Setup‐Optimized Sequencing in Job Shops: Modeling Workstation Productivity and Lateness Behavior

Sequence‐dependent setups in job‐shop manufacturing create a trade‐off: raising productivity through setup‐optimized sequencing tends to reduce schedule reliability. This study presents a modeling approach that quantifies this trade‐off at the workstation level. Building on the production operating curve and the boundary case with many setup families, the approach links sequencing effects to mean work‐in‐process (WIP) and utilization. The model yields expressions for the performance‐based and the effective productivity gains, which are bounded by the relative setup share and can only be realized during active production time. It also provides an expression for the sequence‐induced standard deviation of relative lateness as a function of WIP and utilization. Sensitivity results show proportional dependence on the setup share and diminishing gains with increasing numbers of setup families, while a two‐point comparison demonstrates the trade‐off. The model provides consistent metrics for positioning workstations within the productivity–schedule‐reliability trade‐off and for supporting sequencing and WIP‐related operating decisions.