A Two-phase Model for Product Design Development and Evaluation and Supplier Selection in Product Configuration Change Process (Case study: SUPCO)

Journal of Modern Processes in Manufacturing and Production

مقاله 2، دوره 3، شماره 3، آبان 2014، صفحه 17-40   

نویسندگان

Mousa Amini^{* 1}؛ Alireza Alinezhad²؛ Sepideh Ghasemian²

¹M.Sc. graduate of Industrial Engineering, Alghadir University, Tabriz, Iran

²Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

چکیده

A supply chain is composed of a complex sequence of processing stages, ranging from raw materials supplies, parts manufacturing, components and end-products assembling, to the delivery of end products. In the context of supply chain management, supplier selection decision is considered one of the key issues faced by operations and purchasing managers to remain competitive. Therefore, requirements of engineers or customers may result in product configuration change with product life cycle. Effective management of product configuration can actually enhance productivity and customer satisfaction. This study proposes a two-phase model in the first phase of which an innovative design for new parts will be proposed by contradiction matrix, and translating contradictions into 39 engineering parameters of TRIZ , solving them by 40 innovative principals and by means of AHP fuzzy. In the second phase, an appropriate supplier for new product will be selected by value engineering and target costing. Finally, a case of clutch system in SUPCO is used to approve the applicability of the proposed approach. In this study, the best choice is the use of fuzzy AHP. After determining the total cost of the target product and initial screening of the suppliers based on that, the index values are calculated for each supplier according to the criteria of the organization. Thus, the best suppliers with the highest value to the organization have been selected.

کلیدواژه‌ها

TRIZ؛ Product configuration change؛ fuzzy AHP؛ Target costing؛ Value engineering