Abstract
This study proposes two production planning models for a case study solar cell manufacturing company who faces uncertain future demands. The objective of the case study company is to determine which and how many materials should be purchased and which and how many products should be produced with the objective of maximizing net profit. However, uncertain demands make the planning problem difficult. Many deterministic production planning models are used to solve the production planning problem. In a significantly uncertain environment, it is questionable that a deterministic model could drive robust plans. Therefore, it could be necessary to develop stochastic models that consider uncertainties. This study proposes two production planning models, a deterministic model and a stochastic model, to solve a production planning problem for a case study solar cell manufacturing company with demand uncertainty and compares their long-term effectiveness via simulation experiments. A common practice production planning is called rolling horizon, in which production plan is revised at the beginning of each period. This study simulates the deterministic model and stochastic model under rolling planning horizon environment and compares their performances under a number of control factors. At the end of the experiments, a paired -test is used to compare whether the long-term profit of these two production planning models are statistically significantly different.