Skip to main content
SpringerLink
Log in

A comprehensive end-of-life strategy decision making approach to handle uncertainty in the product design stage

  • Original Paper
  • Published:
Research in Engineering Design Aims and scope Submit manuscript

Abstract

This study employs fuzzy logic to evaluate uncertain component end-of-life (EOL) options in the design stage. Determining EOL strategies during the product design stage can be complex. For example, EOL strategies for retired bicycle components are various and may change with geographic location. Thus, adopting fixed EOL strategies in the product design stage may not always be appropriate; the element of uncertainty should be considered. Limited research has examined uncertainty of EOL strategies during the design stage. Moreover, the evaluation of EOL strategies in a comprehensive manner has not been shown in a realistic case study. These facts motivate this investigation. Fourteen evaluation criteria are used to generate a comprehensive framework for assessing seven EOL strategies. The evaluation process generates the likelihood for each of these strategies by aggregating fuzzy set operations and a left–right fuzzy ranking method. Using SUMPRODUCT calculation for these weights/probabilities and input sustainability value (i.e., cost, environmental impact and labor time), expected values are derived to represent the sustainability values for each EOL strategy. A Technique-for-Order-of-Preference-by-Similarity-to-Ideal-Solution (TOPSIS) based method is employed to identify the appropriate EOL strategy for each component/product. A refrigerator is used as a case study to illustrate the methodology. This study addresses the uncertainty involved in identifying an EOL strategy for a specific product component during the design stage through the use of fuzzy logic. The method closes a gap in the current EOL strategy assessment criteria and introduces a comprehensive evaluation framework to capture multiple strategic perspectives by incorporating 14 key evaluation criteria.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

(Adapted from Ma and Kremer 2015)

Fig. 3

(Adapted from Ma and Kremer 2016b)

Fig. 4

(Adapted from Ma and Kremer 2016b)

Fig. 5
Fig. 6

(Adopted from Chung et al. 2011)

Similar content being viewed by others

References

  • Abudullah ZT, Shunsheng G, Buyun S (2015) Eco-design application to drive sustainable manufacturing. Adv Sci Lett 21(12):3610–3614

    Article  Google Scholar 

  • Appelqvist P, Lehtonen JM, Kokkonen J (2004) Modeling in product and supply chain design: literature survey and case study. J Manuf Technol Manag 15(7):675–686

    Article  Google Scholar 

  • Beach R, Muhlemann AP, Price DHR, Paterson A, Sharp JA (2000) A review of manufacturing flexibility. Eur J Oper Res 122(1):41–57

    Article  MATH  Google Scholar 

  • Behdad S, Williams AS, Thurston D (2012) End-of-life decision making with uncertain product return quality. J Mech Des 134(10):10092

    Article  Google Scholar 

  • Boran FE, Genc S, Kurt M, Akay D (2009) A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst Appl 36:11363–11368

    Article  Google Scholar 

  • Bryant CR, Sivaramakrishnan KL, Wie MV, Stone RB, McAdams DA (2004) A modular design approach to support sustainable design. In: Proceedings of DETC’04 ASME 2004 design engineering technical conference and computers and information in engineering conference, Salt Lake City, Utah

  • Bufardi A, Gheorghe R, Kiritsis D, Xirouchakis P (2004) Multicriteria decision-aid approach for product end-of-life alternative selection. Int J Prod Res 42(16):3139–3157

    Article  Google Scholar 

  • Center for Remanufacturing and Reuse (2013) A description of the design for end-of-life process. http://www.remanufacturing.org.uk/pdf/story/1p295.pdf?session=RemanSession:807618970f36920117UiJ20B9285

  • Chen SJ, Hwang CL (1992) Fuzzy multiple attribute decision making methods and application. Springer, Berlin

    Book  Google Scholar 

  • Chung WS, Okudan GE, Wysk RA (2011) A modular design approach to improve the life cycle performance derived from optimized closed-loop supply chain. In: Proceedings of the ASME 2011 international design engineering technical conference & computers and information in engineering conference, Washington, DC

  • Chung WS, Kremer GEO, Wysk RA (2016) A dynamic programming method for product upgrade planning incorporating technology development and end-of-life decisions. J Ind Prod Eng 5:1–12

