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Manufacturing system comprehensive evaluation method based on improved data envelopment analysis

An envelope analysis and manufacturing system technology, applied in the fields of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of the production system being difficult to meet, the DEA method is no longer applicable, etc.

Inactive Publication Date: 2014-10-29
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

However, for some complex systems whose input / output factors are difficult to describe with precise numbers, the deterministic DEA method is no longer applicable
Aiming at the fuzziness and uncertainty of the manufacturing system, the fuzzy DEA evaluation method is proposed in the prior art, but the method requires the manufacturing system to meet the constraints of constant returns to scale
However, the actual production system is often difficult to meet this constraint

Method used

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  • Manufacturing system comprehensive evaluation method based on improved data envelopment analysis
  • Manufacturing system comprehensive evaluation method based on improved data envelopment analysis
  • Manufacturing system comprehensive evaluation method based on improved data envelopment analysis

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Embodiment

[0069] The existing manufacturing system evaluation of the automobile lamp production industry is used as an example to verify the effectiveness of the method provided by the present invention. The production data of each manufacturing system are shown in Table 1.

[0070] Table 1 Manufacturing system production data

[0071]

[0072] According to the expert scoring method to determine the weight ranges of production cost, floor area and production time input, respectively: ω 1 =[0.3523,0.3835],ω 2 =[0.1318,0.1996] and ω 3 =[0.4547,0.4838], the ranges of the weights of quality, output and profit are: U 1 =[0.6105,0.6895],υ 2 =[0.0855,0.1895] and U 3 =[0.2013,0.2387]. Let α=0.1,0.2,...,1.0, calculate the relative effective of each manufacturing system upper and lower bounds of . Table 2 shows the performance of 8 manufacturing systems under 10 discrete values ​​of α and

[0073] Table 2 Fuzzy effectiveness of eight manufacturing systems based on α-cut sets

[...

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Abstract

The invention discloses a manufacturing system comprehensive evaluation method based on improved data envelopment analysis. On the basis of a traditional data envelopment analysis model, uncertainty and fuzziness of production factors in a complex manufacturing system are taken into account, triangular fuzzy numbers are introduced to represent the production factors, and a fuzzy data envelopment analysis and evaluation model is built. In order to avoid the situation that certain input / output factors are depended on excessively or neglected during the manufacturing system evaluation process, the concept of a guarantee domain is introduced into the model, as a result, it is guaranteed that the weight values of all the production factors are within a reasonable range, and a fuzzy data envelopment analysis / guarantee domain model is built. An alpha cut set is introduced to calculate the upper bound and the lower bound of manufacturing system fuzzy effectiveness, a sorting method is disclosed to sort the upper bound and the lower bound, and it is the most effective manufacturing system that has the highest ordering index. The manufacturing system comprehensive evaluation method based on improved data envelopment analysis breaks the restraint of constant returns to scale in the production process of the manufacturing system, and has practical significance in actual production systems.

Description

technical field [0001] The invention relates to a comprehensive evaluation method of a manufacturing system, in particular to a method and technology for a comprehensive evaluation of a manufacturing system based on improved data envelopment analysis. Background technique [0002] Effective evaluation of the relative effectiveness of input and output of manufacturing systems in the industry has guiding significance for decision-making of manufacturing enterprises. In recent years, the evaluation and decision-making problems of advanced manufacturing systems have received extensive attention, mainly in the methods of multi-objective mathematical programming, intelligent optimization and fuzzy decision-making. The above method needs to establish an accurate mathematical model, so it is not suitable for the evaluation of complex manufacturing systems that are difficult to model. Data Envelopment Analysis (DEA) was proposed by operations research scientists Charnes, Cooper and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 王玉芳王志华宋莹杨丽薛力红
Owner NANJING UNIV OF INFORMATION SCI & TECH
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