Quality control and tool condition monitoring are two most important aspects of machining process. This paper studies the correlation between tool wear and surface roughness to explore the possibility of modelling the interdependencies between these two aspects. An experimental study is presented in this paper to model the relationship between product quality parameter i.e. average surface roughness and tool wear. Current study reveals that there is a strong positive correlation between surface roughness and tool wear. To map this relationship an ensemble (random forest) fault estimation model is developed for identification and estimation of cutting tool health state. The results from fault estimation model are then used to provide guidelines for future process monitoring and developing dynamic quality control policy.
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prognosis, Tool condition monitoring, tool wear, Quality control
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