近年來冷水壺產品以使用者為意念導向為設計日益提升，要能引發消費者的消費動機，產品意象則是觸發購買行為的第一要素。本研究藉由感性工學，運用數量化I類統計探討產品造型與消費者之間巧妙關係，進而使設計師能有效的理解產品特徵與消費者感受間的關聯，成為設計師數據資產。
本研究透過大量蒐集冷水壺樣本，借重專家訪談與問卷調查，篩選出20項冷水壺與10組形容詞語彙進行消費者與產品意象關聯分析，根據冷水壺造型特徵拆解出6項型態要素，再進行20項冷水壺特徵編碼。運用數量化I類，歸納語彙與冷水壺特徵之關聯性。根據分析結果，找出10組語彙偏相關係數最高之型態要素項目，再邀請設計系學生進行3D模型建構，繪製出10項樣本進行DFM評估。其DFM評估目的希望讓設計師能快速了解產品在注塑成型製造時，會面臨不良之原因，藉由模流分析軟體來預判產品之「充填平衡」、「表面凹痕」、「縫合線」、「包封位置」、「翹曲變形」等瑕疵。最後再透過10項樣本，尋找出「好製造產品」、「具美觀實用產品」、「好製造又具美觀實用產品」分類的產品。本研究結果發現樣品6與9為好製造又具美觀實用產品，其中樣品6以72%以上得分為具美觀實用性最高的產品，也呼應運用數量化一類分析而繪製「裝飾的-實用的」形容詞語彙之型態要素設計。
本研究希望從前端產品設計與後端製造生產能有完整的銜接，讓未來新進設計師能理解製造端的考量，藉此在產品設計階段能把其納入評估，讓新進設計師能比同行更能具有製造概念與設計實力，成為成功的工匠師。

In the dilemma of market competition, design is the first step in manufacturing, and it is where most of the important decisions are made that affect the final cost of a product. In recent years, the design of cold water jugs products has been increasingly oriented to the user-oriented idea. To be able to trigger consumer motivation, the image of the product is the first element of triggering behavior. In this study, through the use of Kansei Engineering, the ingenious relationship between QTI statistical product modeling and consumers has enabled designers to effectively understand the relationship between product features and consumer perceptions, becoming the designer's largest data asset.
In this study, we collected a large number of cold water jugs samples, relied on expert interviews and questionnaires, and screened out 20 cold water jugs and 10 sets of adjectives to analyze the relationship between consumers and product images, and disassembled 6 form factors based on the characteristics of cold water jugs. Then carry out 20 cold water jugs feature coding. Using QTI, summarize the relevance of vocabulary and the characteristics of cold water jugs. According to the analysis results, 10 groups of morphological element items with the highest vocabulary partial correlation coefficients were identified, and then design students were invited to construct 3D models, and 10 samples were drawn for DFM evaluation. The purpose of the DFM evaluation is to allow designers to quickly understand the causes of defects when products are manufactured by injection molding, and use mold-flow analysis software to predict the "Filling balance", "Sink mark", and "Suture lines" of the product, "Sleepy position", "Warpage deformation" and other defects. Finally, through 10 samples, we can find products in the categories of "good manufacturing products", "beautiful and practical products", and "good manufacturing and beautiful and practical products". The results of this study found that samples 6 and 9 are good for manufacturing and beautiful and practical products. Among them, sample 6 scored more than 72% as the most beautiful and practical product. It also echoes the use of quantitative analysis to draw "decorative-practical" The design of the form element of the descriptive vocabulary. This research hopes to have a complete connection between front-end product design and back-end manufacturing, so that future novel designers can understand the considerations on the manufacturing side, so that they can be included in the evaluation during the product design stage, so that designers can be better than their peers. With manufacturing concept and solidified strength, he has become a highly anticipated craftsman.

Afeyan, N. B., Malek, K. M., Bufton, N. J., Ficici, S. G., & Austin, H. A. (2010). Method for iterative design of products. In: Google Patents.
Anderson, D. M. (2014). Design for manufacturability: how to use concurrent engineering to rapidly develop low-cost, high-quality products for lean production: Productivity Press.
Atwood, M. E., & Polson, P. G. (1976). A process model for water jug problems. Cognitive Psychology, 8(2), 191-216.
Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49-59. doi:https://doi.org/10.1016/0005-7916(94)90063-9
Chang, Y.-M., & Chen, C.-W. (2016). Kansei assessment of the constituent elements and the overall interrelations in car steering wheel design. International Journal of Industrial Ergonomics, 56, 97-105. doi:https://doi.org/10.1016/j.ergon.2016.09.010
Chin, S., & Kim, K.-Y. (2010). Facial configuration and BMI based personalized face and upper body modeling for customer-oriented wearable product design. Computers in Industry, 61(6), 559-575. doi:https://doi.org/10.1016/j.compind.2010.03.006
Chou, J.-R. (2016). A Kansei evaluation approach based on the technique of computing with words. Advanced Engineering Informatics, 30(1), 1-15. doi:https://doi.org/10.1016/j.aei.2015.11.001
Friborg, O., Martinussen, M., & Rosenvinge, J. H. (2006). Likert-based vs. semantic differential-based scorings of positive psychological constructs: A psychometric comparison of two versions of a scale measuring resilience. Personality and Individual Differences, 40(5), 873-884. doi:https://doi.org/10.1016/j.paid.2005.08.015
Fu, J., & Ma, Y. (2019). A method to predict early-ejected plastic part air-cooling behavior towards quality mold design and less molding cycle time. Robotics and Computer-Integrated Manufacturing, 56, 66-74. doi:https://doi.org/10.1016/j.rcim.2018.08.004
Günay, K. A., Theato, P., & Klok, H. A. (2013). Standing on the shoulders of Hermann Staudinger: Post‐polymerization modification from past to present. Journal of Polymer Science Part A: Polymer Chemistry, 51(1), 1-28.
Guart, A., Wagner, M., Mezquida, A., Lacorte, S., Oehlmann, J., & Borrell, A. (2013). Migration of plasticisers from Tritan™ and polycarbonate bottles and toxicological evaluation. Food Chemistry, 141(1), 373-380. doi:https://doi.org/10.1016/j.foodchem.2013.02.129
Hayashi, C. (1951). On the prediction of phenomena from qualitative data and the quantification of qualitative data from the mathematico-statistical point of view. Annals of the institute of statistical mathematics, 3(1), 69-98.
Horiguchi, A., & Suetomi, T. (1995). A Kansei Engineering approach to a driver/vehicle system. International Journal of Industrial Ergonomics, 15(1), 25-37. doi:https://doi.org/10.1016/0169-8141(94)00054-7
Hsiao, S.-W., Chiu, F.-Y., & Lu, S.-H. (2010). Product-form design model based on genetic algorithms. International Journal of Industrial Ergonomics, 40(3), 237-246. doi:https://doi.org/10.1016/j.ergon.2010.01.009
Hsu, S. H., Chuang, M. C., & Chang, C. C. (2000). A semantic differential study of designers’ and users’ product form perception. International Journal of Industrial Ergonomics, 25(4), 375-391. doi:https://doi.org/10.1016/S0169-8141(99)00026-8
Jiao, Y., & Qu, Q.-X. (2019). A proposal for Kansei knowledge extraction method based on natural language processing technology and online product reviews. Computers in Industry, 108, 1-11. doi:https://doi.org/10.1016/j.compind.2019.02.011
Kim, W., Ko, T., Rhiu, I., & Yun, M. H. (2019). Mining affective experience for a kansei design study on a recliner. Applied ergonomics, 74, 145-153. doi:https://doi.org/10.1016/j.apergo.2018.08.014
Lee, B., Parks, D., & Ahzi, S. (1993). Micromechanical modeling of large plastic deformation and texture evolution in semi-crystalline polymers. Journal of the Mechanics and Physics of Solids, 41(10), 1651-1687.
Lee, S., Harada, A., & Stappers, P. J. (2002). Pleasure with products: Design based on Kansei. Pleasure with products: Beyond usability, 219-229.
Li, Z., Tian, Z., Wang, J., Wang, W., & Huang, G. (2018). Dynamic mapping of design elements and affective responses: a machine learning based method for affective design. Journal of Engineering Design, 29(7), 358-380.
Lin, C.-T., Wu, W.-J., & Cheng, L.-M. (2015). Towards understanding integration of heavyweight-product managers and collaboration software in collaborative product development: An empirical study in Taiwan. Technological Forecasting and Social Change, 99, 156-167. doi:https://doi.org/10.1016/j.techfore.2015.06.030
Llinares, C., & Page, A. F. (2011). Kano’s model in Kansei Engineering to evaluate subjective real estate consumer preferences. International Journal of Industrial Ergonomics, 41(3), 233-246. doi:https://doi.org/10.1016/j.ergon.2011.01.011
Maleki, S., Amiri Aghdaie, S. F., Shahin, A., & Ansari, A. (2019). Investigating the relationship among the Kansei-based design of chocolate packaging, consumer perception, and willingness to buy. Journal of Marketing Communications, 1-20.
