A two-level optimisation-simulation method for production planning and scheduling: the industrial case of a human–robot collaborative assembly line. Issue 9 (3rd May 2022)

• Record Type: Journal Article
• Authors: Vieira, Miguel; Moniz, Samuel; Gonçalves, Bruno S.; Pinto-Varela, Tânia; Barbosa-Póvoa, Ana Paula; Neto, Pedro
• Is Part Of: International journal of production research. Volume 60:Issue 9(2022)
• Page Start: 2942
• Page End: 2962
• Publication Date: 2022-05-03
• Subjects: Production planning and scheduling -- optimisation-simulation method -- human–robot industrial assembly -- mixed-integer linear programming -- ‌discrete-event simulation; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2021.1906461
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : In this work, a novel optimisation-simulation based on the Recursive Optimisation-Simulation Approach (ROSA) methodology is developed to provide effective decision-support for integrated production planning and scheduling. The proposed iterative approach optimises production plans while satisfying complex scheduling constraints, such as robots' allocation in collaborative tasks. The plans are determined through a two-level MILP model and are iteratively evaluated by a detailed discrete-event simulation model to guarantee capacity-feasible solutions at the scheduling level. Through an industrial case study of a multistage assembly line design collaboratively operated by humans and mobile shared robots, near-optimal solutions comprise lot-sizing decisions, the release schedule of production orders, the allocation of tasks to humans or robots, and the number of robots per period. Moreover, by addressing a set of propositions to assess the methodology, the results highlight the advantages of the hybrid approach to converge into optimised operational decisions and analyse the process dynamics.