strategies, the ineffective state is completely shielded by zeroing, thereby enhancing the robustness and practicality of the scheme in real complex storage and transportation scenarios, and preventing invalid data from polluting the evaluation results.

[0386] In some specific embodiments, The value of the indicator is 0 or 1.

[0387] By adopting binary values, the parameter setting is greatly simplified, the complex correction judgment is converted into a binary decision of "whether to correct", and the operation complexity is significantly reduced, which is suitable for scenarios with low precision requirements or the need for rapid response.

[0388] In some specific embodiments, the judgment matrix is adapted to all scenarios The analytic hierarchy process weight calculation includes:

[0389] S301. The matrix is standardized by column to obtain a column standardized matrix ;

[0390] S302. The matrix is added by row to obtain a one-dimensional matrix

[0391] S303. The one-dimensional matrix is standardized to obtain a partition weight matrix ;

[0392] S304. The value of the indicator is calculated

[0393]

[0394] wherein, is the weighting of the scene of the i-th end-level indicator;

[0395] is the number of end-level indicators;

[0396] is the value of the i-th end-level indicator in the corresponding partition weight matrix

[0397] S305. All are summarized as an end-level indicator scene weighting matrix , is the total number of end-level indicators.

[0398] ​​​​​​​The model of weight accumulation along the hierarchy keeps the internal consistency of the evaluation system and solves the problem of weight distribution fragmentation of multi-level indicators.

[0399] In some embodiments, after obtaining the partition weight matrix in S303, consistency check is performed, including:

[0400] S3031. According to the one-dimensional matrix Calculate :

[0401]

[0402] is the maximum eigenvalue;

[0403] is the value of the i-th indicator in the one-dimensional matrix

[0404] S3032. Calculate :

[0405]

[0406] is the consistency index;

[0407] S3033. Calculate the consistency ratio :

[0408]

[0409] is the average random consistency index corresponding to the matrix order;

[0410] S3034. Judge the consistency of the matrix:

[0411] When , it is judged that the partition weight matrix passes the consistency check and the next step can be directly executed;

[0412] When , it is judged that the partition weight matrix does not pass the consistency check and needs to be corrected.

[0413] The steps and threshold settings of the consistency check provide an objective criterion for the rationality of the weight and solve the risk of distortion of subjective judgment.

[0414] Step S4, calculate the initial evaluation value of each terminal indicator of the evaluation object , according to and ​​The maintenance support capability comprehensive evaluation value of the storage and transportation system is calculated, and then the equipment maintenance support capability of the evaluation object is evaluated.

[0415] By fusing the initial evaluation value of the last-level index and the last-level index scene weighting matrix, the multi-dimensional capability index is objectively integrated, and the problem of poor comparability of the comprehensive evaluation result is solved.

[0416] In some embodiments, the method for calculating the initial evaluation value of each last-level index of the evaluation object comprises:

[0417] When the last-level index is a quantitative index, the calculated value of the quantitative index is taken as the initial evaluation value of the last-level index.

[0418] When the last-level index is a qualitative index, the evaluation result of the last-level index is quantified by a membership function to obtain a qualitative quantified value, and the qualitative quantified value is taken as the initial evaluation value of the last-level index, and the value range of the qualitative quantified value is [0, 1].

[0419] By the dual-track mechanism of quantitative direct calculation and qualitative membership conversion, the standardization processing of heterogeneous indexes is realized, and the problem of mixed data integration is solved.

[0420] In some embodiments, the evaluation result of the last-level index comprises excellent, good, medium, poor and extremely poor.

[0421] Quantifying the evaluation result of the last-level index by the membership function comprises: mapping the evaluation result of the last-level index to a numerical value, wherein excellent corresponds to (0.9, 1.0], good corresponds to (0.8, 0.9], medium corresponds to (0.6, 0.8], poor corresponds to (0.4, 0.6], and extremely poor corresponds to (0, 0.4].

[0422] By the segmented mapping rule of five-level evaluation to the interval (0, 1], the quantification standard of the qualitative index is unified, and the problem of different subjective evaluation scales is solved.

