| 研究生: |
李狄學 Li, Di-Xue |
|---|---|
| 論文名稱: |
精實思維導入運動眼鏡設計流程之改善研究 A Study on Applying Lean Thinking to Improve the Sports Eyewear Design Process |
| 指導教授: |
洪郁修
Hung, Yu-Hsiu |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 工業設計學系 Department of Industrial Design |
| 論文出版年: | 2026 |
| 畢業學年度: | 114 |
| 語文別: | 中文 |
| 論文頁數: | 124 |
| 中文關鍵詞: | 精實思維 、精實研發 、價值流程圖 、流程改善 |
| 外文關鍵詞: | Lean Thinking, Lean Product and Process Development (LPPD), Value Stream Mapping (VSM), Process Improvement |
| 相關次數: | 點閱:4 下載:0 |
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台灣運動眼鏡產業長期以 OEM與ODM 代工模式為主,其產品開發特徵在於需同時兼顧精密光學功能、嚴格防護安規與流行時尚美學,流程複雜度極高。然而,此產業之傳統研發模式普遍面臨「知識孤島」與「高度依賴隱性經驗」之結構性困境,導致設計端與製造端存在嚴重的資訊不對稱。此種缺乏系統性整合的流程,常迫使關鍵工程問題延後至高成本的開模試產階段才被發現,造成反覆修模、重工與交期延宕,已成為該產業在面對全球競爭時,轉型與價值提升的主要瓶頸。
本研究旨在探討傳統研發模式面臨之結構性挑戰,並建構一套適用於 ODM 轉型之「精實研發 (LPPD) 改善模式」。其核心目的在於釐清如何將「精實思維」之應用範疇由生產現場延伸至研發前端,將過往依賴個人經驗的作業模式,轉化為系統化的知識流動體系,藉以解決設計與製造間的知識斷層問題。
實證推動上,選定一家具垂直整合能力的運動眼鏡企業為場域,採用行動研究法「診斷、對策、驗證」之邏輯框架展開:首先運用「價值流程圖」將無形的研發資訊流視覺化,精準識別出流程中資訊斷點與非加值浪費。再針對識別之瓶頸,導入以「知識顯性化」與「風險前置」為核心之精實策略。具體實施機制包含:
(1) 建立跨部門大部屋 (Obeya) 機制,同步整合設計與工程資訊;
(2) 導入快速原型 (RP) 驗證與設計查檢表,將下游模具限制提前至設計階段解決;
(3) 推動總工程師 (Chief Engineer) 職能概念,強化跨單位的專案協調力。
研究結果顯示,透過上述精實機制之導入,個案公司之開發前置時間顯著縮短 45.8%(由 192 天降至 104 天),關鍵重工迴圈次數由平均 7 次降至 3 次,大幅提升了設計變更的決策品質。本研究證實,精實思維不僅適用於製造現場,更能有效診斷並改善研發階段的知識流動效率。所提出之「價值流診斷-知識整合-風險前置」改善框架,可作為相關 ODM 產業優化研發體質、降低試錯成本之具體參考模型。
Taiwan’s sports eyewear industry predominantly operates under OEM and ODM models. Its product development is characterized by high complexity, requiring the simultaneous integration of precision optical functions, stringent safety regulations, and fashion aesthetics. However, traditional R&D models in this industry often face structural dilemmas characterized by "knowledge silos" and a high reliance on "tacit knowledge," leading to severe information asymmetry between design and manufacturing. This lack of systematic integration frequently forces critical engineering issues to be postponed until the high-cost tooling and pilot production stages. Consequently, iterative mold modifications, rework, and schedule delays have become major bottlenecks for the industry in its pursuit of transformation and value enhancement amidst global competition.
To address these structural challenges, this study aims to construct a "Lean Product and Process Development (LPPD) Improvement Model" suitable for ODM transformation. The core objective is to clarify how to extend the application of "Lean Thinking" from the production floor to the front-end R&D stage, transforming traditional experience-based operations into a systematic knowledge flow system to bridge the knowledge gap between design and manufacturing.
In terms of empirical implementation, a vertically integrated sports eyewear company was selected as the research field. Adopting Action Research, the study followed a logical framework of "Diagnosis, Countermeasure, and Verification." First, Value Stream Mapping (VSM) was utilized to visualize the intangible R&D information flow, precisely identifying information disconnects and non-value-added (NVA) waste within the process. Subsequently, aiming at the identified bottlenecks, Lean strategies centered on "Knowledge Explication" and "Front-loading" were introduced. Specific implementation mechanisms included: (1) establishing a cross-functional "Obeya" (Big Room) mechanism to synchronize design and engineering information; (2) introducing Rapid Prototyping (RP) verification and design checklists to resolve downstream tooling constraints during the design phase; and (3) promoting the "Chief Engineer" concept to strengthen cross-unit project coordination.
The research results indicate that through the introduction of these Lean mechanisms, the case company’s development lead time was significantly reduced by 45.8% (from 192 days to 104 days), and critical rework loops decreased from an average of 7 to 3, substantially improving the decision-making quality of design changes. This study confirms that Lean Thinking is not only applicable to manufacturing sites but is also effective in diagnosing and improving knowledge flow efficiency in the R&D stage. The proposed "Value Stream Diagnosis – Knowledge Integration – Front-loading" improvement framework serves as a concrete reference model for related ODM industries to optimize R&D constitution and reduce trial-and-error costs.
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