Date of Award

August 2016

Degree Type

Thesis

Degree Name

Master of Science

Department

Engineering

First Advisor

Wilkistar Otieno

Committee Members

Jaejin Jang, Benjamin Church

Keywords

Fuzzy, Remanufacturing, Topsis

Abstract

While the average life cycle of consumer goods is continuously decreasing, the amount of used product at their end-of-life (EOL) is accumulating fast at and at the same pace. Most EOL products end up in landfills, and many of which are not biodegradable. These two challenges have necessitated renewed global interest in product EOL management strategies by manufacturers, third party companies, consumers and governments. Remanufacturing is one of the EOL strategies which is highly environmental-friendly. Additionally, remanufacturing is seen as one of the highly profitable re-use business strategies. The selling price of remanufactured products is usually about 50—80% of a new one, making remanufacturing a win—win solution, saving both money and preserving the environment as well as raising the bottom-line of enterprises.

Through the literature review of remanufacturing, we realize many researchers in this area have focused on a few product categories such as automotive, electrical and electronic equipment as well as ink cartridge, thus accelerating innovations for the remanufacture of these product categories. There is therefore, a need to explore the remanufaturability of other products, especially the ones with high market potential growth as well as profit margin. Furniture industry is the one that fits the description and is the focus of this thesis.

The goal of this exploratory research is to present the first framework of its kind that aims at assessing the remanufacturability of office furniture. The proposed evaluation model considers three aspects of the assessment problem: economic, social and environmental to obtain a holistic view of remanufacturability of office furniture. We apply the fuzzy TOPSIS methodology to deal with incomplete and often subjective information during the evaluation.

Furthermore, we validate our evaluation model using published research data for a multi-criteria allocation decision making (MCDM) problem. Through the model validation, we show that the proposed evaluation model has the capability to solve MCDM problems. Lastly, a case study which involves three pieces of office furniture is used to illustrate the function of the proposed model.

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