Multi-stage production planning using fuzzy multi-objective programming with consideration of maintenance

Production planning is one of the crucial issues in manufacturing environments and is responsible for determining the optimal production and inventory levels. There are many studies conducted in this domain that are mainly focused on production planning costs. This study, proposes a novel multi-objective Mixed Integer Programming (MIP) model for multi-stage production planning. Considered objectives in this study are conflicting, un-measurable and fuzzy consisting of: determining optimal production level, minimizing work-in-process (WIP) inventory procurement cost, maintenance cost and new machine installations cost. In addition, this study provides a methodology based on fuzzy logic to maintain the desired balanced input-output relation at each stage and to achieve targeted production output in the final stage. In order to solve this model, six different multi-objective optimization methods are used and then compared. Among the findings of this study, with the focus on minimizing the total cost of the production system, we consider determination of the appropriate stages for the provision of WIP inventory, maintenance and the installation of new machine(s) to create a production process with minimum stop altogether. The solution approach is illustrated with a numerical example. Finally the sensitivity analysis in the form of charts is presented.