Single machine scheduling with consideration of preventivemaintenance and machine health

Abstract

Because of Industry 4.0 and Internet of Things, it is easier to collect data from machines through sensors that are embedded inside machines. Once the status change of a machine is detected, production on that machine may need to be adjusted accordingly. In this research, we focus on single machine scheduling with considering the Preventive Maintenance (PM) and machine health index. Machine health index is categorized into three states: good, fair, and breakdown. When the machine moves from one state to another, the processing time of jobs will change as well as the machine failure rate. We develop a model to determine an optimal interval of performing PM and production sequence of jobs. A two-phase heuristic method is proposed to solve a large-size problem. Through different parameter settings, such as the machine failure rate, number of jobs, repair and maintenance cost, we show that the two-phase heuristic can obtain a solution with high quality.