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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers & Industrial Engineering, Volume 63, Issue 4, December 2012, Pages 1030–1037
In response to fast-growing and rapidly-changing markets, launching new products faster than competitors cannot only assist firms in acquiring larger market share but also reducing development lead time, significantly. However, owing to its intrinsically uncertain properties of managing NPD (new product development), manufacturing companies often struggle with the dilemma of increasing product variety or controlling manufacturing complexity. In this study, a fuzzy MCDM (multi-criteria decision making) based QFD (quality function deployment) which integrates fuzzy Delphi, fuzzy DEMATEL (decision making trial and evaluation laboratory), with LIP (linear integer programming) is proposed to assist an enterprise in fulfilling collaborative product design and optimal selection of module mix when aiming at multi-segments. In particular, Fuzzy Delphi is adopted to gather marketing information from invited customers and their assessments of marketing requirements are pooled to reach a consensus; fuzzy DEMATEL is utilized to derive the priorities of technical attributes in a market-oriented manner; and LIP is used to maximize product capability with consideration of supplier’s budget constraints of manufacturing resources. Furthermore, a real case study on developing various types of sport and water digital cameras is demonstrated to validate the proposed approach.
In an era of customer-oriented global economy, dominating the majority market with a single product line becomes very challenging and almost infeasible for most companies (Hsiao & Liu, 2005). Traditionally, to satisfy market majorities, companies considered providing products with high quality, low cost, fast delivery and courteous after-sales service at most. Nowadays, owing to fiercely competitive environments and rapidly changing demand, the capability and the speed of developing niche products and launching them into the niche segments gradually dominate the competition paradigm, particularly when a transition has been shifting from “supply push” to “demand pull” (Jiao, Ma, & Tseng, 2003). To put it another way, “mass customization” embarks a new paradigm for modern manufacturing industries since it treats each customer as an individual and attempts to provide “tailor-made” featured products that was only offered in the pre-industrial “craft” era. Over the past two decades, numerous publications originated from different disciplines have witnessed in the field of customer requirement management (Jiao & Chen, 2006). For example, various fields such as marketing research, consumer behavior, collaborative design, and concurrent engineering, attempt to contribute to different stages for new product development (NPD). Among them, marketing research and consumer behavior emphasize the front issues relevant to collecting the information of customer preference via specific channels. In contrast, collaborative design and concurrent engineering focus on utilizing a systematic and parallel approach for integrating a wide spectrum of product design and related manufacturing processes (Lin, Wang, Chen, & Chang, 2008). Although high product variety does stimulate product sales, companies still inevitably face the trade-offs between the diversity of customer needs and numerous adverse effects, such as larger inventory cost, longer cycle time and expensive research investment. As a result, it is very imperative for companies to keep high flexibility while incurring limited manufacturing cost, concurrently. In practice, two common techniques have been proposed to tackle the above-mentioned issue, including product family architecture (Jiao and Tseng, 1999 and Moon et al., 2010) and modular product or product family design (Hsiao and Liu, 2005 and Kreng and Lee, 2004). Modular product design offers a feasible way by developing a product architecture, in which physical relationships across modules are limited while functional relationships among components within a module are coherent. Furthermore, product family design based on a standard platform usually provides a cost-effective way to develop highly related but differentiated products. By sharing/reusing physical manufacturing resources and intangible human capitals, companies can efficiently balance the benefit and cost for NPD. Based on previous studies, most of them are deficient in constructing a systematic approach to assist companies in achieving mass customization while keeping reasonable manufacturing cost. In this study, a fuzzy MCDM based QFD (quality function deployment) is proposed to fulfill collaborative product design and optimal selection of module mixes when aiming at multi-segments. Moreover, this paper contributes to this domain by presenting the following merits: • QFD provides a communication platform to gather different opinions between industrial experts and even among customer individuals. • QFD is capable to transform intangible marketing requirements (MRs) into measurable technical attributes (TAs) and to accommodate the dependences between MRs and TAs and the correlations among themselves. • In additional to deriving the weights of MRs and TAs, the proposed fuzzy MCDM based QFD could further identify the optimal module mix (product variety) for a specific market segment. The remaining of this paper is organized as follows. Section 2 overviews the related works and Section 3 introduces the proposed framework which integrates fuzzy Delphi, fuzzy DEMATEL with LIP (linear integer programming). A real example regarding collaborative design for various sport and water digital cameras is illustrated in Section 4. Conclusions are drawn in Section 5.
نتیجه گیری انگلیسی
In the era of global customization, to survive in a wide range of market segments, companies need to balance the trade-offs between enhancing product varieties and controlling manufacturing complexity. Consequently, numerous paradigms have received much attention, including product family architecture, platform-based development, and modular product design. In this paper, a fuzzy MCDM based QFD which integrates fuzzy Delphi, fuzzy DEMATEL, with LIP is presented to accomplish two fundamental tasks of NPD: collaborative product design and optimal selection of module mix with respect to distinct multi-segments. More importantly, this paper demonstrates the following merits: • To reduce the gap between customer needs and product development, this study is capable to gather opinions between individual customers and industrial experts and then fuse their assessments to reach a consensus. • To understand the causal impacts of marketing requirements on technical attributes, this study could visualize their complicated interrelationships and derive the priorities of technical attributes in a market-oriented manner. • To assist an enterprise in optimizing product varieties with respect to multi-segments, this study utilizes linear integer programming to maximize product capability with consideration of budget constraints on manufacturing costs, concurrently. For simplification, this study assumes that the entire market is partitioned into three segments which are based on the pricing policy of an enterprise. Future study might extend our current framework to a more general scenario in which market segmentation is based on customer preference. In addition, other classical techniques like conjoint analysis (Luce & Tukey, 1964) or Kano model (1984) might be further incorporated into the proposed framework to fulfill sufficient customer involvement.