近二十年來，感性工學系統已經成功應用各種的數學假設模型，解決了消費者導向式產品開發問題。然而，近期全球消費市場急劇成長與暗潮洶湧的競爭，導致開發面在擷取關鍵設計因子的需求倍增。因此，如何幫助設計師快速獲取消費者情感偏好的關鍵內容，並提供設計師更完善的產品特徵之屬性配對，已變成全球設計研究所矚目的焦點之一。約略集為一種應用法則基準擷取關鍵因子的工具與探求屬性間相互關係的方法，約略集可針對人類的感知行為不精確與非線性，提供柔性偏好法則作為評價的基準。然而，在感性工學系統研究當中，在人類感知相關的產品造形設計中，使用約略集合的方式來處理此類問題的研究為數甚少，且約略集融合感性工學系統來探求設計關鍵因子的研究亦是相當罕見。因此，本研究透過論述感性工學與約略集兩者相關的重要架構與概念，並且系統性的剖析感性工學已經成功的數學假設模型與設計相關案例，逐步比對約略集用於感性工學系統的評價方式，藉以探討以約略集方式用於感性工學的模型基礎在產品設計的可行性。本研究最後以實例帶入模型演練方式，評估此方法的模型精準度等各項指標，並以交叉驗證的方式評估所建構的約略集模型在產品設計的可行性。案例一以服裝的外觀為研究，探討產品外觀特徵與情感之間的關係法則，應用約略集方法特性找出關鍵的服裝特徵所對應的情感回饋。案例二則以牙刷的外型與顏色的複合特徵為研究，探討複合特徵中應用約略集所產生的關鍵法則，是否可為產品設計所用，並找出牙刷外型、色彩與人類感知三個維度之間的相互關係，並應用混淆矩陣、交叉驗證、接收者操作特徵分析與曲線下面積等評價與驗證方法來檢視本次實驗的模型好壞與可行性。最後，兩案例的模型皆有良好預測準確能力，在產品設計中可提供讓設計師可讀性高且易懂的設計參照法則。

Recent twenty years, Kansei engineering system (KES) has been successfully employed a variety of mathematical assumption models to overcome the customer-oriented product development problems. However, last few years globalized consumer market has become more competitive than ever in capture the critical design factor, a set of methods how developers can quickly capture consumer affective responses and to provide designers more completed preference information at product features, have become a focus. Rough set theory (RST) as a rule-based critical factor acquisition method, which can be targeted the imprecise and non-linear behavior of the human perception of the reference rules as the basis for evaluation. To the author surprise, in KES researches, especially product form features related to human cognition, RST is still quite rare and has not been specific development combined with KES. Therefore, this study describes important concepts related to KES and RST, and systematically reviewed from the literature which has been successfully applied KES to design related cases, and step by step compared with RST for assessment of the development in KES, in order to reference as a follow-up of KES merging RST. Two case studies brought into model exercises and verified rough set model construction. The first case study in apparel patterns is to explore the relationship between the appearance of the product characteristics and affective responses between rules, the application of the rough set method to identify the critical characteristics of the clothing features corresponding affective responses. The second case with a toothbrush form and color composited characteristics on the critical features in the application of rough sets for rules generated, whether used as product design, and identify toothbrush form, color and human perception of three the relationship between the dimensions and apply confusion matrix, cross-validation, receiver operating characteristic and area under the curve, etc. evaluation and verified capabilities and methods to examine the feasibility of the experimental model. Finally, the study brought into the model training examples and validated the constructed rough set model. Accurate predictive models of the two cases were presented an acceptable predictive ability and provided high readability and comprehensive reference rules.

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