以顧客需求為導向之產品技術開發規劃策略方法論

A Methodology for Creating a Customer Demand-Oriented Product Technology Development Planning Strategy

陳建宏(Jian-Hong Chen)

指導教授 ： 車振華

國立臺北科技大學/管理學院/工業工程與管理系碩士班/碩士(2013年)

摘要

近年來消費性電子產品競爭激烈，且消費者意識抬頭，因此，若企業無法開發出滿足顧客需求之創新產品技術，將面臨企業虧損與市占率下降之窘境。因此，本研究將發展以顧客需求為導向之產品技術開發規劃策略方法論。該方法論使用層級分析法與品質機能展開，分析每項顧客需求項目之相對重要性，以及顧客需求項目對應關鍵技術之關係程度，進而協助企業分析每項關鍵技術滿足顧客需求的程度。接著，透過專利資料與關鍵技術生命週期辨識模式，以了解關鍵技術之生命週期階段，並判定關鍵技術可取得方式。隨後，本研究建立多目標產品技術開發規劃策略評估模式，分析不同的產品技術開發規劃策略之績效。為協助企業擬定的產品技術開發規劃策略，因此，本研究運用多目標基因演算法，以找出在產品開發時間之限制條件下，最高顧客滿意度與最低的產品開發成本之最佳化產品技術開發規劃策略。最後，本研究使用綠色智慧型手機開發為案例說明與驗證本方法論之實務上的貢獻。

關鍵字

多目標基因演算法 ； 技術生命週期階段 ； 產品技術開發規劃 ； 品質機能展開

並列摘要

In recent years, due to the highly competitive marketplace for consumer electronics products and the increase in consumer consciousness, if a company cannot develop innovative product-technology to meet customer demands, enterprises will face the dilemma of decreasing market share and even making a loss. Therefore, this study develops a methodology for creating a customer demand-oriented product-technology development planning strategy. The proposed methodology uses AHP (Analytical Hierarchical Process) and QFD (Quality Function Deployment) to analyze the relative importance of each customer demand and the corresponding relationships between key technologies and customer demands, and then to further help a company analyze the satisfactory levels that each key technology meets the customer demand items. Next, through an identification model of key technology life cycles to understand the life cycle stage of each key technology and to determine the way of obtaining critical technologies. Subsequently, this research creates a multi-objective evaluation model of product-technology development planning strategies to analyze the performance of different product-technology development planning strategies. To help a company establish the product-technology development planning strategy, this study applies a multi-objective genetic algorithm to find the optimal product-technology development planning strategy with the maximum customer satisfaction level and the minimum product development cost. Finally, this study uses green smartphone development as a case study to explain and verify the practical contributions of the proposed methodology.

並列關鍵字

multi-objective genetic algorithms (MOGA) ； technology life cycle ； product-technology development planning ； quality function deployment (QFD)

參考文獻

[1] A. Kengpol and C. O’Brien, “The development of a decision support tool for the selection of advanced technology to achieve rapid product development,” Journal of Production Economics, vol. 69, no. 2, 2001, pp. 177-191.

[2] A. Halog, F. Schultmann and O. Rentz, “Using quality function deployment for technique selection for optimum environmental performance improvement,” Journal of Cleaner Production, vol. 9, no. 5, 2001, pp. 387-394.

[3] B. Almannai, R. Greenough and J. Kay, “A decision support tool based on QFD and FMEA for the selection of manufacturing automation technologies,” Journal of Robotics and Computer-Integrated Manufacturing, vol. 24, no. 4, 2008, pp. 501-507.

[4] B. Nepal, O. P. Yadav and A. Murat “A fuzzy-AHP approach to prioritization of CS attributes in target planning for automotive product development,” Journal of Expert Systems with Applications, vol. 37, no. 10, 2010, pp. 6775-6786.

[5] C. P. Blocker and D. J. Flint, “Customer segments as moving targets: integrating customer value dynamism into segment instability logic,” Journal of Industrial Marketing Management, vol. 36, no. 6, 2007, pp. 810-822.