Abstract

Predictive maintenance is a subbranch of Zero Defect Manufacturing concept. The goal is to achieve higher quality at the final product with the most optimum and efficient way. Predictive maintenance may be applied with various alternative ways for achieving the same goal. The current paper investigates and identifies the key control parameters for an effective predictive maintenance, such as prediction horizon. The identified parameters were implemented in a dynamic scheduling tool and simulations were performed for different manufacturing system layouts and the effect of the identified parameters to each layout were identified.

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