Aircraft production and operation unit performance evaluation method and system

Abstract

The present invention discloses a method and system for evaluating the effectiveness of aircraft production and operation units. The method comprises the following steps: S1, constructing an evaluation index system and historical sample evaluation data, and performing data normalization processing on the historical sample evaluation data; S2, constructing an indicator weight assignment model, inputting the normalized historical sample evaluation data into the historical sample evaluation data, and the indicator weight assignment model includes four calculation modules to respectively obtain indicator weights A1 to A4; S3, constructing a combination evaluation model based on maximizing deviation to calculate the corresponding combination evaluation weights of the indicators; S4, constructing a topological network using the indicators as network nodes, and correcting the indicator weights through the topological network; S4, obtaining evaluation data for each indicator based on the evaluation index system, and calculating the effectiveness evaluation results. The present invention realizes effective evaluation of the incident investigation effectiveness of aircraft production and operation units, facilitates understanding of effectiveness, and is conducive to improving core investigation capabilities and safety management effectiveness.

Description

Technical Field

[0001] The present invention relates to the field of event investigation effectiveness evaluation, and in particular to an aircraft production and operation unit effectiveness evaluation method and system. Background Art

[0002] Safety is the lifeline and eternal theme of civil aviation. Aircraft manufacturers and operators are key entities involved in civil aircraft incident investigations and a crucial component of civil aviation safety management. To strengthen the development of incident investigation systems within aircraft manufacturers and operators, the Civil Aviation Administration of China (CAAC) issued and implemented the "Guidelines for the Development of Aircraft Incident Investigation Systems for Civil Aviation Manufacturers and Operators" (Civil Aviation General Safety Administration

[2020] No. 5) in 2020. Aircraft manufacturers and operators have attached great importance to this initiative, taking immediate action to actively promote the development of incident investigation systems, continuing to conduct in-depth investigations, further improving the capabilities of investigators, and demonstrating the effectiveness of investigations.

[0003] Conducting aircraft incident investigations is an important task for aircraft production and operation units. It is a complex and systematic work involving multiple departments and multiple personnel. Aircraft production and operation units need to evaluate the construction and effectiveness of the incident investigation system internally, and civil aviation management units also need to effectively evaluate the system effectiveness of different aircraft production and operation units. However, since the incident investigation system involves many sections and projects, generally including investigation organizations or institutions, emergency response investigation work manuals, investigator teams, investigation equipment or equipment, engineering test analysis, safety recommendation management, etc., these sections and projects each include subordinate specific projects. The incident investigation system is constructed in sequence according to the subordinate hierarchy. How to conduct system effectiveness evaluation is a major problem for management departments to perform management and supervision. Conducting effectiveness evaluation can effectively identify weak links, make up for shortcomings and weaknesses, continuously consolidate and deepen incident investigation work, improve system maturity, and strive to build a more scientific, reasonable, and safety-oriented investigation system to better play the actual role of investigation in promoting safety. Therefore, the effectiveness evaluation of the incident investigation system of aircraft production and operation units is a current difficulty and key task. It is also an important measure to promote aircraft production and operation units to conduct safety investigations, safe production, and safe research and development at the source. It plays a positive role in promoting safety and urgently needs to carry out evaluation research. Summary of the Invention

[0004] The purpose of the present invention is to solve the technical problems pointed out by the background technology, and to provide a method and system for evaluating the performance of aircraft production and operation units. The method adopts an indicator weight assignment model, a combined evaluation model, and a topological network to process historical sample evaluation data in sequence, so as to obtain the weight of each indicator in the evaluation indicator system, and then multiply the evaluation data of the indicator by the corresponding weight to obtain the indicator evaluation result corresponding to the indicator item, and then add up all the indicator evaluation results to obtain the final performance evaluation result.

