Supply chain management: a modular Fuzzy Inference System approach in supplier selection for new product development

The critical objectives of purchasing departments include obtaining the product requested, at the right cost, in the right quantity, with the best quality, at the right time, from the right supplier. These goals require effective decisions concerning supplier selection at the early stage of product...

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Bibliographic Details
Published inJournal of intelligent manufacturing Vol. 19; no. 1; pp. 1 - 12
Main Authors Carrera, Diego A., Mayorga, Rene V.
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.02.2008
Springer Nature B.V
Subjects
Business and Management
Cognition & reasoning
Competition
Competitive advantage
Control
Decision making
Decision making models
Fuzzy logic
Fuzzy sets
Machines
Manufacturing
Mathematical programming
Mechatronics
Process controls
Processes
Product development
Production
Production management
Purchasing
Robotics
Set theory
Studies
Suppliers
Supply chain management
Fuzzy logic
Fuzzy Inference System (FIS)
Product suppliers
Supply chain management
Intelligent systems
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Summary:The critical objectives of purchasing departments include obtaining the product requested, at the right cost, in the right quantity, with the best quality, at the right time, from the right supplier. These goals require effective decisions concerning supplier selection at the early stage of product development. This work provides an application of fuzzy set theory in supply chain management, specifically in supplier selection for new product development. Here, a Fuzzy Inference System is proposed as an alternative approach to handle effectively the impreciseness and uncertainty that are normally found in supplier selection processes. This paper also shows that the proposed decision-making model is applicable to any supply chain system.
ISSN:0956-5515
1572-8145
DOI:10.1007/s10845-007-0041-9