Open AccessPattern Recognition on Remanufacturing Automotive Component as Support Decision Making Using Mahalanobis-taguchi System
Author(s) -
Abu Yazid,
J. Khairur Rijal,
Awaluddin Mohamed Shaharoun,
Emelia Sari
Publication year - 2015
Publication title -
procedia cirp
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.683
H-Index - 65
ISSN - 2212-8271
DOI - 10.1016/j.procir.2014.07.025
Subject(s) - remanufacturing , mahalanobis distance , taguchi methods , automotive industry , component (thermodynamics) , manufacturing engineering , pattern recognition (psychology) , computer science , engineering , automotive engineering , artificial intelligence , machine learning , physics , thermodynamics , aerospace engineering
An unsystematic of pattern recognition system based historical data caused the industrial practitioners failed to predict in a short time either the part can be rejected or remanufactured. In a worst case, their justification is really weak without any particular analysis to convince the client because the current situation, they only depend on a traditional inspection to make a decision. Thus, the aim of this work is to provide a systematic pattern recognition using T Method-3 by constructing a scatter diagram which could support decision making of particular industry on 14 main journals of crankshaft belong to 7 engine models with different numbers of samples. Consequently, the outcome of this work is the client will be more convince on the development of remanufacturing process and the human's perspective will be that remanufactured product be thought as second hand, of poor quality and will be improved
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