A hybrid approach to support recovery strategies (A case study)

被引:15
作者
Dehghanbaghi, M. [1 ]
Hosseininasab, H. [1 ]
Sadeghieh, A. [1 ]
机构
[1] Yazd Univ, Dept Ind Engn, Yazd, Iran
关键词
Fuzzy inference system; Fuzzy AHP; Product returns; Recovery; GROUP DECISION-MAKING; REVERSE LOGISTICS; DISASSEMBLY PROCESSES; PRODUCT RETURNS; SYSTEM; SELECTION; SUSTAINABILITY; IMPLEMENTATION; IMPACT;
D O I
10.1016/j.jclepro.2015.11.064
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A key strategic consideration in the recovery system of any product is to make accurate decisions on reverse manufacturing alternatives including both recovery and disposal options. The nature of such decisions is complex due to the uncertainty that exists in the quality of the product returns and the lack of information on them. Consequently, the need for the correct diagnosis of recovery/disposal options for the returned products necessitates the development of a comprehensive model that gives consideration to all general and specific parameters. Finding the best recovery strategies is based on both the product and the recovery process properties. This study therefore presents a new integrated approach, focusing on brown goods, based on a fuzzy rule-based system and fuzzy AHP to provide a correct and accurate decision-making mechanism for ranking the recovery/disposal strategies by knowledge acquisition for each particular returned product. The presented model considers the products' properties and the recovery/disposal processes' properties separately in two phases. To achieve the objective of this study, the proposed model is used to analyze a case study of mobile phone returns, to support recovery strategies of returns by correct decisions on recovery options which leads to reduce human errors, wastes and the costs of recovery process. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:717 / 729
页数:13
相关论文
共 49 条
[1]  
Abraham A., 2005, HDB MEASURING SYSTEM
[2]   Sustainable supplier selection: A ranking model based on fuzzy inference system [J].
Amindoust, Atefeh ;
Ahmed, Shamsuddin ;
Saghafinia, Ali ;
Bahreininejad, Ardeshir .
APPLIED SOFT COMPUTING, 2012, 12 (06) :1668-1677
[3]   The effect of categorizing returned products in remanufacturing [J].
Aras, N ;
Boyaci, T ;
Verter, V .
IIE TRANSACTIONS, 2004, 36 (04) :319-331
[4]   A fuzzy inference system for pump failure diagnosis to improve maintenance process: The case of a petrochemical industry [J].
Azadeh, A. ;
Ebrahimipour, V. ;
Bavar, P. .
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (01) :627-639
[5]   Performance analysis of a hybrid system under quality impact of returns [J].
Behret, Huelya ;
Korugan, Aybek .
COMPUTERS & INDUSTRIAL ENGINEERING, 2009, 56 (02) :507-520
[6]   FUZZY HIERARCHICAL ANALYSIS [J].
BUCKLEY, JJ .
FUZZY SETS AND SYSTEMS, 1985, 17 (03) :233-247
[7]   An integrated fuzzy decision support system for multicriterion decision-making problems [J].
Chan, FTS ;
Chan, HK ;
Chan, MH .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2003, 217 (01) :11-27
[8]   A decision-making support system on a products recovery management framework a fuzzy approach [J].
Fernandez, Isabel ;
Puente, Javier ;
Garcia, Nazario ;
Gomez, Alberto .
CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, 2008, 16 (02) :129-138
[9]   Quantitative models for reverse logistics: A review [J].
Fleischmann, M ;
BloemhofRuwaard, JM ;
Dekker, R ;
vanderLaan, E ;
vanNunen, JAEE ;
VanWassenhove, LN .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1997, 103 (01) :1-17
[10]   Improving sustainability through effective reuse of product returns: minimizing waste in a batch blending process environment [J].
French, Monique L. .
JOURNAL OF CLEANER PRODUCTION, 2008, 16 (15) :1679-1687