Optimum production planning model under probabilistic market demand

Abstract

An Optimum Production Planning ( OPP ) Model for a robot-served machine in the make-to-order (MTO) industry is proposed to minimize the production cost under deterministic order quantity and deadline constraints. The operational cost of the machine and the part handling robot, as well as the fixed costs for both equipments and the product holding cost are considered simultaneously into the objective of the model. This study not only implements the Lagrange Method to resolve the production planning problem, but also provides a verified cost-related property of the Lagrange Multiplier for budget and/or cost forecasting under the deterministic market. Through the forecasted future demand, the step-by-step algorithm to reach the optimal production plan for the probabilistic market is then constructed. In addition, the versatility and adaptability of this study are exemplified through numerical simulation. This paper surely contributes the applicable solution to control a robot-served machine under certain market, as well as to plan the productivity of the machine and the robot in the forecasted future..