新產品開發是企業競爭力的一項重要指標。隨著技術創新以及生產力提升，客戶對於新產品的要求越趨嚴苛。許多企業認為研發能力與產品的創新，為企業維持競爭力的關鍵。隨著消費者意識之抬頭，「滿足顧客需求」遂成為企業所追求之目標。 全球工業電腦產業的競爭越趨激烈。現今科技追求處理速度越來越快，工業用電腦也開始有了巨大的改變，從先前人力為主的生產系統，漸漸走進自動化及智能化生產，為了確保市場競爭力，工業電腦如何提高生產效率、降低製造成本，成為了現今工業電腦製造商所面臨的最大挑戰以及成功的關鍵因素。 本研究為了確保產品開發設計階段的品質符合顧客要求，利用協同設計概念，使產品設計能與市場需求變化保持一致， 因此透過品質機能展開(Quality Function Deployment, QFD)分析消費者對產品之需求與產品設計之間的關係，並藉由模組化的設計概念，以設計結構矩陣(Design Structure Matrix, DSM)，進行零件模組之分群，達成模組最佳化之效益，再進一步藉由此方法之交互作用結果，完成工業電腦中之兩兩比較 的零件模組收斂，找出最符合產品的分群方式。;New product development is an important indicator of corporate competitiveness. With technological innovation and increased productivity, customer requirements for new products are becoming more stringent. Many companies believe that R & D capabilities and product innovation are key to maintaining competition. As consumer sentiment rises, "To meet customer demand" has become the goal pursued by enterprises Customer requests. Competition between the global industrial computer industry is becoming increasingly fierce. Nowadays, the pursuit of processing speed is getting faster and faster , and industrial computers have begun to change dramatically. From the previous human-based production system, it gradually entered the automation and intelligent production. To ensure market competitiveness, How industrial computers improve production efficiency and reduce manufacturing costs has become the biggest challenge and a key factor for success for today′s industrial computer manufacturers. In order to ensure that the quality of the product development and design phase meets customer requirements, this study uses the concept of collaborative design to make product design consistent with changes in market demand. Therefore, the relationship between consumer demand for products and product design was analyzed through Quality Function Deployment (QFD). With modular design overview, design structure matrix (Design Structure Matrix, DSM) is used to group the module modules to achieve the benefits of module optimization. Further, the interaction results of this method are used to complete the comparison of the software module convergence in the industrial computer, and to find the clustering method that best matches the product.