[0423] In some embodiments, the step of calculating the maintenance support capability comprehensive evaluation value of the storage and transportation system according to the initial evaluation value and the last-level index scene weighting matrix comprises:

[0424] The initial evaluation value is constructed as an evaluation matrix ;

[0425] The maintenance support capability comprehensive evaluation value of the storage and transportation system is calculated :

[0426]

[0427] The value range of the maintenance support capability comprehensive evaluation value of the storage and transportation system is [0, 1].

[0428] The single storage and transportation system maintenance support capability comprehensive evaluation value is generated by a weighted average algorithm of the scenario weighting matrix and the evaluation value matrix, and the multi-dimensional index decision difficulty problem is solved.

[0429] In some specific embodiments, the equipment maintenance support capability of the evaluation object is evaluated by using one or more of the following methods:

[0430] The qualified threshold of the storage and transportation system maintenance support capability comprehensive evaluation value is set, and when the storage and transportation system maintenance support capability comprehensive evaluation value of the evaluation object is greater than or equal to the qualified threshold, it is determined that the maintenance support capability of the evaluation object is qualified, otherwise it is unqualified;

[0431] The storage and transportation system maintenance support capability comprehensive evaluation values of a plurality of evaluation objects are calculated and sorted, and the evaluation object with a higher storage and transportation system maintenance support capability comprehensive evaluation value has a stronger maintenance support capability.

[0432] Through the dual evaluation mechanism of threshold determination and multi-object sorting, an operable evaluation standard of the maintenance support capability is provided, and the weak application problem of the evaluation result is solved.

[0433] In one specific embodiment, the steps of the storage and transportation system equipment maintenance support capability evaluation method include:

[0434] Step S1, constructing an evaluation index system of the storage and transportation system equipment maintenance support capability, the evaluation index system including a set of indexes with hierarchical relationship, a total of four levels of indexes, wherein the fourth level of indexes is the last level of indexes;

[0435] The specific setting of the evaluation index system is shown in Table 1.

[0436] Table 1 Evaluation index system table

[0437]

[0438] Step S2, defining a set of indexes with the same direct superior index in the evaluation index system as a homologous index group, and constructing a pairwise comparison matrix for each homologous index group ;

[0439] Pairwise comparison matrix is a order matrix, n is the number of indexes included in the corresponding homologous index group; Each element in the matrix represents the importance scale value of the index relative to the index , and are reciprocal, ;

[0440] The importance scale values ​​are set according to the rules in Table 2.

[0441] Table 2 Scale Comparison Table

[0442]

[0443] Step S3: Based on the storage and transportation scenario of the evaluation object, generate a pairwise comparison matrix for each object. Construct a matrix of influencing factors , The order and the corresponding same;

[0444] Determine the influencing factor matrix Each element As an indicator relative to indicators The importance scenario correction coefficient is a non-negative real number; a larger value indicates a more significant impact. and They are reciprocals of each other. ;

[0445] For each With the corresponding Perform the Hadamard product operation to obtain the corresponding scene adaptation judgment matrix. ;

[0446] For all Perform weight calculation using the analytic hierarchy process (AHP) to obtain the scenario-based weight matrix for the final-level indicators. ;

[0447] The final level indicators are either quantitative or qualitative, with the range of values ​​for quantitative indicators being [0,1].

[0448] Adaptation judgment matrix for all scenarios The weight calculation for the analytic hierarchy process includes:

[0449] S301. Will Column-normalized matrix is ​​obtained by standardizing the columns. ;

[0450] S302. The matrix Adding rows together yields a one-dimensional matrix.

[0451] S303. Transform a one-dimensional matrix Standardization yields the partition weight matrix. ;

[0452] Perform consistency checks, including:

[0453] S3031. Based on a one-dimensional matrix calculate :

[0454]

[0455] It is the largest eigenvalue;

[0456] A one-dimensional matrix The Middle The values ​​of each indicator;

[0457] S3032. Calculation :

[0458]

[0459] As a consistency indicator;

[0460] S3033. Calculate the consistency ratio :

[0461]

[0462] The average random consistency index corresponding to the matrix order. The values ​​of are shown in Table 3;

[0463] Table 3 Average Random Consistency Index Value table

[0464]

[0465] S3034. Determine matrix consistency:

[0466] when At that time, determine the partition weight matrix If the consistency check is passed, the next step can be executed directly;

[0467] when At that time, determine the partition weight matrix The consistency check failed and needs to be corrected.

