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A novel AMFMEA approach to identify most critical component and decision making approach for combining NDTS for screw compressor

Ashish Khaira ; Department of Mechanical Engineering, SATI, Vidisha, India
Ravi K. Dwivedi ; Department of Mechanical Engineering, MANIT, Bhopal, India

Puni tekst: engleski pdf 1.588 Kb

str. 104-124

preuzimanja: 98



To ensure higher reliability, it is necessary to identify the most prominent cause of failure. It was observed in multiple works that most of the researchers used failure mode and effect analysis (FMEA) and failure mode and effect criticality analysis (FMECA) but these approaches contain lots of hindrances. Alternatively, the MATRIX FMEA approach applied to identify the most prominent cause of failure and critical sub-component prone to that particular failure. The matrix FMEA developed for design engineers so that they can identify the potential cause of failures and design-out them in new product design. The central idea of this research is to apply this approach to maintenance, since the potential failure mode and the affected components were known. In most research, a single component such as a cylinder or turbocharger is used for analysis, but this research targets an entire machine. Multiple researchers also highlighted that the combination of non-destructive testing (NDT) provides better results instead of single NDT. Multiple researchers also highlighted the suitability of the analytical hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) for decision making (DM). Therefore, this work covered firstly, a novel AMFMEA (AHP-Matrix FMEA) to identify the most critical component of particular machinery located in a heavy industrial setup and secondly, DM approach for combining NDTs. It was observed that the incorporation of AHP in Matrix-FMEA improved its analytical ability and reduced overall computation time. This work also provided the guideline with a detailed procedure for combining NDTs.

Ključne riječi

failure analysis; decision making; AHP; PROMETHEE; matrix-FMEA

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