[0005] The purpose of the present invention is achieved through the following technical solutions:

[0006] A method for evaluating the effectiveness of an aircraft production and operation unit, comprising:

[0007] S1. Construct an evaluation index system including an index item library, which includes several upper and lower level indicators and corresponding evaluation criteria; construct historical sample evaluation data, which is obtained by sequentially evaluating the indicators based on the evaluation index system, and perform data normalization on the historical sample evaluation data;

[0008] S2. Construct an indicator weight assignment model and input the normalized historical sample evaluation data into the indicator weight assignment model. The indicator weight assignment model includes four calculation modules. The first calculation module in the indicator weight assignment model uses the hierarchical analysis method to compare the indicators as factors to obtain the judgment matrix. And find its maximum eigenvalue and normalized eigenvectors, and the weight A1 corresponding to each indicator is obtained through consistency test; the second calculation module in the indicator weight assignment model uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the indicator importance ratio as the weight A2; the third calculation module in the indicator weight assignment model uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator; the fourth calculation module in the indicator weight assignment model uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator;

[0009] S3. Construct a combined evaluation model based on maximum deviation, taking the indicator as the evaluation object and obtaining the indicator according to the following formula Corresponding combination evaluation weight : ,in Indicates the indicator in the indicator weight assignment model The evaluation value corresponding to the p-th calculation module, It represents the evaluation value corresponding to the p-th calculation module of indicator t in the indicator weight assignment model, and n represents the total number of indicators;

[0010] S4. Use indicators as network nodes to build a topological network. The topological potential of network nodes The expression is: ,in Indicator 、 The difference in combined evaluation weights between Indicator The node attribute value of the node is an indicator The combined evaluation weight of Represents the control coefficient; the index is obtained according to the following formula Weights after topological network correction : ;

[0011] S5, based on the evaluation index system, obtain the evaluation data of each indicator, normalize the evaluation data of each indicator and add them to the weight obtained in step S4. The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0012] In order to better implement the aircraft production and operation unit performance evaluation method of the present invention, in step S5, the evaluation data of each indicator also includes the following data updating processing method before normalization processing: calculating the mission completion ratio of the indicator ,in represents the actual evaluation data of the indicator, Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to , otherwise no processing is done.

[0013] Preferably, in step S2, the judgment matrix The expression is as follows: ,in Indicator Corresponding elements and indicators Corresponding elements The impact ratio.

[0014] Preferably, in step S2, the importance matrix expression is as follows: ,in Indicator and indicators The relative importance value between Add up to get the total value : ;

[0015] The weight A2 formula of a certain indicator is as follows: , Represents the indicators in the importance matrix The total sum of the data in the row.

[0016] Preferably, in step S2, the third calculation module uses the entropy weight method to obtain the discriminant matrix : ,in Indicator Data after dimensionless processing; indicators Contribution The expression is as follows: , ;

[0017] index The weight A3 is expressed as follows: ,in .

[0018] Preferably, in step S2, the fourth calculation module uses the coefficient of variation method to obtain the index The coefficient of variation expression is as follows: ,in Indicator The mean after normalization, Indicator The standard deviation after normalization;

[0019] Normalize the coefficient of variation of all indicators to obtain the indicator The corresponding weight A4 expression is as follows:

[0020] .

[0021] Preferably, in step S4, the weight matrix expression of the network nodes in the topological network is as follows:

[0022] .

[0023] Preferably, in step S1, the data normalization processing formula of the historical sample evaluation data is as follows:

[0024] , Indicates that the indicator corresponds to the standardized data, Indicates the minimum data in the corresponding data of the indicator. Indicates the maximum data among the corresponding data of the indicator. Indicates the data corresponding to the indicator.

[0025] An aircraft production and operation unit performance evaluation system includes an indicator weight assignment model, a combination evaluation model, an evaluation indicator system, historical sample evaluation data, a topological network and an efficiency evaluation module. The evaluation indicator system is constructed according to an indicator item library, and the indicator item library includes a number of upper and lower level indicators and corresponding evaluation standards; the historical sample evaluation data is obtained by sequential evaluation according to the indicators based on the evaluation indicator system, and the historical sample evaluation data is normalized; the indicator weight assignment model is used to receive the input normalized historical sample evaluation data and perform the following processing: the weighting model includes a hierarchical analysis calculation module, a priority diagram calculation module, an entropy weight calculation module, and a variation coefficient calculation module. The hierarchical analysis calculation module adopts a hierarchical analysis method to perform pairwise comparisons with indicators as factors to obtain a judgment matrix And find its maximum eigenvalue and normalized eigenvectors, and obtain the weight A1 corresponding to each indicator through consistency test; the priority diagram calculation module uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the indicator importance ratio as the weight A2; the entropy weight calculation module uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator; the coefficient of variation calculation module uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator;

