Dual-Resource Constrained Flexible Job Shop Scheduling for SMT Back-End Production and an Empirical Study of Wearable Devices

Increasing needs for smart production of high-mix consumer electronics products with shortening product life cycles and complex product mix in wearable electronics industry are challenging. Surface mount technology (SMT) back-end manufacturing is semi-automatic and labor-intensive with combinatorial complexity for configurating multiple resources that have caused increasing costs and resource waste. This study aims to develop an effective solution for dual resource constrained flexible job shop scheduling considering realistic production constraints, non-deterministic polynomial-time hardness, and anthropic factors for implementation in real settings. Indeed, the main contributions of the proposed adaptive scheduling solution include the integration of quantum tunneling mutation mechanism and genetic algorithm to minimize the total tardy jobs, the first-day due tardiness, and makespan for high-mix dual resource constrained flexible job shop scheduling that can obtain near optimal solution within practically limited computing time. An empirical study was conducted for validation. The results have shown the practical viability of the developed solution that can be quickly responsive and adaptive to dynamic needs. Note to Practitioners—SMT back-end scheduling solution is developed to empower smart production of high-mix for wearable consumer electronics with shortening product life cycles in practice. The developed solution for dual resource constrained flexible job shop scheduling considering realistic production constraints, non-deterministic polynomial-time hardness, and anthropic factors to minimize the total tardy jobs, the first-day due tardiness, and makespan. The developed solution has been implemented in a world leading consumer electronics company.