Make-to-stock (MTS) production systems, characterized by high product variety and complex sequence-dependent setup times, face a critical challenge in production scheduling. Conventional single-objective or rule-based scheduling methods often lead to suboptimal Overall Equipment Effectiveness (OEE) and significant inventory service-level violations. To address this gap, this study proposes a novel Hierarchical Greedy Optimization Heuristic. This multi-criteria approach systematically integrates tool group constraints, toolset compatibility, and Earliest Start Date (ESD) sequencing to determine inventory urgency, balancing operational efficiency and service reliability. The methodology is rigorously evaluated using real-world industrial data from a steel tube manufacturing system, with its performance benchmarked against two widely recognized, single-objective heuristics: the Group by Toolset Heuristic and the Order by Earliest Start Date (ESD) Heuristic. Experimental results demonstrate that the proposed heuristic consistently and significantly outperforms the benchmark methods, achieving substantially higher machine utilization (OEE) and a drastic reduction in inventory service-level violations (stockout and safety-stock violations). The findings confirm that the proposed scheduling approach is practical, scalable, and establishes a superior trade-off for sustainable MTS production environments.

Keywords

Sustainable Production Scheduling; Make-to-Stock Manufacturing; Sequence-Dependent Setup Time; Greedy Optimization; Machine Utilization; Inventory Service Level