[0026] The combined evaluation model is constructed based on the maximum deviation. The combined evaluation model uses the index as the evaluation object and obtains the index according to the following formula Corresponding combination evaluation weight :

[0027] ,in Indicates the indicator in the indicator weight assignment model The evaluation value corresponding to the p-th calculation module, P represents the total number of calculation modules in the indicator weight assignment model, and n represents the total number of indicators;

[0028] The topological network is constructed with indicators as network nodes, and the topological potential of network nodes The expression is: ,in Indicator 、 The difference in combined evaluation weights between Indicator The node attribute value of the node is an indicator The combined evaluation weight of Represents the control coefficient; the index is obtained according to the following formula Weights after topological network correction : ;

[0029] The performance evaluation module obtains the evaluation data of each indicator based on the evaluation index system, normalizes the evaluation data of each indicator and adds them to the weight The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0030] In order to better realize the aircraft production and operation unit performance evaluation system of the present invention, the performance evaluation module calculates the mission completion ratio of the index ,in represents the actual evaluation data of the indicator, Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to , otherwise no processing is done; the evaluation data of each indicator after update is normalized and combined with the weight The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

[0031] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0032] (1) The present invention uses an indicator weight assignment model, a combined evaluation model, and a topological network to process the historical sample evaluation data in sequence, and can obtain the weight of each indicator in the evaluation indicator system. Then, the evaluation data of the indicator is multiplied by the corresponding weight to obtain the indicator evaluation result corresponding to the indicator item, and all the indicator evaluation results are added together to obtain the final performance evaluation result.

[0033] (2) The present invention constructs an evaluation index system that can scientifically evaluate the effectiveness of the complex incident investigation system, realize the effective evaluation of the incident investigation effectiveness of aircraft production and operation units, and obtain quantitative single indicator evaluation results and overall effectiveness evaluation results, which makes it easier to understand the effectiveness and is conducive to improving core investigation capabilities and safety management effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention is a flowchart of the method for evaluating the effectiveness of aircraft production and operation units. DETAILED DESCRIPTION

[0035] Below in conjunction with embodiment, the present invention is described in further detail:

[0036] Example

[0037] like Figure 1 As shown, a method for evaluating the effectiveness of an aircraft production and operation unit includes:

[0038] S1. Construct an evaluation index system comprising an index library containing several hierarchical indicators and corresponding evaluation criteria. In this embodiment, aircraft production and operation units must assess six primary items: investigation organization or institution, emergency response investigation work manual, investigator team, investigation equipment or facilities, engineering test analysis, and safety recommendation management. Each primary item includes several secondary items. For example, the primary items for the investigation organization or institution include four secondary items: document manual, organizational structure, departmental responsibilities, and investigation mechanism. For example, the primary items for the investigator team include five secondary items: investigator training, selection and appointment, responsibilities and authority, investigator file and certificate management, and occupational health protection. Each secondary item includes several tertiary items. For example, the secondary items for the document manual include clarifying the responsibilities of each investigation department and the qualifications of relevant investigation personnel. For example, the secondary items for selection and appointment include accreditation of qualified investigators, the required number of qualified investigators, and ensuring that the professional coverage of selected investigators meets the required scope. Therefore, the indicators in the indicator library of the evaluation index system of the present invention are extracted according to the content that needs to be evaluated by aircraft production and operation units and constructed according to the corresponding hierarchy, and corresponding evaluation standards are also constructed according to the hierarchy. The evaluation index system constructed in this embodiment has 6 first-level indicators and 28 second-level indicators respectively, and a number of third-level indicators.

[0039] Construct historical sample evaluation data. The historical sample evaluation data is obtained by evaluating in sequence according to the indicators based on the evaluation index system (the historical sample evaluation data is evaluated according to the evaluation index system to obtain its corresponding evaluation value. The evaluation value is generally a score, also known as the data obtained by the evaluation corresponding to the indicator. The evaluation value of a certain indicator corresponds to the content of the corresponding level that the aircraft production and operation unit needs to evaluate). Perform data normalization on the historical sample evaluation data.

