Abstract
Human labor plays a central role in modern manufacturing systems. Therefore, a reliable description of both hardware and human components is required for the (re)design of such systems. In past work, hardware has received much attention, whereas the quantification of operator performance and its variability was often neglected. Mummolo et al. [2004. Learning and tiredness phenomena in manual operation performed in lean automated manufacturing systems: a reference model. In: International IMS Intelligent Manufacturing Systems Forum 2004, Cernobbio, CO, Italy, pp. 341–346] presented a model describing both fatigue and learning effects on worker behavior. In this paper, the authors show that dynamic worker behavior over time has a profound impact on the queuing behavior of flow lines. Simulation results show that these conclusion hold for both short- and long-term simulation models.
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