2021•IOP Conference Series Materials Science and EngineeringOpen access

System reliability analysis of forage crushing machine based on fuzzy FMECA

X Y Zhai, Z P Zhai, Yongqing Lan, Y M Wu, Heng-Hsing Cheng, C C Zhang

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Abstract

Abstract This paper aims to address the problems of high failure rate, poor reliability, and incomplete failure data associated with forage crushing machines. First, the failure mode effects and criticality analysis (FMECA) is combined with the fuzzy theory to transform the influencing factors on failure modes into fuzzy variables. Then, the analytic hierarchy process (AHP) is used to determine the weight of each influencing factor, and a comprehensive criticality degree is calculated for each failure mode to determine the key component posing the greatest criticality of disrupting the operation of the equipment. The results of the analysis show that fuzzy FMECA can be used to rank the comprehensive criticality degree of each failure mode. Furthermore, the results are consistent with the criticality ranking of failure modes obtained under actual operating conditions and can therefore be to determine the most critical failure mode and the key component. Fuzzy FMECA also provides valuable reference data for improving the design and system reliability and to effectively reduce the failure rate of forage crushing machines.

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Abstract This paper aims to address the problems of high failure rate, poor reliability, and incomplete failure data associated with forage crushing machines. First, the failure mode effects and criticality analysis (FMECA) is combined with the fuzzy theory to transform the influencing factors on failure modes into fuzzy variables. Then, the analytic hierarchy process (AHP) is used to determine the weight of each influencing factor, and a comprehensive criticality degree is calculated for each failure mode to determine the key component posing the greatest criticality of disrupting the operation of the equipment. The results of the analysis show that fuzzy FMECA can be used to rank the comprehensive criticality degree of each failure mode. Furthermore, the results are consistent with the criticality ranking of failure modes obtained under actual operating conditions and can therefore be to determine the most critical failure mode and the key component. Fuzzy FMECA also provides valuable reference data for improving the design and system reliability and to effectively reduce the failure rate of forage crushing machines.

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Available abstract

Abstract This paper aims to address the problems of high failure rate, poor reliability, and incomplete failure data associated with forage crushing machines. First, the failure mode effects and criticality analysis (FMECA) is combined with the fuzzy theory to transform the influencing factors on failure modes into fuzzy variables. Then, the analytic hierarchy process (AHP) is used to determine the weight of each influencing factor, and a comprehensive criticality degree is calculated for each failure mode to determine the key component posing the greatest criticality of disrupting the operation of the equipment. The results of the analysis show that fuzzy FMECA can be used to rank the comprehensive criticality degree of each failure mode. Furthermore, the results are consistent with the criticality ranking of failure modes obtained under actual operating conditions and can therefore be to determine the most critical failure mode and the key component. Fuzzy FMECA also provides valuable reference data for improving the design and system reliability and to effectively reduce the failure rate of forage crushing machines.

Key concepts: Failure mode, effects, and criticality analysis, Failure mode and effects analysis, Criticality, Reliability engineering, Fuzzy logic, Reliability (semiconductor), Failure rate, Analytic hierarchy process

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