[0040] In some embodiments, the data normalization processing formula for historical sample evaluation data is as follows:

[0041] , Indicates that the indicator corresponds to the standardized data, Indicates the minimum data in the corresponding data of the indicator. Indicates the maximum data among the corresponding data of the indicator. Indicates the data corresponding to the indicator.

[0042] S2. Construct an indicator weight assignment model and input the normalized historical sample evaluation data into the indicator weight assignment model. The indicator weight assignment model includes four calculation modules. The first calculation module in the indicator weight assignment model uses the hierarchical analysis method to compare the indicators as factors to obtain the judgment matrix. And find its maximum eigenvalue And the normalized eigenvector, the weight A1 corresponding to each indicator is obtained through consistency test; the judgment matrix of the first calculation module in the indicator weight assignment model The expression is as follows:

[0043] ,in Indicator Corresponding elements and indicators Corresponding elements Then find its maximum eigenvalue and eigenvectors , based on the maximum eigenvalue Conduct consistency indicators , consistency ratio Double test, after the test passes, the eigenvector Normalization is performed to obtain the normalized feature vectors corresponding to each indicator and use them as weights A1 in turn.

[0044] In some embodiments, the judgment matrix is calculated The maximum eigenvalue of

[0045] Calculating consistency index (Consistency Index)

[0046] ;

[0047] Check the following table to obtain the corresponding average random consistency index (Random Index), as shown in the following table:

[0048] Table 3 Average random consistency index values

[0049]

[0050] Calculating the consistency ratio (Consistency Ratio)

[0051] ;

[0052] Make consistency judgment: When When If there is satisfactory consistency, the analysis result is accepted; otherwise, When , the judgment matrix There is no satisfactory consistency and modification is required.

[0053] The above steps yield a single-level ranking, a weight vector representing the weight of a group of elements relative to an element in the previous level. A hierarchical total ranking calculates the relative importance of the lowest-level factors relative to the highest-level factors, layer by layer, along the recursive hierarchy. This means the relative importance of all factors at a given level relative to the highest level. The total ranking weight is a top-down synthesis of the weights of the individual criteria.

[0054] Set up one level Include common factors, and their hierarchical weights are , the next layer Include factors ,about The hierarchical single ranking weights are . Using the weighted synthesis method to find The total hierarchical ranking weight of each factor in the layer ,Right now The calculation method is as follows:

[0055] Table 4. Hierarchical total ranking weight synthesis method

[0056]

[0057] The weight vector obtained by the total hierarchical sorting still needs to be checked for consistency to verify whether the result is satisfactory. Layer The consistency index of the factor is , the average random consistency index is , then The comprehensive indicators of the layers are:

[0058] ;

[0059] ;

[0060] ;

[0061] like , then the hierarchy is considered to be in the If the judgments above the level have overall satisfactory consistency, the analysis results are accepted; on the contrary, if When the hierarchy is considered to be The judgments above the level do not have satisfactory consistency as a whole, and the judgment matrix needs to be modified. In practical applications, if the single-level sorting has been tested to have satisfactory consistency, there is no need to perform a satisfactory consistency test on the whole, because it is not only very difficult to consider the whole, but also very difficult to adjust the judgment matrix of the whole.

[0062] The second calculation module in the indicator weight assignment model uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the indicator importance ratio as the weight A2. The importance matrix expression of the second calculation module in the indicator weight assignment model is as follows: ,in Indicator and indicators The relative importance value between Add up to get the total value : ; A certain indicator (a certain indicator calculated by the second calculation module, such as indicator ) weight A2 formula is as follows: , Represents the indicators in the importance matrix The total sum of the data in the row.

[0063] The third calculation module in the indicator weight assignment model uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator. The third calculation module uses the entropy weight method to obtain the discriminant matrix : ,in Indicator Data after dimensionless processing; indicators Contribution The expression is as follows: , ;

[0064] index The weight A3 is expressed as follows: ,in ,, ,and .

[0065] The fourth calculation module in the indicator weight assignment model uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator. The coefficient of variation expression is as follows: ,in Indicator The mean after normalization, Indicator The standard deviation after normalization;

[0066] Normalize the coefficient of variation of all indicators to obtain the indicator The corresponding weight A4 expression is as follows:

[0067] .

