A fuzzy QFD approach to determine supply chain management strategies in the dairy industry

被引:43
作者
Ayag, Zeki [1 ]
Samanlioglu, Funda [1 ]
Buyukozkan, Gulcin [2 ]
机构
[1] Kadir Has Univ, Fac Engn, Dept Ind Engn, Istanbul, Turkey
[2] Galatasaray Univ, Fac Engn & Technol, Dept Ind Engn, Istanbul, Turkey
关键词
Dairy customer needs; Dairy logistics requirements; Supply chain management strategies; Fuzzy QFD; Multi-objective mathematical programming; QUALITY FUNCTION DEPLOYMENT; PRIORITIZE DESIGN REQUIREMENTS; SYSTEM;
D O I
10.1007/s10845-012-0639-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The aim of this study is to identify the crucial logistics requirements and supply chain management (SCM) strategies for the dairy industry. For product or service development, quality function deployment (QFD) is a useful approach to maximize customer satisfaction. The determination of design requirements and supply chain management strategies are important issues during QFD processes for product or service design. For this reason, a fuzzy QFD methodology is proposed in this study to determine these aspects and to improve customer satisfaction. Qualitative information is converted firstly into quantitative parameters, and then this data is combined with other quantitative data to parameterize two multi-objective mathematical programming models. In the first model, the most important logistic requirements for the company are determined based on total technical importance, total cost, total feasibility and total value increment objectives, and in the second model, based on these objectives, appropriate supply chain management strategies are determined. Finally, a case study from the Turkish dairy industry is given to illustrate the proposed approach.
引用
收藏
页码:1111 / 1122
页数:12
相关论文
共 28 条
[1]  
Akao Y., 1990, QUALITY FUNCTION DEP
[2]  
[Anonymous], 1985, INT J APPROXIMATE RE
[3]  
[Anonymous], 1999, APPL MODIFIED FUZZY
[4]   A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment [J].
Ayag, Z .
IIE TRANSACTIONS, 2005, 37 (09) :827-842
[5]   An intelligent approach to machine tool selection through fuzzy analytic network process [J].
Ayag, Z. ;
Ozdemir, R. G. .
JOURNAL OF INTELLIGENT MANUFACTURING, 2011, 22 (02) :163-177
[6]  
Bech AC, 1997, DEV FOOD SCI, V38, P3
[7]  
BECH AC, 1994, 19 MAPP
[8]  
Costa A. I. A., 1996, THESIS WAGENINGEN U
[9]   Product design resources optimization using a non-linear fuzzy quality function deployment model [J].
Fung, RYK ;
Tang, J ;
Tu, Y ;
Wang, D .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2002, 40 (03) :585-599
[10]   An intelligent hybrid system for customer requirements analysis and product attribute targets determination [J].
Fung, RYK ;
Popplewell, K ;
Xie, J .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1998, 36 (01) :13-34