    Google Scholar 

  • Delgado M, Verdegay JL, Vila V (1993) Linguistic decision making models. Int J Intell Syst 7(5):479–492

    Article  MATH  Google Scholar 

  • Dowlatshahi S (1992) Purchasing’s role in a concurrent engineering environment. Int J Purch Mater Manag 28(1):21–25

    Google Scholar 

  • Dror IE, Charlton D (2006) Why experts make errors. J Forensic Identif 56(4):600–616

    Google Scholar 

  • Dutta P, Boruah H, Ali T (2011) Fuzzy arithmetic with and without using α-cut method: a comparative study. Int J Latest Trends Comput 2(1):99–107

    Google Scholar 

  • Erdos G, Kis T, Xirouchakis P (2001) Modeling and evaluating product end-of-life options. Int J Prod Res 39(6):1203–1220

    Article  MATH  Google Scholar 

  • Gao MM, Zhou MC, Tang Y (2004) Intelligent decision making in disassembly process based on fuzzy reasoning Petri nets. IEEE Trans Syst Man Cybern Part B Cybern 34(5):2029–2034

    Article  Google Scholar 

  • Huang HH, Zhang L, Liu ZF, Sutherland JW (2010) Multi-criteria decision making and uncertainty analysis for materials selection in environmentally conscious design. Int J Adv Manuf Technol 52(5):421–432

    Google Scholar 

  • Hula A, Jalali K, Hamza K, Skerlos SJ, Saitou K (2003) Multi-criteria decision-making for optimization of product disassembly under multiple situations. Environ Sci Technol 37(23):5303–5313

    Article  Google Scholar 

  • Ijomah W, Bennett JP, Pearce J (1999) Remanufacturing Evidence of environmental conscious business practice in UK. In: EcoDesign ‘99 first international symposium on environmentally conscious design and inverse manufacturing, Published by IEEE Computer Society Piscataway NJ, Tokyo, Japan, pp 192–196

  • Ishii K, Juengel C, Eubanks CF (1995) Design for product variety: key to product line structuring. In: Proceedings of the 1995 ASME design engineering technical conferences, 7th international conference on design theory and methodology, Boston, MA

  • Ji YJ, Chen XB, Qi GN, Song LW (2013) Modular design involving effectiveness of multiple phases for product life cycle. Int J Adv Manuf Technol 66(9–12):1475–1488

    Article  Google Scholar 

  • Keeney RL, Raiffa H (1976) Decisions with multiple objectives: preference and value tradeoffs. Wiley, Chichester

    MATH  Google Scholar 

  • Kikke HR, Harten AV, Schuur PC (1998) On a medium term of product recovery and disposal strategy for durable assembly products. Int J Prod Res 36(1):111–139

    Article  MATH  Google Scholar 

  • Kiritsis D, Bufardi A, Xirouuchakis P (2003) Multi-criteria decision aid for product end of life options selections. In: IEEE international symposium on electronics and the environment, pp 48–53. https://doi.org/10.1109/ISEE.2003.1208046

  • Kreng VB, Lee TP (2004a) Modular product design with grouping genetic algorithm: a case study. Comput Ind Eng 46(3):443–460

    Article  Google Scholar 

  • Kreng VB, Lee TP (2004b) QFD-based modular product design with linear integer programming—a case study. J Eng Des 15(3):261–284

    Article  Google Scholar 

  • Lai XX, Gershenson JK (2009) DSM-based product representation for retirement process-based modularity. In: Proceedings of the ASME 2009 international design engineering technical conferences and computers and information in engineering conference, San Diego, CA, Aug. 30–Sep. 2

  • Lee SG, Lye SW, Khoo MK (2001) A multi-objective methodology for evaluating product end-of-life options and disassembly. Int J Adv Manuf Technol 18:148–156

    Article  Google Scholar 

  • Li JZ, Zhang HC, Gonzalez MA, Yu S (2008) A multi-objective fuzzy graph approach for modular formulation considering end of life issues. Int J Prod Res 46(14):4011–4033

    Article  MATH  Google Scholar 

  • Ma J, Kremer GE (2014a) A modular product design approach with key components consideration to improve sustainability. In: Proceedings of the ASME 2014 IDETC conference, Buffalo, NY, Aug. 17–20