[0068] S3. Construct a combined evaluation model based on maximum deviation, taking the indicator as the evaluation object and obtaining the indicator according to the following formula Corresponding combination evaluation weight : ,in Indicates the indicator in the indicator weight assignment model The evaluation value corresponding to the p-th calculation module, It represents the evaluation value corresponding to the p-th calculation module of indicator t in the indicator weight assignment model, and n represents the total number of indicators.

[0069] S4. Use indicators as network nodes to build a topological network. The topological potential of network nodes The expression is: ,in Indicator 、 The difference in combined evaluation weights between Indicator The node attribute value of the node is an indicator The combined evaluation weight of The combined evaluation weight is used as an indicator The node attribute value of the topological network is the indicator as the network node, and the node attribute value of the network node directly adopts the combined evaluation weight corresponding to the indicator). represents the control coefficient (in this embodiment, the value is 1); the index is obtained according to the following formula Weights after topological network correction : The weight matrix expression of network nodes in the topological network is as follows:

[0070] .

[0071] This example takes the effectiveness evaluation of the incident investigation system of COMAC aircraft production and operation units as an example, and lists the weights of some indicators as follows:

[0072] ;

[0073] S5, based on the evaluation index system, obtain the evaluation data of each indicator, normalize the evaluation data of each indicator and add them to the weight obtained in step S4. Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation results. First, the evaluation data after normalization of indicator j and the weight of indicator j are added. The result j is obtained by multiplying them together (the multiplication of the indicator of the present invention and the corresponding weight of the indicator constitutes the indicator evaluation result corresponding to the indicator), and the results j of all indicators are added together to obtain the performance evaluation result.

[0074] In some embodiments, step S5 can be replaced by: obtaining evaluation data of each indicator based on the evaluation indicator system, and calculating the mission completion ratio of the indicator. ,in represents the actual evaluation data of the indicator, Indicates the expected evaluation data set by the indicator (that is, the expected target data set by the indicator, that is, the expected target achieved by the indicator); if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to , otherwise no processing is done. The evaluation data of each indicator after update is normalized and combined with the weight obtained in step S4 Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation results. First, update the evaluation data after normalization of indicator j and the weight of indicator j Multiplying the results yields result j (the product of the present invention's indicators and their corresponding weights constitutes the indicator evaluation result corresponding to that indicator). Summing the results j for all indicators yields the performance evaluation result. This embodiment uses the performance evaluation of the incident investigation system of COMAC's aircraft production and operation units as an example, ultimately yielding a performance evaluation result of 95.5344. The inventive method was used to evaluate COMAC's incident investigation system, and the performance evaluation method has been fully validated and tested. By establishing a performance evaluation method for the aircraft production and operation unit incident investigation system, the evaluation calculation results can scientifically reflect the maturity of system construction and its actual performance, providing a basis for evaluating system construction and a reference for clarifying the direction of system improvement.

[0075] An aircraft production and operation unit performance evaluation system includes an indicator weight assignment model, a combination evaluation model, an evaluation indicator system, historical sample evaluation data, a topological network and an efficiency evaluation module. The evaluation indicator system is constructed according to an indicator item library, and the indicator item library includes a number of upper and lower level indicators and corresponding evaluation standards; the historical sample evaluation data is obtained by sequential evaluation according to the indicators based on the evaluation indicator system, and the historical sample evaluation data is normalized; the indicator weight assignment model is used to receive the input normalized historical sample evaluation data and perform the following processing: the weighting model includes a hierarchical analysis calculation module, a priority diagram calculation module, an entropy weight calculation module, and a variation coefficient calculation module. The hierarchical analysis calculation module adopts the hierarchical analysis method to perform pairwise comparison with indicators as factors to obtain a judgment matrix And find its maximum eigenvalue and normalized eigenvectors, and obtain the weight A1 corresponding to each indicator after consistency test; the priority diagram calculation module uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the indicator importance ratio as the weight A2; the entropy weight calculation module uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator; the coefficient of variation calculation module uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator;

[0076] The combined evaluation model is constructed based on the maximum deviation. The combined evaluation model takes the indicator as the evaluation object and obtains the indicator according to the following formula: Corresponding combination evaluation weight :

[0077] ,in Indicates the indicator in the indicator weight assignment model The evaluation value corresponding to the p-th calculation module, P represents the total number of calculation modules in the indicator weight assignment model, and n represents the total number of indicators.

