Jobs scheduling within Industry 4.0 with consideration of worker’s fatigue and reliability using Greedy Randomized Adaptive Search Procedure

摘要

The agility and the reactivity of the emerging Industry 4.0 work paradigm will probably lead to work intensification. Hence, in order to ensure an effective and safe human machine systems, jobs scheduling must be addressed with consideration of human factors. Following this trend, this paper details a new integer programming model for jobs scheduling with consideration of worker fatigue and reliability. Using Greedy Randomized Adaptive Search Procedure (GRASP), this model can be used in real-time to support manufacturing execution system in Factories of the Future to achieve efficient and safe jobs scheduling.