TY - JOUR
T1 - AHP, Gray Correlation, and TOPSIS Combined Approach to Green Performance Evaluation of Design Alternatives
AU - Tian, Guangdong
AU - Zhang, Honghao
AU - Zhou, Mengchu
AU - Li, Zhiwu
N1 - Funding Information:
Manuscript received October 25, 2016; accepted December 1, 2016. Date of publication March 14, 2017; date of current version June 14, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 51405075 and in part by the International Cooperation and Exchange of the National Natural Science Foundation of China under Grant 51561125002. An earlier version of this work was presented at the 13th IEEE International Conference on Networking, Sensing and Control (ICNSC 2016), Mexico City, Mexico. This paper was recommended by Associate Editor K. W. Hipel. (Corresponding author: MengChu Zhou.) G. Tian is with Transportation College, Jilin University, Changchun 130022, China (e-mail: tiangd2013@163.com).
Publisher Copyright:
© 2013 IEEE.
PY - 2018/7
Y1 - 2018/7
N2 - The green design of electromechanical products is a pivotal link to manufacturing industry. The question on how to design green products must be answered by excellent designers using both advanced design methods and effective assessment techniques of design alternatives. Making an objective and precise assessment of green designs is of increasing importance to ensure sustainable development. This work proposes a framework based on the combination of analytical hierarchy process (AHP), gray correlation (GC), and technique for order performance by similarity to ideal solution (TOPSIS) to evaluate the performance of design alternatives. AHP is used to determine the weights of performance indices and a nonlinear programming model with constraints is proposed to obtain the integrated closeness index based on the similarity closeness index from GC and distance closeness index from TOPSIS. A case study, i.e., three kinds of refrigerators, is illustrated to verify the proposed method. By comparing with existing methods, i.e., AHP-TOPSIS and AHP-GC, the effectiveness of the proposed method has been confirmed. In addition, sensitivity analysis is also provided in order to assess the robustness of the proposed method. Also, the following implication can be obtained from our results: 1) chloro-fluoro-carbons (mg/m3) (C1), production noise (dB) (C6), and environmental cost (C16) have a large impact on refrigerator's green design since these factors carry relatively larger weights. Results of the sensitivity analysis from different cases demonstrate that the best alternative may change when different weights are assigned to the evaluation criteria. This finding means the importance of establishing a qualified group of experts/designers in design evaluation and 2) the selection of design alternatives to produce a green product is critical to product development. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers to assess product design alternatives. The results show that it overcomes the one-sidedness of AHP-TOPSIS and AHP-GC, and makes the evaluation results more objective and realistic. It provides an accurate, effective, and systematic decision support tool for green performance evaluation of product design alternatives.
AB - The green design of electromechanical products is a pivotal link to manufacturing industry. The question on how to design green products must be answered by excellent designers using both advanced design methods and effective assessment techniques of design alternatives. Making an objective and precise assessment of green designs is of increasing importance to ensure sustainable development. This work proposes a framework based on the combination of analytical hierarchy process (AHP), gray correlation (GC), and technique for order performance by similarity to ideal solution (TOPSIS) to evaluate the performance of design alternatives. AHP is used to determine the weights of performance indices and a nonlinear programming model with constraints is proposed to obtain the integrated closeness index based on the similarity closeness index from GC and distance closeness index from TOPSIS. A case study, i.e., three kinds of refrigerators, is illustrated to verify the proposed method. By comparing with existing methods, i.e., AHP-TOPSIS and AHP-GC, the effectiveness of the proposed method has been confirmed. In addition, sensitivity analysis is also provided in order to assess the robustness of the proposed method. Also, the following implication can be obtained from our results: 1) chloro-fluoro-carbons (mg/m3) (C1), production noise (dB) (C6), and environmental cost (C16) have a large impact on refrigerator's green design since these factors carry relatively larger weights. Results of the sensitivity analysis from different cases demonstrate that the best alternative may change when different weights are assigned to the evaluation criteria. This finding means the importance of establishing a qualified group of experts/designers in design evaluation and 2) the selection of design alternatives to produce a green product is critical to product development. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers to assess product design alternatives. The results show that it overcomes the one-sidedness of AHP-TOPSIS and AHP-GC, and makes the evaluation results more objective and realistic. It provides an accurate, effective, and systematic decision support tool for green performance evaluation of product design alternatives.
KW - Analytical hierarchy process (AHP)
KW - design alternatives
KW - evaluation
KW - gray correlation (GC)
KW - green performance
KW - technique for order performance by similarity to ideal solution (TOPSIS)
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U2 - 10.1109/TSMC.2016.2640179
DO - 10.1109/TSMC.2016.2640179
M3 - Article
AN - SCOPUS:85040069353
SN - 2168-2216
VL - 48
SP - 1093
EP - 1105
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 7
ER -