Incorporating human fatigue and recovery into the learning-forgetting process

The available learning and forgetting models do not consider the physical loading that performing a task requires. In some situations, physical loading results in workers' fatigue on the job that is followed by rest breaks to alleviate it. The aim of this paper is to present the learning-forgetting-fatigue-recovery model (LFFRM) that addresses possible issues relating to workers' capabilities and restrictions in manufacturing environments. Numerical examples are solved to address some research questions regarding the model optimization and its constraints. The main results show that incorporating learning into a production process decreases fatigue and improves the performance of the system. Worker fatigue, on the other hand, increases production time and decreases production output. A recovery break must be of enough length to alleviate some of the accumulated fatigue. However, longer recovery times extend the lead time and deteriorate the production performance due to forgetting. (C) 2013 Elsevier Inc. All rights reserved.