[0078] The topological network is constructed with indicators as network nodes. The expression is: ,in Indicator 、 The difference in combined evaluation weights between Indicator The node attribute value of the node is an indicator The combined evaluation weight of The combined evaluation weight As an indicator ), represents the control coefficient (in this embodiment, the value is 1); the index is obtained according to the following formula Weights after topological network correction : .

[0079] The performance evaluation module obtains the evaluation data of each indicator based on the evaluation index system, normalizes the evaluation data of each indicator and adds them to the weight Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation results (first normalize the evaluation data of indicator j and the weight of indicator j Multiply them to get the result j, and add the results j of all indicators to get the performance evaluation result).

[0080] In some embodiments, the performance evaluation module obtains evaluation data of each indicator based on the evaluation indicator system, and calculates the mission completion ratio of the indicator. ,in represents the actual evaluation data of the indicator, Indicates the expected evaluation data set by the indicator (that is, the expected target data set by the indicator, that is, the expected target achieved by the indicator); if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to Otherwise, no processing is done; the performance evaluation module normalizes the evaluation data of each indicator after updating and adds them to the weights. Multiply the corresponding indicators and add up the multiplication results of all indicators to get the performance evaluation results (first update the indicator j, normalize the evaluation data and the weight of indicator j Multiply them to get the result j, and add the results j of all indicators to get the performance evaluation result).

[0081] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating the effectiveness of an aircraft production and operation unit, characterized by: The methods include: S1. Construct an evaluation index system including an index item library, which includes several upper and lower level indicators and corresponding evaluation criteria; construct historical sample evaluation data, which is obtained by sequentially evaluating the indicators based on the evaluation index system, and perform data normalization on the historical sample evaluation data; S2. Construct an indicator weight assignment model and input the normalized historical sample evaluation data into the indicator weight assignment model. The indicator weight assignment model includes four calculation modules. The first calculation module in the indicator weight assignment model uses the hierarchical analysis method to compare the indicators as factors to obtain the judgment matrix. And find its maximum eigenvalue and normalized eigenvectors, and the weight A1 corresponding to each indicator is obtained through consistency test; the second calculation module in the indicator weight assignment model uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the indicator importance ratio as the weight A2; the third calculation module in the indicator weight assignment model uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator; the fourth calculation module in the indicator weight assignment model uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator; S3. Construct a combined evaluation model based on maximum deviation, taking the indicator as the evaluation object and obtaining the indicator according to the following formula Corresponding combination evaluation weight : ,in Indicates the indicator in the indicator weight assignment model The evaluation value corresponding to the p-th calculation module, It represents the evaluation value corresponding to the p-th calculation module of indicator t in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, and n represents the total number of indicators; S4. Use indicators as network nodes to build a topological network. The topological potential of network nodes The expression is: ,in Indicator 、 The difference in combined evaluation weights between Indicator The node attribute value of the node is an indicator The combined evaluation weight of Represents the control coefficient; the index is obtained according to the following formula Weights after topological network correction : ; S5, based on the evaluation index system, obtain the evaluation data of each indicator, normalize the evaluation data of each indicator and add them to the weight obtained in step S4. The performance evaluation results are obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators; the evaluation data of each indicator also includes the following data update processing method before normalization: Calculate the mission completion ratio of the indicator ,in represents the actual evaluation data of the indicator, Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to , otherwise no processing is done.

2. The aircraft production and operation unit efficiency evaluation method according to claim 1, characterized in that: In step S2, the judgment matrix The expression is as follows: ,in Indicator Corresponding elements and indicators Corresponding elements The impact ratio.

3. The aircraft production and operation unit efficiency evaluation method according to claim 1, characterized in that: In step S2, the importance matrix expression is as follows: ,in Indicator and indicators The relative importance value between Add up to get the total value : ; The weight A2 formula of a certain indicator is as follows: , Represents the indicators in the importance matrix The total sum of the data in the row.

