Sensitivity Analysis on Inventory Classification Methods for Oilfield Equipment Industry

This paper presents a case study for inventory management for an oilfield equipment company. The management encounters the problem of deciding which parts to manufacture in-house and which ones to subcontract. A decision support system (DSS) is developed which ranks component parts by integrating multi-criteria classification methods considering both quantitative (e.g., cost and demand) and qualitative (e.g., importance) factors. The focus on this research is to perform a sensitivity analysis on weight assignment for each criterion. This information is important in applications of inventory management since industries may not be able to manufacture all the necessary parts on time. Real world data from an oilfield equipment industry are used where inventory control problems have arisen because the company does not have the capacity to manufacture all the required parts to satisfy customer orders.