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Research Papers

Maximizing Profits From End-of-Life and Initial Sales With Heterogeneous Consumer Demand

[+] Author and Article Information
Yuan Zhao

Graduate Research Assistant
e-mail: yzhao21@illinois.edu

Deborah Thurston

Fellow, ASME
e-mail: thurston@illinois.edu
Industrial and Enterprise Systems
Engineering Department,
University of Illinois at Urbana-Champaign,
Urbana, IL 61801

Contributed by the Design Automation Committee of ASME for publication in the Journal of Mechanical Design. Manuscript received December 12, 2011; final manuscript received October 26, 2012; published online February 20, 2013. Assoc. Editor: Wei Chen.

J. Mech. Des 135(4), 041001 (Feb 20, 2013) (10 pages) Paper No: MD-11-1506; doi: 10.1115/1.4023154 History: Received December 12, 2011; Revised October 26, 2012

Growing concerns from customers and the government about product disposal highlight the necessity of improving product take-back systems to retain the embedded values in disposed products. Progress has been made toward minimizing the cost of the end-of-life (EOL) processes. While some progress has been made in recovering end-of-life value through decision making in the early design stage, contradictive objectives make it difficult to simultaneously optimize initial sales profits and EOL value. In this paper, a mathematical model is developed to integrate end-of-life recovery value considerations with product design decisions. The improvement of component reuse value or recycling value is achieved by linking design decisions in the early design stage with end-of-life decisions in order to maximize total product value across the span of product life cycle. A matrix based representation that can group components into several end-of-life modules with the same end-of-life decisions is also presented. The results are discussed to compare different design alternatives to understand their influence on net present product lifecycle value. The original contribution here is the simultaneous consideration of profits from initial and returned product sales, resulting from consumer demand as a function of heterogeneous preferences for the product attribute set. In order to estimate consumer demand resulting from discrete choices made by individuals, a random coefficient, mixed logit model was employed. The proposed method is illustrated through a cell phone example of product design decisions and end-of-life strategies.

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Figures

Grahic Jump Location
Fig. 1

End-of-life module disassembly matrix

Grahic Jump Location
Fig. 2

Disassembly time in initial product structure matrix

Grahic Jump Location
Fig. 3

Disassembly module in disassembly matrix for the cell phone case study

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