Configuration-Driven Machine Availability Constraints in Job Shop Scheduling

This dataset supports research on configuration-driven job shop scheduling with machine availability constraints, where machine reliability is directly affected by operating configurations. In real-world manufacturing systems—particularly Reconfigurable Manufacturing Systems (RMS)—factors such as tooling, spindle speed, and load level influence equipment wear, degradation, and maintenance needs. The dataset captures this configuration–reliability relationship by providing: Operation-specific processing times across multiple machine configurations Setup times between configurations Configuration eligibility per operation Machine-specific maintenance windows Configuration-induced degradation effects on machines It is designed for use in optimization models that jointly schedule production and maintenance, enabling more responsive and cost-efficient decisions in systems where machine reliability varies with usage. The structure is compatible with MILP formulations that integrate degradation-aware maintenance planning in RMS environments.