4. The aircraft production and operation unit efficiency evaluation method according to claim 1, characterized in that: The third calculation module uses the entropy weight method to obtain the discriminant matrix : ,in Indicator Data after dimensionless processing; indicators Contribution The expression is as follows: , ; index The weight A3 is expressed as follows: ,in .

5. The aircraft production and operation unit efficiency evaluation method according to claim 1, characterized in that: The fourth calculation module uses the coefficient of variation method to obtain the index The coefficient of variation expression is as follows: ,in Indicator The mean after normalization, Indicator The standard deviation after normalization; Normalize the coefficient of variation of all indicators to obtain the indicator The corresponding weight A4 expression is as follows: 。 6. The aircraft production and operation unit efficiency evaluation method according to claim 1, characterized in that: The weight matrix expression of network nodes in the topological network is as follows: 。 7. The aircraft production and operation unit efficiency evaluation method according to claim 1, characterized in that: In step S1, the data normalization processing formula of the historical sample evaluation data is as follows: , Indicates that the indicator corresponds to the standardized data, Indicates the minimum data in the corresponding data of the indicator. Indicates the maximum data among the corresponding data of the indicator. Indicates the data corresponding to the indicator.

8. An aircraft production and operation unit performance evaluation system, characterized by: It includes an indicator weight assignment model, a combination evaluation model, an evaluation indicator system, historical sample evaluation data, a topological network and an efficiency evaluation module. The evaluation indicator system is constructed according to an indicator item library, which contains several upper and lower level indicators and corresponding evaluation standards. The historical sample evaluation data is obtained by sequential evaluation according to the indicators based on the evaluation indicator system, and the historical sample evaluation data is normalized. The indicator weight assignment model is used to receive the input normalized historical sample evaluation data and perform the following processing: the weighting model includes a hierarchical analysis calculation module, a priority diagram calculation module, an entropy weight calculation module, and a variation coefficient calculation module. The hierarchical analysis calculation module uses the hierarchical analysis method to perform pairwise comparisons with indicators as factors to obtain a judgment matrix. And find its maximum eigenvalue and normalized eigenvectors, and obtain the weight A1 corresponding to each indicator through consistency test; the priority diagram calculation module uses the priority diagram method to calculate the importance of each pair of indicators and obtain the importance matrix, with the indicator importance ratio as the weight A2; the entropy weight calculation module uses the entropy weight method to calculate the contribution and entropy weight of the indicator, and uses the entropy weight as the weight A3 corresponding to the indicator; the coefficient of variation calculation module uses the coefficient of variation method to calculate the mean and standard deviation of the indicator, and then calculates the coefficient of variation of the indicator and normalizes it to obtain the weight A4 corresponding to the indicator; The combined evaluation model is constructed based on the maximum deviation. The combined evaluation model uses the index as the evaluation object and obtains the index according to the following formula Corresponding combination evaluation weight : ,in Indicates the indicator in the indicator weight assignment model The evaluation value corresponding to the p-th calculation module, It represents the evaluation value corresponding to the p-th calculation module of indicator t in the indicator weight assignment model, P represents the total number of calculation modules in the indicator weight assignment model, and n represents the total number of indicators; The topological network is constructed with indicators as network nodes, and the topological potential of network nodes The expression is: ,in Indicator 、 The difference in combined evaluation weights between Indicator The node attribute value of the node is an indicator The combined evaluation weight of Represents the control coefficient; the index is obtained according to the following formula Weights after topological network correction : ; The performance evaluation module obtains the evaluation data of each indicator based on the evaluation index system, normalizes the evaluation data of each indicator and adds them to the weight Multiply the corresponding indicators and add up the multiplication results of all indicators to obtain the performance evaluation result; the performance evaluation module calculates the mission completion ratio of the indicator ,in represents the actual evaluation data of the indicator, Indicates the expected evaluation data set by the indicator; if the mission completion ratio is less than 1, the evaluation data of the corresponding indicator is updated to , otherwise no processing is done; the evaluation data of each indicator after update is normalized and combined with the weight The performance evaluation result is obtained by multiplying the corresponding indicators and adding up the multiplication results of all indicators.

Images