[0468] S304. Calculation

[0469]

[0470] in, For the first Contextualized weighting of each final-level indicator;

[0471] The level of the final indicator;

[0472] the first level index to which the first last level index belongs in the corresponding partition weight matrix ;

[0473] S305. Sum up all the last level index to obtain a last level index scenario weight matrix , wherein the total number of the last level indexes is

[0474] Step S4, calculating an initial evaluation value of each last level index of the evaluation object , and calculating a comprehensive evaluation value of the maintenance support capability of the storage and transportation system according to and , so as to evaluate the equipment maintenance support capability of the evaluation object;

[0475] The method for calculating the initial evaluation value of each last level index of the evaluation object comprises:

[0476] when the last level index is a quantitative index, taking the calculated value of the quantitative index as the initial evaluation value of the last level index;

[0477] when the last level index is a qualitative index, quantifying the evaluation result of the last level index by a membership function to obtain a qualitative quantified value, and taking the qualitative quantified value as the initial evaluation value of the last level index, wherein the value range of the qualitative quantified value is [0, 1];

[0478] the evaluation result of the last level index comprises excellent, good, medium, poor and extremely poor;

[0479] quantifying the evaluation result of the last level index by the membership function comprises: mapping the evaluation result of the last level index into a numerical value, wherein excellent corresponds to (0.9, 1.0], good corresponds to (0.8, 0.9], medium corresponds to (0.6, 0.8], poor corresponds to (0.4, 0.6], and extremely poor corresponds to (0, 0.4];

[0480] The step for calculating the comprehensive evaluation value of the maintenance support capability of the storage and transportation system according to the initial evaluation value and the last level index scenario weight matrix comprises:

[0481] constructing the initial evaluation value into an evaluation matrix ;

[0482] calculating the comprehensive evaluation value of the maintenance support capability of the storage and transportation system :

[0483]

[0484] ​The value range of the initial evaluation value is [0, 1], and the steps for calculating the comprehensive evaluation value of the storage and transportation system maintenance support capability according to the initial evaluation value and the final index scene weighting matrix include:

[0485] The initial evaluation value is constructed as an evaluation matrix ;

[0486] The comprehensive evaluation value of the storage and transportation system maintenance support capability is calculated :

[0487]

[0488] The value range of the initial evaluation value is [0, 1];

[0489] The equipment maintenance support capability of the evaluation object is evaluated by using one or more of the following methods:

[0490] The qualified threshold of the comprehensive evaluation value of the storage and transportation system maintenance support capability is set, and when the comprehensive evaluation value of the storage and transportation system maintenance support capability of the evaluation object is greater than or equal to the qualified threshold, it is determined that the maintenance support capability of the evaluation object is qualified, otherwise it is unqualified;

[0491] The comprehensive evaluation values of the storage and transportation system maintenance support capabilities of a plurality of evaluation objects are calculated and sorted, and the evaluation object with a higher comprehensive evaluation value of the storage and transportation system maintenance support capability has a stronger maintenance support capability.

[0492] The following is an embodiment of the storage and transportation system equipment maintenance support capability evaluation system provided by the embodiment, which belongs to the same inventive concept as the storage and transportation system equipment maintenance support capability evaluation method of each embodiment described above. Details not described in detail in the embodiment of the storage and transportation system equipment maintenance support capability evaluation system can be referred to the embodiment of the storage and transportation system equipment maintenance support capability evaluation method described above.

[0493] As shown in Figure 2 , the storage and transportation system equipment maintenance support capability evaluation system includes:

[0494] An evaluation index system construction module is configured to construct an evaluation index system of the storage and transportation system equipment maintenance support capability.

[0495] A comparison matrix construction module is configured to define a set of indexes with the same direct superior index in the evaluation index system as a homologous index group, and construct a pairwise comparison matrix for each homologous index group.

[0496] The scene adaptation judgment matrix construction and weight calculation module is configured to construct a judgment influence factor matrix for each pairwise comparison matrix according to the storage and transportation scene of the evaluation object, then perform Hadamard product operation to obtain a corresponding scene adaptation judgment matrix, and then perform analytic hierarchy process weight calculation to obtain a scene-weighted matrix of the final index.

