Abstract
The modern manufacturing systems are adopting with lean practices to ensure value addition and waste elimination. Also, product recovery options are found to be vital. Appropriate product design characteristics are identified, and their prioritization is framed as decision-making problem with multiple criteria. Analytical network process is used as solution methodology. The objective of the study is to formulate multi-criteria decision making problem for assessment of lean remanufacturing product design characteristics. The priority order of lean remanufacturing operations is obtained. The study is exemplified with a case conducted with reference to remanufacture of an automotive component. The priority order of criteria is Disassembly > Cleaning > Inspection > Remanufacturing > Reassembly. The inferences desired from the study would facilitate cleaner manufacturing practices. Sensitivity analysis is conducted and practical validity of the method has been tested with an industrial case study.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Chakraborty K, Mondal S, Mukherjee K (2016) Analysis of product design characteristics in remanufacturability: a case study. In Proceedings of international conference on E-business and supply chain competitiveness (EBSCC), Indian Institute of Technology Kharagpur, India, pp 225–235, 12–14 February
Dixit SB (2006) Product design: a conceptual development of product remanufacturing index. Dissertations, University of South Florida
Fang HC, Ong SK, Nee AYC (2015) Product remanufacturability assessment and implementation based on design features. Procedia CIRP 26:571–576
Gungor A, Gupta SM (1999) Issues in environmentally conscious manufacturing and product recovery: a survey. Comput Ind Eng 36(4):811–853
Harivardhini S, Chakrabarti A (2016) A new model for estimating end-of-life disassembly effort during early stages of product design. Clean Technol Environ Policy 18(5):1585–1598
Hatcher GD, Ijomah WL, Windmill JF (2011) Integration of remanufacturing issues into the design process. In: Proceedings of international conference on engineering design (ICED11), vol 5. Technical University of Denmark, pp 259–264, 15–18 Aug 2011
Jayakrishna K, Vimal KEK, Vinodh S (2015) ANP based sustainable concept selection. J Model Manag 10(1):118–136. doi:10.1108/jm2-12-2012-0042
Jeandin T, Mascle C (2016) A New model to select fasteners in design for disassembly. Procedia CIRP 40:425–430
Jun HB, Cusin M, Kiritsis D, Xirouchakis P (2007) A multi-objective evolutionary algorithm for EOL product recovery optimization: turbocharger case study. Int J Prod Res 45(18–19):4573–4594
Lam JSL, Dai J (2015) Environmental sustainability of logistics service provider: an ANP-QFD approach. Int J Logist Manag 26(2):313–333
Lee H, Kim C, Cho H, Park Y (2009) An ANP-based technology network for identification of core technologies: a case of telecommunication technologies. Expert Syst Appl 36(1):894–908
Lin CT, Chiu H, Tseng YH (2006) Agility evaluation using fuzzy logic. Int J Prod Econ 101:353–368
Robotis A, Boyaci T, Verter V (2012) Investing in reusability of products of uncertain remanufacturing cost: the role of inspection capabilities. Int J Prod Econ 140(1):385–395
Rubio S, Corominas A (2008) Optimal manufacturing–remanufacturing policies in a lean production environment. Comput Ind Eng 55(1):234–242
Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill International Book, New York
Seitz MA (2007) A critical assessment of motives for product recovery: the case of engine remanufacturing. J Clean Prod 15(11):1147–1157
Soh SL, Ong SK, Nee AYC (2015) Application of design for disassembly from remanufacturing perspective. Procedia CIRP 26:577–582
Soh SL, Ong SK, Nee AYC (2016) Design for assembly and disassembly for remanufacturing. Assem Autom 36(1):12–24
Tchertchian N, Millet D, El Korchi A (2012) Design for remanufacturing: what performances can be expected? Int J Environ Technol Manag 15(1):28–49
Van Wassenhove LN, Zikopoulos C (2010) On the effect of quality overestimation in remanufacturing. Int J Prod Res 48(18):5263–5280
Vimal KEK, Vinodh S (2015) LCA integrated ANP framework for selection of sustainable manufacturing processes. Environ Model Assess 21(4):507–516. doi:10.1007/s10666-015-9490-2
Yang YPO, Shieh HM, Leu JD, Tzeng GH (2008) A novel hybrid MCDM model combined with DEMATEL and ANP with applications. Int J Oper Res 5(3):160–168
Yang SS, Ong SK, Nee AYC (2015) Towards implementation of DfRem into the product development process. Procedia CIRP 26:565–570
Yang SS, Ong SK, Nee AYC (2016) A decision support tool for product design for remanufacturing. Procedia CIRP 40:144–149
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
See Tables 9, 10, 11, 12, 13, 14, 15, 16, 17 and 18.
Rights and permissions
About this article
Cite this article
Vasanthakumar, C., Vinodh, S. & Vishal, A.W. Application of analytical network process for analysis of product design characteristics of lean remanufacturing system: a case study. Clean Techn Environ Policy 19, 971–990 (2017). https://doi.org/10.1007/s10098-016-1293-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10098-016-1293-x