  • Ma J, Kremer GE (2014b) A fuzzy logic-based approach for handling uncertain EOL options in product design stage. In: Proceedings of ISERC 2014 conference, Montreal, QC, Canada, May 31–June 3

  • Ma J, Kremer GE (2015) A fuzzy logic-based approach to determine product component end-of-life option from the views of sustainability and designer’s perception. J Clean Prod 108:289–300

    Article  Google Scholar 

  • Ma J, Kremer GE (2016a) A systematic literature review of modular product design (MPD) from the perspective of sustainability. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-015-8290-9

    Google Scholar 

  • Ma J, Kremer GE (2016b) A sustainable modular product design approach with key components and uncertain end-of-life strategy consideration. Int J Adv Manuf Technol 85(1):741–763

    Article  Google Scholar 

  • Mangun D, Thurston DL (2002) Incorporating component reuse, remanufacture and recycle into product portfolio design. IEEE Trans Eng Manag 49(4):479–490

    Article  Google Scholar 

  • Marco P, Eubanks CF, Ishii K (1994) Compatibility analysis of product design for recyclability and reuse. In: Proceedings of the 1994 ASME computers in engineering conference

  • Oberkampf WL, Helton JC, Sentz K (2001) Mathematical representation of uncertainty. American Institute of Aeronautics and Astronautics Non-Deterministic Approaches Forum, Seattle

    Book  Google Scholar 

  • Remery M, Mascle C, Agard B (2012) A new method for evaluating the best product end-of-life strategy during the early design phase. J Eng Des 23(6):419–441

    Article  Google Scholar 

  • Rose CM (2001) Design for environment: a method for formulating product end-of-life strategies. Ph.D. dissertation, Stanford University

  • Singh RK, Kumar S, Choudhury AK, Tiwari MK (2006) Lean tool selection in a die casting unit: a fuzzy-based decision support heuristic. Int J Prod Res 44(7):1399–1429

    Article  Google Scholar 

  • Stevels ALN (1997) Optimization of the end-of-life system. In: Brezet JC, van Hemel C (eds) Appears in ecodesign: a promising approach. UNEP Working Group on Sustainable Product Development, Paris, p 346

    Google Scholar 

  • Teunter RH (2006) Determining optimal disassembly and recovery strategies. Int J Manag Sci 34:533–537

    Google Scholar 

  • Walls M (2006) Extended producer responsibility and product design: economic theory and selected case studies. Resources for the future discussion paper 06-08

  • Yan JH, Feng CH, Cheng K (2012) Sustainability-oriented product modular design using kernel-based fuzzy c-means clustering and genetic algorithm. Proc Inst Mech Eng Part B J Eng Manuf 226(10):1635–1647

    Article  Google Scholar 

  • Yang SL, Li TF (2002) Agility evaluation of mass customization product manufacturing. J Mater Process Technol 129(1–3):640–644

    Article  Google Scholar 

  • Ye Y, Jankovic M, Okudan Kremer GE 2015. Integration of expert estimation uncertainty into supplier identification. ASCE ASME J Risk Uncertain Eng Syst Part P Mech Syst 1(3):031005. https://doi.org/10.1115/1.4030463

    Article  Google Scholar 

  • Ziout A, Azab A, Atwan M (2013) A holistic approach for decision on selection of end-of-life products recovery options. J Clean Prod 65:497–516

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, MS, 39762, USA

    Junfeng Ma

  2. Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA, 50011, USA

    Gül E. Okudan Kremer

  3. Department of Ecosystem Science and Management, The Pennsylvania State University, University Park, PA, 16802, USA

    Charles David Ray

Authors
  1. Junfeng Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gül E. Okudan Kremer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Charles David Ray
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Junfeng Ma.

Appendix

Appendix

See Tables 10, 11 and 12.

Table 10 Refrigerator component EOL strategy environmental impact (mPt)
Full size table
Table 11 Refrigerator component EOL strategy labor time (s)
Full size table
Table 12 Refrigerator component fuzzy evaluation
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ma, J., Kremer, G.E.O. & Ray, C.D. A comprehensive end-of-life strategy decision making approach to handle uncertainty in the product design stage. Res Eng Design 29, 469–487 (2018). https://doi.org/10.1007/s00163-017-0277-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00163-017-0277-0

Keywords

Search

Navigation