@article { author = {Fu, K. and Chen, Zh. and Zhang, Y. and Wee, H.M.}, title = {Optimal production inventory decision with learning and fatigue behavioral effects in labor-intensive manufacturing}, journal = {Scientia Iranica}, volume = {27}, number = {2}, pages = {918-934}, year = {2020}, publisher = {Sharif University of Technology}, issn = {1026-3098}, eissn = {2345-3605}, doi = {10.24200/sci.2018.50614.1788}, abstract = {Behavioral economic has received much attention recently. Learning and fatigue are two typical behavioral phenomena in industrial production operation processes. The existence of learning and fatigue result in a dynamic change in productivity. In this paper, a classical economic production quantity model is extended to consider the behavioral economic value of learning and fatigue. Based on a real case study, each production cycle is divided into five phases, i.e, the learning phase, stable phase, fatigue phase, fatigue recovery (rest) phase, and the relearning phase. The new production inventory decision model is incorporated with dynamic productivity and learning-stable-fatigue-recovery effect. Numerical simulation and sensitivity analysis show that appropriate rest alleviates employees fatigue and increases productivity, resulting in a lower average production cost. On the other hand, when the rest time is too high, exceeding a certain value, it leads to the decline of the actual labor productivity, resulting in an increase in the average cost of the system.}, keywords = {Behavioral economics,productivity,human factor,learning effect,fatigue effect,production inventory decision}, url = {https://scientiairanica.sharif.edu/article_21014.html}, eprint = {https://scientiairanica.sharif.edu/article_21014_3efd208e1213175653d6cea332cfd34b.pdf} }