Abstract
The onset of Industry 4.0 has led to an increased research interest in mass customization production systems. Reconfigurable jigs and fixtures are expected to facilitate customer-driven manufacturing. Scheduling of such fixtures in a mass customization system is yet to be comprehensively investigated. The chapter presents a three-stage method for the optimal scheduling of a two-cell just-in-time manufacturing system that recirculates fixtures for customized parts. The first two stages implemented clustering to produce fixture-part mappings, and intracluster sequencing to enable efficient successive fixture reconfigurations, respectively. The third stage implemented a Mixed Integer Linear Programming (MILP) model to synchronously schedule operations in the two specialized cells, such that total idle time was minimized. A heuristic was developed as an alternative to the MILP model. The paper discusses the three-stage method, with emphasis on the MILP model and Stage 3 Heuristic (S3H). The solutions were compared, and the goodness of the S3H solutions was evaluated in comparison to the optimal solutions. The S3H was found to produce solutions within a range of 5–35% of the corresponding optimal solutions, with far superior solutions times and problem size capabilities.
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