Research on Maintenance Strategy Evaluation Method for Power Equipment through Experimental Verification

The data of engine failures about automobile operating in field conditions was collected by running engine failure tracking tests. An evaluative model was established using the theory of Fuzzy Neural Network (FNN) for the automobile “using reliability, based on the data of failures about automobiles, finally, the evaluative result for the automobile” using reliability was obtained by evaluative model of reliability. The result of research can be used as references for the improvement of reliability and maintainability of automobile engines, and for the establishment of maintenance strategy, and it also laid a theoretical foundation for studying the improvement of evaluation method for the automobiles' reliability as well.

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An optimization method of maintenance strategy for power equipment

2016 International Conference on Condition Monitoring and Diagnosis (CMD) ◽

10.1109/cmd.2016.7757979 ◽

2016 ◽

Cited By ~ 1

Author(s):

Hang Liu ◽

Youyuan Wang ◽

Liwei Zhou ◽

Yufeng Chen ◽

Xiuming Du

Keyword(s):

Optimization Method ◽

Power Equipment ◽

Maintenance Strategy

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Maintenance Strategy Evaluation Using ANP and Goal Programming

Management Theories and Strategic Practices for Decision Making ◽

10.4018/978-1-4666-2473-3.ch007 ◽

2012 ◽

pp. 117-138

Author(s):

Sarojini Jajimoggala ◽

V. V. S. Kesava Rao ◽

Beela Satyanarayana

Keyword(s):

Goal Programming ◽

Multiple Criteria Decision Making ◽

Cost Savings ◽

Integrated Approach ◽

Analytic Network Process ◽

Maintenance Strategy ◽

Maintenance Policy ◽

Strategy Evaluation ◽

Network Process ◽

Criteria Weights

An optimal maintenance strategy mix is necessary for increasing availability and reliability levels of production facilities without significantly increasing operational costs. The selection of maintenance strategies is a typical Multiple Criteria Decision-Making (MCDM) problem with conflicting goals. Consideration of interdependence among the criteria and alternative policies for maintenance strategy provides valuable cost savings and greater benefits for any hybrid flow systems. For any decision maker, it is convenient to prioritize the criteria of MCDM problems and goals of goal programming problems in fuzzy terms. This paper presents an integrated approach for maintenance policy selection, using fuzzy Analytic Network Process (ANP) within a Goal Programming, based on fuzzy preemptive priority where goal hierarchies are specified in different levels of fuzzy importance. To overcome the criticism of inconsistency, unbalanced scale of judgments and uncertainty in the pair-wise comparison process, criteria weights are determined using modified fuzzy LLSM method.

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Research on the Application of Fuzzy Neural Network in the Tobacco Heights Department of Tractor Reliability

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.152-154.1899 ◽

2012 ◽

Vol 152-154 ◽

pp. 1899-1903

Author(s):

Yan Zhong Men ◽

De Tang Zou

Keyword(s):

Neural Network ◽

Fuzzy Neural Network ◽

Evaluation Method ◽

Theoretical Foundation ◽

Field Conditions ◽

Maintenance Strategy ◽

Fuzzy Neural ◽

Engine Failure

The data of engine failures about tobacco Heights Department of tractor operating in field conditions was collected by running engine failure tracking tests. An evaluative model was established using the theory of Fuzzy Neural Network(FNN) for the tractor ' using reliability, based on the data of failures about tractors, the observed values of the reliability standards were made out and the degree of subordination was figured out, finally, the evaluative result for the tractors ' using reliability was obtained by evaluative model of reliability. The result of research can be used as references for the improvement of reliability and maintainability of tractor engines, and for the establishment of maintenance strategy, and it also lay a theoretical foundation for studying the improvement of evaluation method for the tobacco Heights Department of tractor ' reliability as well.

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