[0497] The evaluation value calculation and capability evaluation module is configured to calculate an initial evaluation value of each final index of the evaluation object, then calculate a comprehensive evaluation value of the storage and transportation system maintenance support capability, and further evaluate the equipment maintenance support capability of the evaluation object.

[0498] The storage and transportation system equipment maintenance support capability evaluation system of the embodiment is configured to implement the storage and transportation system equipment maintenance support capability evaluation method.

[0499] The application further provides an electronic device for implementing the various embodiments of the application, Figure 3 A hardware structure schematic diagram of an electronic device for implementing the various embodiments of the application is shown in FIG. 1. Figure 3 As shown in FIG. 1, the electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0500] Those skilled in the art can understand that the electronic device structure involved in the embodiments of the application does not constitute a limitation on the electronic device, and the electronic device can include more or fewer components than the diagram, or combine certain components, or different component arrangements.

[0501] In the embodiments of the application, the electronic device includes but is not limited to a laptop computer, a desktop computer, a workstation, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the application described and / or claimed herein.

[0502] In the embodiments of the present application, the processor can be implemented by using at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a processor, a controller, a microcontroller, a microprocessor, an electronic unit designed to perform the functions described herein, in some cases, such an implementation can be implemented in a controller. For software implementation, the implementation of such as processes or functions can be implemented with separate software modules allowing at least one function or operation to be performed, the software code can be implemented by a software application (or program) written in any appropriate programming language, the software code can be stored in a memory and executed by a controller.

[0503] In addition, the electronic device includes some function modules not shown here, which will not be described here.

[0504] Those skilled in the art can understand that various aspects of the electronic device provided by the present application can be implemented as a system, a method or a program product. Therefore, various aspects of the present application can be embodied as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combined with hardware and software aspects, which can be collectively referred to as "circuitry", "module" or "system" here.

[0505] The present application also provides a storage medium in which a program product capable of realizing the storage and transportation system equipment maintenance support capability evaluation method is stored. In some possible embodiments, various aspects of the present application can also be implemented in the form of a program product, which includes program code for causing the terminal device to perform the steps described in the "example method" part of the present specification according to various example embodiments of the present application when the program product is run on the terminal device.

[0506] The storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium may, for example, be but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0507] The foregoing description of the disclosed embodiments enables a person skilled in the art to make or use the application. Modifications of these embodiments will occur to persons of skill in the art, and, while certain embodiments according to the principles set forth herein have been shown and described, various modifications and substitutions can be made by those skilled in the art without departing from the spirit and scope of the application as set forth in the following claims. Therefore, the application is not intended to be limited to the embodiments disclosed herein, but rather is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the maintenance support capability of a storage and transport system equipment, characterized in that, Comprise: S1. Construct an evaluation index system of the maintenance support capability of the storage and transportation system equipment, the evaluation index system comprising a set of indexes with hierarchical relationships; In the evaluation index system, the last-level indexes are the bottommost indexes that cannot be further divided, and all the last-level indexes have the same level; The hierarchy of the evaluation index system of the maintenance support capability of the storage and transportation system equipment comprises: 1 primary index: maintenance support capability index; The maintenance support capability index comprises the following 4 secondary indexes: human resource support capability index U1, material resource support capability index U2, technical resource support capability index U3, and maintenance management support capability index U4; Each secondary index is provided with at least one tertiary index, and each tertiary index is provided with at least one fourth index as a last-level index; S2. Define the index set with the same direct superior index in the evaluation index system as the homologous index group, and construct a pairwise comparison matrix for each homologous index group ; pairwise comparison matrix is a square matrix, n where n is the number of indices included in the corresponding homogenous index group; each element in the matrix represents an index relative to the importance scale value of the index , and are reciprocals of each other, ; S3. For each pair-wise comparison matrix, construct a judgment influence factor matrix S4. For each pair-wise comparison matrix, construct a judgment influence factor matrix , The order of the judgment influence factor matrix is the same as the corresponding . judgment influence factor matrix each element of the judgment influence factor matrix is an index relative to the index a non-negative real number, the larger the value, the more significant the influence, and reciprocals of each other, ; For each With the corresponding Performing Hadamard product operation, obtaining the corresponding scene adaptation judgment matrix ; For all The analytic hierarchy process weight calculation is performed to obtain a final index scene weight matrix ; The last-level indexes are quantitative indexes or qualitative indexes, and the quantitative indexes have a value range of [0, 1]; S4. Calculate the initial evaluation value of each final index of the evaluation object , according to and , calculate the comprehensive evaluation value of the maintenance support capability of the storage and transportation system, and further evaluate the equipment maintenance support capability of the evaluation object.