Massy, J. (2017). The Burgeoning of Modern Plastics. In A Little Book about BIG Chemistry (pp. 27-27): Springer.
Merton, R. K. (1987). The focussed interview and focus groups: Continuities and discontinuities. The Public opinion quarterly, 51(4), 550-566.
Misaka, M., & Aoyama, H. (2018). Development of design system for crack patterns on cup surface based on KANSEI. Journal of Computational Design and Engineering, 5(4), 435-441. doi:https://doi.org/10.1016/j.jcde.2017.12.008
Nagamachi, M. (1995). Kansei Engineering: A new ergonomic consumer-oriented technology for product development. International Journal of Industrial Ergonomics, 15(1), 3-11. doi:https://doi.org/10.1016/0169-8141(94)00052-5
Nelson, A. M., & Long, T. E. (2012). A perspective on emerging polymer technologies for bisphenol‐A replacement. Polymer International, 61(10), 1485-1491.
O’Driscoll, M. (2002). Design for manufacture. Journal of Materials Processing Technology, 122(2-3), 318-321.
Osgood, C. E. (1964). Semantic differential technique in the comparative study of cultures 1. American Anthropologist, 66(3), 171-200.
Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning: University of Illinois press.
Ries, E. (2011). The lean startup: How today's entrepreneurs use continuous innovation to create radically successful businesses: Crown Books.
Schütte, S. (2005). Engineering emotional values in product design: Kansei engineering in development. Institutionen för konstruktions-och produktionsteknik,
Schütte, S., & Eklund, J. (2005). Design of rocker switches for work-vehicles—an application of Kansei Engineering. Applied ergonomics, 36(5), 557-567. doi:https://doi.org/10.1016/j.apergo.2005.02.002
Schütte, S. T., Eklund, J., Axelsson, J. R., & Nagamachi, M. (2004). Concepts, methods and tools in Kansei engineering. Theoretical Issues in Ergonomics Science, 5(3), 214-231.
Shimizu, Y. (2004). On‐demand production system of apparel on the basis of Kansei engineering. International Journal of Clothing Science and Technology, 16(1/2), 32-42. doi:10.1108/09556220410520333
Sinnwell, C., Krenkel, N., & Aurich, J. C. (2019). Conceptual manufacturing system design based on early product information. CIRP Annals, 68(1), 121-124. doi:https://doi.org/10.1016/j.cirp.2019.04.031
Takasu, N. (2003). Friction welding of plastics. Welding international, 17(11), 856-859.
Thompson, R. C., Swan, S. H., Moore, C. J., & Vom Saal, F. S. (2009). Our plastic age. In: The Royal Society Publishing.
Vieira, J., Osório, J. M. A., Mouta, S., Delgado, P., Portinha, A., Meireles, J. F., & Santos, J. A. (2017). Kansei engineering as a tool for the design of in-vehicle rubber keypads. Applied ergonomics, 61, 1-11. doi:https://doi.org/10.1016/j.apergo.2016.12.019
Wang, W. M., Li, Z., Tian, Z. G., Wang, J. W., & Cheng, M. N. (2018). Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach. Engineering Applications of Artificial Intelligence, 73, 149-162. doi:https://doi.org/10.1016/j.engappai.2018.05.005
Wheelwright, S. C., & Clark, K. B. (1992). Revolutionizing product development: quantum leaps in speed, efficiency, and quality: Simon and Schuster.
Yan, H.-B., Huynh, V.-N., Murai, T., & Nakamori, Y. (2008). Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis. Information Sciences, 178(21), 4080-4093. doi:https://doi.org/10.1016/j.ins.2008.06.023
王肇儀. (2008). 感性工學為基礎之人工表情分析. 中央大學, Available from Airiti AiritiLibrary database. (2008年)
何裕安. (2016). 感性工學運用於工業用 LED 頭燈產品設計之研究. 成功大學工業設計學系學位論文, 1-93.
呂旭弘. (2003). 應用感性工學與基因遺傳演算法於產品造形設計. 成功大學工業設計學系學位論文, 1-113.
郝永平, 王崇海, 寧汝新, & 劉永賢. (2002). 基於協同環境下的衝突管理機制研究. [Research on Mechanism of Conflict Management in Collaborative Environment]. 計算機集成製造系統, 8(4), 299-302.
莊明振, & 陳俊智. (2009). 產品形態特徵與構成關係影響消費者感性評價之研究─ 以水壺的設計為例. 設計學報 (Journal of Design), 9(3).
曾清旗. (2003). 銀行企業品牌商標感性語彙意象認知與設計決策建構之研究. 成功大學, Available from Airiti AiritiLibrary database. (2003年)