Abstract This paper aims at implementing an optimization technique in smart manufacturing applications for co-optimizing the operation of multiple production lines to supply the desired demand for multiple products. The proposed model, which is formulated as a mixed-integer linear programming (MILP) problem, minimizes the total manufacturing cost by co-optimizing the operation schedule of production lines. The proposed model implements several operating constraints of the production lines that include their energy consumption and associated costs, productivity, scrap rates, changeover duration, and labor costs. The proposed model is implemented on a sample manufacturer, where seven production lines with different operational constraints are optimized to manufacture six product types. In addition, the model is utilized to optimize the operation of a real-world food production plant with five lines and twelve different product types. The simulation results show that the proposed optimal scheduling model allows the manufacturers to enhance production efficiency and save on operation costs by co-optimizing the operation schedule of production lines. Sensitivity analyses are conducted to demonstrate the performance of the model in different demand levels, where the manufacturers are enabled to optimally schedule the production lines at minimum cost given the production demand.

中文翻译：

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应用于食品生产计划的智能制造商优化生产调度

摘要 本文旨在在智能制造应用中实施一种优化技术，以协同优化多条生产线的运行，以满足多种产品的需求。所提出的模型被表述为混合整数线性规划 (MILP) 问题，通过共同优化生产线的操作计划来最小化总制造成本。提议的模型实现了生产线的几个操作约束，包括它们的能源消耗和相关成本、生产率、废品率、转换持续时间和劳动力成本。建议的模型在样本制造商上实施，其中优化了具有不同操作约束的 7 条生产线，以制造 6 种产品类型。此外，该模型用于优化具有 5 条生产线和 12 种不同产品类型的真实食品生产工厂的运营。仿真结果表明，所提出的优化调度模型可以使制造商通过协同优化生产线的运行调度来提高生产效率并节省运营成本。进行敏感性分析以证明模型在不同需求水平下的性能，使制造商能够在给定生产需求的情况下以最低成本对生产线进行最佳调度。仿真结果表明，所提出的优化调度模型可以使制造商通过协同优化生产线的运行调度来提高生产效率并节省运营成本。进行敏感性分析以证明模型在不同需求水平下的性能，其中制造商能够在给定生产需求的情况下以最低成本对生产线进行最佳调度。仿真结果表明，所提出的优化调度模型可以使制造商通过协同优化生产线的运行调度来提高生产效率并节省运营成本。进行敏感性分析以证明模型在不同需求水平下的性能，其中制造商能够在给定生产需求的情况下以最低成本对生产线进行最佳调度。