Analysis of an Industrial Component Commonality Problem
European Journal of Operational Research , Volume 186 - Issue 2 p. 801- 811
We discuss a case study of an industrial production-marketing coordination problem involving component commonality. For the product line considered, the strategic goal of the company is to move from the current low volume market to a high volume market. The marketing department believes that this can be achieved by substantially lowering the end products’ prices. However, this requires a product redesign to lower production costs in order to maintain profit margins. The redesign decision involves grouping end products into families. All products within one family use the same version of some components. This paper fits in the stream of recent literature on component commonality where the focus has shifted from inventory cost savings to production and development cost savings. Further, we consider both costs and revenues, leading to a profit maximization approach. The price elasticity of demand determines the relationship between the price level and number of units sold. Consequently, we integrate information from different functional areas such as production, marketing and accounting. We formulate the problem as a net-present-value investment decision. We propose a mixed integer nonlinear optimization model to find the optimal commonality decision. The recommendation based on our analysis has been implemented in the company. In addition, the application allows us to experimentally validate some claims made in the literature and obtain managerial insights into the trade-offs.
|application, assortment problem, case study, component commonality, component sharing, manufacturing|
|ERIM Top-Core Articles|
|European Journal of Operational Research|
|Organisation||Erasmus Research Institute of Management|
Jans, R.F, Degraeve, Z, & Schepens, L. (2008). Analysis of an Industrial Component Commonality Problem. European Journal of Operational Research, 186(2), 801–811. doi:10.1016/j.ejor.2007.01.008