A Multiple Objective Decision Analysis Model for Capacity Expansion Plans Selection in Manufacturing

Abstract

Capacity expansion is a critical decision with potential circumstances of risks and opportunities. This decision is further complicated given the conflicting decision measures and stakeholders’ preferences. Previous research is limited in providing a systematic framework to deal with such decisions in manufacturing environments. In this paper, decision analysis is used for the assessment of the appropriate capacity expansion plans of a mechanical contracting and fabrication company serving aluminum smelting industry. Repairing anodes used in aluminum smelting is a critical work that is outsourced to qualified companies. The increased demand for this kind of repair creates an opportunity for the contracting company to expand capacity. The expansion will qualify the company to receive more orders for anode maintenance and other mechanical services and respond more effectively to client demands, allowing for the advancement of expertise through the acquisition of large projects. However, the decision to expand may be a complex problem for a number of reasons. One of the reasons is ascribed to the appropriate form and the time required for expansion. Factors such as market rivalry, investment risk, budget constraints, bidding policies, and operational capabilities all complicate the decision making process, necessitating the use of a decision analysis model. Therefore, this article proposes the multiple objective decision analysis (MODA) approach for studying capacity expansion problem. MODA's cost-value model examines expansion plans within acceptable budgets and allows for trade-offs between value and cost, whilst the value gap analysis identifies opportunities to improve the values of the expansion plans. The sensitivity analysis demonstrates the model's robustness to changes in swing weights and value curves. The proposed model provides manufacturers with further investigation of the alternative expansion plans with insights into the associated cost and gaps for improvements.