Production planning with a two stage stochastic programming model in a kitting facility under demand and yield uncertainties
ABSTRACT The main objective of this study is to develop a two stage stochastic programming framework for lot sizing and scheduling the production activities at a kitting facility to support a manufacturing plant. The novelty of the study lies in modeling multiple uncertainties using two stage stochastic programming to solve a kitting specific production planning problem in a manufacturing setting. The demand for the kits and the yield of the kitting workers are the two sources of uncertainties considered in this study. The first stage decisions include the baseline production schedule and the workforce requirement, while the second stage makes recourse decisions on overtime production. The proposed decision making framework is validated on a multi period, multi product case study involving a kitting facility supporting a manufacturing plant producing braking equipment. The main conclusion of the study is that uncertainties have significant impacts on kitting planning decisions and that the proposed two stage stochastic programming model was robust in determining optimal production plans under uncertainty.