MONITORING MACHINE OPERATIONS USING ONLINE SENSORS

Monitoring machine operations and production process conditions using on-line sensors has drawn increasing attention recently. In this paper , we discuss a situation where an on-line sensor is used to monitor a randomly deteriorating machine operation. The machine condition is des cribed by a finite number of states, and the machine deterioration fol lows a Markov process. It is assumed that the sensor measurement and t he true machine condition have a statistical relation. A decision is t o be made on when a machine setup should be made, based on the observe d sensor measurement. A Markovian model is developed by considering th e cost of operating the machine and the cost of performing preventive maintenance, and a steady state threshold policy is developed by minim izing the total cost. In addition, a heuristic method based on Bayes r ule is proposed. A simulation study is used to study and compare the p roperties of these two policies.