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Research Papers

Uncertainty Management in Remanufacturing Decisions: A Consideration of Uncertainties in Market Demand, Quantity, and Quality of Returns

[+] Author and Article Information
A. Raihanian Mashhadi

Mechanical and Aerospace Engineering Department, University at Buffalo, SUNY, Buffalo, NY 14260-1660

Behzad Esmaeilian

Mechanical and Industrial Engineering Department, Northeastern University, Boston, MA 02115

Sara Behdad

Mechanical and Aerospace Engineering Department;Industrial and Systems Engineering Department, University at Buffalo, SUNY, Buffalo, NY 14260-1660

Manuscript received September 28, 2014; final manuscript received February 3, 2015; published online April 20, 2015. Assoc. Editor: Athanasios Pantelous.

ASME J. Risk Uncertainty Part B 1(2), 021007 (Apr 20, 2015) (8 pages) Paper No: RISK-14-1063; doi: 10.1115/1.4029759 History: Received September 28, 2014; Accepted February 05, 2015; Online April 20, 2015

As market demand for remanufactured products increases and environmental legislation puts further enforcement on original equipment manufacturers (OEMs), remanufacturing is becoming an important business. However, profitability of salvaging operations is still a challenge in remanufacturing industry. Several factors influence the cost effectiveness of remanufacturing operations, including uncertainties in the quantity of return flows and market demand as well as variability in the quality of received items. The objective of this paper is to develop a stochastic optimization model based on chance-constrained programming to deal with these sources of uncertainties in take-back and inventory planning systems. The main purpose of the model is to determine the best upgrade level for a received product with certain quality level with the aim of maximizing profit. An example of personal computer is provided to show the application of the method.

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Figures

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Fig. 1

The upgrade planning process

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Fig. 2

Distribution of electronic products received for remanufacturing by PCRR in 2010; the majority of returns were personal computers

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Fig. 3

Upgrade strategy versus standard deviation of market demand for grade 2 products

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Fig. 4

Profit versus standard deviation of market demand for grade 2 products

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Fig. 5

Upgrade strategy versus standard deviation of incoming grade 2 products

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Fig. 6

Profit versus standard deviation of incoming grade 2 products

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