Failure analysis and prediction for metal jobs using fuzzy computation

TLDR: This paper provides the information regarding the metal jobs failure which was detected earlier by using fuzzy logic and these parameters used in labVIEW for designing fuzzy logic inferential system.

Abstract: Metal jobs (connecting rods) are the one of the essential components of engine's design and also used in industry purpose. The Metal jobs must be able to withstand heavy loads and transmit a great deal of power, the failure of metal jobs leads to damaging engine and other equipment's. This paper provides the information regarding the metal jobs failure which was detected earlier by using fuzzy logic. The failure of metal jobs were predicted by applying different amount of tension on metal jobs which are made of different type of metals like aluminium, copper, steel etc. These different types of metal jobs have a different tensile strength and elongation property, if the applied tension is greater than tensile strength of the material then the metal jobs will break's. So here the tensile strength of the metal jobs were predicted earlier and this values were stored in database. Prediction of failure analysis is done with the help of Hall sensor (AH49E TO-92S) which will get the elongation parameter changes and these parameters used in labVIEW for designing fuzzy logic inferential system. This fuzzy logic will helpful for diagnosing and analysis. In this analysis the tension input values are given to labVIEW to know the break point of the metal jobs without testing. It will give the indication when the metal job is abort to break.