Resilient Scheduling Heuristic for Single Machine Systems to Minimize Variance of Job Completion Time

Industry 5.0 emphasizes human–machine collaboration and focuses on resilience, and sustainability, as defined by the European Commission. With recent trends in technology and availability of abundance data has led to digital transformation of manufacturing processes. The manufacturing system may consist of machines in parallel and/or in series. Typically, when we have a bottleneck machine in a manufacturing system, the problem reduces to that of scheduling on a single machine, namely that of scheduling on the bottleneck machine. In this paper, we consider the problem of scheduling on such a single machine manufacturing system which is prone to failure. There are many measures of performance, among them, the minimization of completion time variance of jobs is considered significant in the context of Just-in-Time manufacturing and when there is a need to have sustainable process, to minimize variation and avoid failure to adhere to common delivery performance measures for better customer satisfaction. We develop two lemmas to determine the order of sequencing jobs and thereafter determine the schedule of jobs for processing on the single machine by a heuristic based on these two lemmas. This heuristic is basically a construction heuristic and therefore, computationally very fast. An extensive computational experimentation is carried out to evaluate the performance of the proposed heuristic by considering benchmark problems instances and benchmark heuristics. The result shows that the proposed heuristic is computationally very fast with an accuracy that is extremely close to the optimal solution, unlike the existing heuristic approaches. These aspects make the proposed heuristic quite attractive for solving the large-sized problem instances.