2. The method of claim 1, wherein: In step S3, the judgment matrix is adapted to all scenarios The analytic hierarchy process weight calculation includes: S301. The method of S300 further comprising: normalizing by column to obtain a column normalized matrix ; S302. Add the matrix Add by row to get a one-dimensional matrix S303. Obtain a one-dimensional matrix S304. Normalize the one-dimensional matrix to obtain a partition weight matrix ; S304. Calculate wherein, is the scenario weight for the nth last index; is the scenario weight for the nth last index; The last stage is the index of the series; the value of the first-level index to which the first last index belongs in the corresponding partition weight matrix ​​ S305. Summing up all to the final indicator scenario weighting matrix , is the total number of final indicators.

3. The method of claim 1, wherein: In step S4, the method for calculating the initial evaluation value of each last-level index of the evaluation object comprises: When the last-level index is a quantitative index, the calculated value of the quantitative index is taken as the initial evaluation value of the last-level index; When the last-level index is a qualitative index, the evaluation result of the last-level index is quantified by a membership function to obtain a qualitative quantified value, and the qualitative quantified value is taken as the initial evaluation value of the last-level index, and the value range of the qualitative quantified value is [0, 1].

4. The method of claim 1, wherein: In step S4, the step for calculating the comprehensive evaluation value of the maintenance support capability of the storage and transportation system according to the initial evaluation value and the scenario-based weighting matrix of the last-level index comprises: constructing the initial evaluation value as an evaluation matrix ; Computing a comprehensive evaluation value of maintenance support capability of a storage and transportation system : the value range of [0, 1].

5. The method of claim 1, wherein: In step S4, the equipment maintenance support capability of the evaluation object is evaluated by using one or more of the following methods: A qualified threshold value of the comprehensive evaluation value of the maintenance support capability of the storage and transportation system is set, and when the comprehensive evaluation value of the maintenance support capability of the storage and transportation system of the evaluation object is greater than or equal to the qualified threshold value, it is determined that the maintenance support capability of the evaluation object is qualified, otherwise it is unqualified; The comprehensive evaluation values of the maintenance support capability of the storage and transportation system of a plurality of evaluation objects are calculated and sorted, and the evaluation object with a higher comprehensive evaluation value of the maintenance support capability of the storage and transportation system has a stronger maintenance support capability.

6. A system for evaluating the sustainment capability of a storage and movement system equipment, characterized by For implementing the method for evaluating the maintenance support capability of the storage and transportation system equipment according to any one of claims 1-5, comprising: An evaluation index system construction module for constructing an evaluation index system of the maintenance support capability of the storage and transportation system equipment; A comparison matrix construction module for defining a set of indexes with the same direct superior index in the evaluation index system as a homologous index group, and constructing a pairwise comparison matrix for each homologous index group; A scenario adaptation judgment matrix construction and weight calculation module for constructing a judgment influence factor matrix for each pairwise comparison matrix according to the storage scenario of the evaluation object, then performing Hadamard product operation to obtain the corresponding scenario adaptation judgment matrix, and then performing analytic hierarchy process weight calculation to obtain the scenario-based weighting matrix of the last-level index; An evaluation value calculation and capability evaluation module for calculating the initial evaluation value of each last-level index of the evaluation object, then calculating the comprehensive evaluation value of the maintenance support capability of the storage and transportation system, and further evaluating the equipment maintenance support capability of the evaluation object.

7. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor being configured to implement the steps of the method for evaluating the maintenance support capability of the logistic system equipment according to any one of claims 1 to 5 when executing the computer program.

8. A storage medium having stored thereon a computer program, the computer program being executable by a processor to implement the steps of the method for evaluating the maintenance support capability of the logistic system equipment according to any one of claims 1 to 5.

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