An integrated marketing and engineering approach to product line design with consideration of remanufactured products

Abstract

To satisfy the increasingly diversified customer needs, many companies have adopted the product line design (PLD) approach to provide a variety of products for customers. In the PLD approach, both marketing and engineering issues need to be considered. In recent years, an increasing number of companies have offered remanufactured products to customers by remanufacturing their end-of-life and returned products in response to social concerns, the enforcement of regulations on environmental protection, and the increasing potential of green markets. This research aims to investigate the integrated marketing and engineering approach to PLD with consideration of remanufactured products.Remanufactured products are normally produced from returned new products and quite often launched in markets where the new products exist. However, the simultaneous consideration of new and remanufactured products in PLD was not found in previous studies. In addition, the coordination of supply chain parties in performing PLD with consideration of remanufactured products was not addressed. PLD quite often involves market surveys, demand estimation, market segmentation, and market potential estimation. Its solutions can be largely affected by various uncertainties. Two types of uncertainties are studied in this research. The first is the uncertainties associated with market potential estimation and survey data in the development of market demand models that were not properly addressed in previous studies. The second type is the uncertainties about the quantity, timing, and quality of returned products. Determining the optimal quantity and quality of product returns for remanufacturing under uncertain quality and multi-period of returns was likewise not properly addressed in earlier studies. In this research, a methodology for optimal PLD with consideration of remanufactured products is proposed based on an integrated marketing and engineering approach. The proposed methodology can address the abovementioned problems by (1) considering the fuzziness associated with survey data and market potential estimation in the development of market demand models using fuzzy regression and fuzzy estimate generation of market potential, (2) simultaneous consideration of new and remanufactured products in a PLD in centralized and decentralized supply chain networks, and (3) determining the optimal quantity and quality of product returns for remanufacturing under multi-period and uncertain quality of the returns. The proposed methodology mainly involves conducting conjoint surveys, generation of fuzzy market demand models, generation of dynamic demand models for simultaneous consideration of new and remanufactured products in PLD, coordination of closed-loop supply chain for PLD, formulation of multi-objective optimization models and their solutions, as well as determining optimal product returns for remanufacturing. A case study on the PLD of tablet PCs based on the proposed methodology was conducted to illustrate the applicability of the proposed methodology. Three validation tests were performed to evaluate the effectiveness of the proposed methodology. Results of the first test indicated that the profit and market share of a PLD for the maximum profit scenario estimated based on the proposed methodology was better than those estimated based on the methodology with separate consideration of new and remanufactured products. Results of the second test showed that estimated market demand for the normal scenario based on the proposed fuzzy demand model was very close to that based on the multinomial logit model. The third validation test was about the quantity and quality grades of product returns for remanufacturing. The test results indicated that the inventory cost of the returned tablet PCs would cause a 0.5%-1.1% increase in the total cost of the remanufactured tablet PCs, while the uncertainty in the quality of returns would result in 4%-6% change in the total cost.