Production planning in DRC systems considering worker performance

This paper studies the effects of some human characteristics on production planning in a Dual-Resource Constrained (DRC) system and the quality of products. Human behavior is captured by the learning-for getting-fatigue-recovery model (LFFRM). The production process is modeled through a Quality Learning Curve (QLC) model while the quality deficits are the result of human error and machine malfunction. The system performance is presented with a twofold cost function considering direct (time) and indirect (quality) costs. The results indicate that the system performance is concave over a production run, which represents the optimum flexibility level, transfer policy, and the workstation configuration. (C) 2015 Elsevier Ltd. All rights reserved.