Digital twin based decision framework for jobshop layout production systems under disruptions

In a hybrid layout production system under uncertainties, making strategic decisions becomes crucial and demanding with increase in complexity of the system. Advent of Industry 4.0 led to development of technologies such as smart factories, simulation, cloud, cyber physical systems which uses digital twins for making informed strategic decisions in a factory. This paper proposes a decision-making framework for a multi-product hybrid layout production system under stochastic disruptions using a digital twin model. A simulation model acts as the digital twin of the physical system which helps to proactively visualize and analyze several key performance parameters of the system and make informed decisions. Objective of this paper is to analyze the performance of two rescheduling methods - Buffer based and Non-buffer based system, subjected to random disruptions. The digital twin is used for simulation of multiple disruption scenarios of the system which uses the two rescheduling methods and performance comparison of the two methods for making strategic decisions based on requirements of increasing profit, and throughput and reducing makespan.