Sustainable product design assessment combining the fuzzy theory and grey correlation analysis method

DOI

10.2991/icmia-16.2016.22How to use a DOI?

Keywords

sustainable design; sustainability assessment; fuzzy theory; grey correlation analysis

Abstract

Sustainable product design has become significant factor for customers' selection, whereas it is difficult to evaluate sustainability with imprecise, vague and uncertain information. This paper proposes sustainable design performance assessment model integrating fuzzy theory and grey correlation analysis method considering fuzziness, uncertainty, correlation and coupling characteristics of evaluation index. The multi-level hierarchical structure is established to conduct a more effective analysis through defining sustainability criteria and sub-criteria. Furthermore, the fuzzy theory is utilized to determine weights of criteria and sub-criteria to improve the accuracy of assessment result and eliminate redundancy and fuzziness of the evaluating indices. Then, grey correlation analysis method is employed to present the correlation degree between reference sequences and comparative sequences involving all criteria and sub-criteria. Meanwhile, the product multi-level comprehensive sustainability index is obtained integrating all factors in every level by superposition to provide accurate for design, evaluation and solve the redundancy and imprecise problems. Finally, sustainability assessment of the elevator as case study to verify the effectiveness of the proposed method.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chunhua Feng
AU  - Qibing Wang
PY  - 2016/11
DA  - 2016/11
TI  - Sustainable product design assessment combining the fuzzy theory and grey correlation analysis method
BT  - Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016)
PB  - Atlantis Press
SP  - 117
EP  - 122
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmia-16.2016.22
DO  - 10.2991/icmia-16.2016.22
ID  - Feng2016/11
ER  -