【摘要】：在競爭日益激烈的國際市場和供大于求的國內(nèi)市場現(xiàn)狀下,機械行業(yè)面臨著許多挑戰(zhàn),如何設(shè)計和生產(chǎn)出滿足用戶需求的產(chǎn)品,獲得良好的市場反饋是設(shè)計師和生產(chǎn)商面臨的永久挑戰(zhàn)。用戶不僅要求產(chǎn)品功能齊全,也希望產(chǎn)品具有情感。如何快速、準(zhǔn)確的提取用戶的情感需求是提高產(chǎn)品競爭力的關(guān)鍵所在,于是能夠有效提取情感需求的感性工學(xué)研究,受到了國內(nèi)外專家學(xué)者的廣泛關(guān)注,并成為研究熱點。 本研究在感性工學(xué)的研究框架內(nèi),挖掘了用戶和設(shè)計師對于產(chǎn)品造型產(chǎn)生的情感意象,提出了基于粗糙集理論的產(chǎn)品造型要素的辨識方法,并基于目標(biāo)情感意象提取出個性要素與平臺要素,以此指導(dǎo)產(chǎn)品定位,從而使得出的造型方案能夠同時滿足用戶和設(shè)計師的需求。 本研究包含三個階段,研究內(nèi)容以及取得的研究成果如下：第一階段研究了情感意象挖掘方法及其技術(shù)流程,并以折彎機為研究實例,運用SD調(diào)查問卷調(diào)查設(shè)計師和終端用戶,得出兩者的情感意象尺度評價表。第二階段基于粗糙集理論提出了一種符合設(shè)計師和終端用戶目標(biāo)情感意象的造型要素辨識方法,首先,在產(chǎn)品情感意象調(diào)查基礎(chǔ)上,通過盲目刪除屬性約簡方法,提取個性要素與平臺因素；然后將個性要素針對情感意象進(jìn)行排序,分析設(shè)計師與終端用戶間的認(rèn)知差異,辨識出同時符合兩者目標(biāo)情感意象的造型要素,用于產(chǎn)品定位。第三階段將現(xiàn)有產(chǎn)品定位方法和基于粗糙集的造型要素辨識方法相結(jié)合,以此重塑折彎機造型,并對設(shè)計方案進(jìn)行驗證分析。結(jié)果表明該方法對于快速、準(zhǔn)確的完成產(chǎn)品定位和溝通設(shè)計師與終端用戶間的認(rèn)知差異具有很好的適用性,能夠有效指導(dǎo)產(chǎn)品意象造型設(shè)計。
[Abstract]:In the increasingly competitive international market and the domestic market oversupply, the machinery industry is facing many challenges, how to design and produce products to meet the needs of users. Getting good market feedback is a permanent challenge for designers and manufacturers. The user not only requires the product function complete, also wants the product to have the emotion. How to quickly and accurately extract the emotional needs of users is the key to improve the competitiveness of products, so the perceptual engineering research, which can effectively extract emotional requirements, has been widely concerned by experts and scholars at home and abroad, and has become a research hotspot. In the research framework of perceptual engineering, this paper excavates the emotional image of product modeling produced by users and designers, and puts forward the identification method of product modeling elements based on rough set theory. Based on the objective emotional image, the personality elements and the platform elements are extracted to guide the product positioning, so that the modeling scheme can meet the needs of both users and designers at the same time. This research includes three stages, the research contents and the research results are as follows: the first stage studies the emotional image mining method and its technical process, and takes the bending machine as an example to investigate the designers and end users by using SD survey. The scale evaluation table of emotional image between them is obtained. In the second stage, based on rough set theory, a modeling element identification method is proposed, which accords with the target emotional image of designer and end-user. Firstly, based on the survey of product emotional image, the method of attribute reduction is blindly deleted. Then the personality elements are sorted according to the emotional images, the cognitive differences between designers and end-users are analyzed, and the modeling elements that accord with both target emotional images are identified and used for product positioning. In the third stage, the existing product positioning method and the rough set based modeling element identification method are combined to reshape the bending machine modeling, and the design scheme is verified and analyzed. The results show that this method has good applicability for fast and accurate product positioning and communication between designers and end-users, and can effectively guide product image modeling design.
【學(xué)位授予單位】：蘭州理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TH122

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