【摘要】：在大批量定制的生產(chǎn)方式下，企業(yè)成功的關(guān)鍵在于能否抓住不確定的用戶需求信息。也就是說，用戶在企業(yè)的經(jīng)營決策中扮演著非常重要的角色。隨著科技進(jìn)步和產(chǎn)品競爭的加劇，企業(yè)對由不確定用戶驅(qū)動的、以產(chǎn)品平臺為基礎(chǔ)的產(chǎn)品設(shè)計理論及其實(shí)踐產(chǎn)生了迫切的需求。本論文針對大批量定制環(huán)境下，由不確定用戶驅(qū)動的產(chǎn)品平臺設(shè)計進(jìn)行了研究，主要包含以下幾部分內(nèi)容： （1）獲取不確定用戶需求信息后，對其進(jìn)行分析和處理。根據(jù)用戶需求信息具有模糊語義、缺失信息、冗余信息的特點(diǎn)，首先采用模糊集對模糊語義信息做量化處理，，再利用模糊集中的隸屬度將其離散化；然后，采用粗糙集對需求信息做�；幚硪匝a(bǔ)全缺失信息，再利用其屬性約簡消除需求信息中的冗余信息。這將為后續(xù)映射產(chǎn)品設(shè)計參數(shù)做準(zhǔn)備。 （2）使用TRIZ理論拓展用戶需求。構(gòu)建產(chǎn)品特性模型，并以注射機(jī)產(chǎn)品為例，建立產(chǎn)品實(shí)例庫。使用NN聚類分析中的廣義歐氏距離，比較需求信息與產(chǎn)品實(shí)例庫中的產(chǎn)品信息，在產(chǎn)品實(shí)例庫中選取較接近的多個實(shí)例產(chǎn)品。建立了基于F-AHP的評價模型對其進(jìn)行綜合評價，以選出用戶最滿意的產(chǎn)品。 （3）對應(yīng)于產(chǎn)品設(shè)計參數(shù)為連續(xù)數(shù)值，建立SVR（回歸）映射模型；為離散數(shù)值，建立SVC（分類）映射模型。使用TRIZ理論解決在產(chǎn)品映射過程中產(chǎn)生的沖突，并根據(jù)沖突消解方案調(diào)整產(chǎn)品設(shè)計參數(shù)。然后，使用LSSVC聚類方法對產(chǎn)品進(jìn)行模塊化設(shè)計，并通過產(chǎn)品設(shè)計參數(shù)和模塊之間的關(guān)系，對相似實(shí)例產(chǎn)品的模塊進(jìn)行修改、調(diào)整或變型設(shè)計。 （4）以注射機(jī)產(chǎn)品為例，通過對不確定用戶提出訂單的處理，展開了基于-NN注射機(jī)產(chǎn)品的配置設(shè)計過程，并基于F-AHP對其配置方案進(jìn)行了評價。在用戶不滿意的情況下，展開了基于粗糙集+支持向量機(jī)映射模型，注射機(jī)產(chǎn)品的定制設(shè)計過程。通過注射機(jī)產(chǎn)品實(shí)例，驗(yàn)證了本論文面向不確定用戶需求信息，以產(chǎn)品平臺為基礎(chǔ)的，產(chǎn)品配置設(shè)計和定制設(shè)計方法研究的正確性和實(shí)用性。
[Abstract]:In mass customization production mode, the key to enterprise success lies in whether or not to grasp the uncertain user demand information. In other words, users play a very important role in business decisions. With the development of science and technology and the aggravation of product competition, there is an urgent need for the theory and practice of product design based on product platform driven by uncertain users. In this paper, the design of product platform driven by uncertain users in mass customization environment is studied. The main contents are as follows: (1) after obtaining the information of uncertain user requirements, it is analyzed and processed. According to the characteristics of fuzzy semantics, missing information and redundant information, the fuzzy set is used to quantify the fuzzy semantic information, and then the membership degree of the fuzzy set is used to discretize the fuzzy semantic information. Then, the requirement information is granulated by rough set to complement the missing information, and then the redundant information is eliminated by attribute reduction. This will prepare for subsequent mapping of product design parameters. (2) using TRIZ theory to expand the user's demand. The product characteristic model was constructed, and the product case library was established by taking the injection machine product as an example. Using the generalized Euclidean distance in NN clustering analysis, the requirement information is compared with the product information in the product case library. A comprehensive evaluation model based on F-AHP is established to select the most satisfied products. (3) the SVR (regression) mapping model and the SVC (classification) mapping model are established for discrete values corresponding to the continuous values of product design parameters. The TRIZ theory is used to solve the conflicts in the process of product mapping, and the product design parameters are adjusted according to the conflict resolution scheme. Then, the modular design of the product is carried out by using LSSVC clustering method, and through the relationship between the product design parameters and the module, the module of the product with similar examples is modified, adjusted or modified. (4) taking the injection machine product as an example, the configuration design process based on-NN injection machine product is carried out, and the configuration scheme is evaluated based on F-AHP. Based on the rough set support vector machine mapping model, the customized design process of injection machine product is carried out in the case of user dissatisfaction. Through the product example of injection machine, the correctness and practicability of product configuration design and customization design method based on product platform are verified in this paper.
【學(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TB472

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 宗鳴鏑,蔡穎,劉旭東,李湘媛;產(chǎn)品模塊化設(shè)計中的多角度、分級模塊劃分方法[J];北京理工大學(xué)學(xué)報;2003年05期

2 李少波;牟健慧;;TRIZ進(jìn)化理論支持的進(jìn)化過程研究[J];長春理工大學(xué)學(xué)報(自然科學(xué)版);2009年03期

3 顧新建,祁國寧;大成組技術(shù)與大規(guī)模定制生產(chǎn)[J];成組技術(shù)與生產(chǎn)現(xiàn)代化;1999年04期

4 岳同啟,王吉軍,王海軍,盛晉珩;智能客戶需求獲取系統(tǒng)的結(jié)構(gòu)設(shè)計[J];大連大學(xué)學(xué)報;2003年04期

5 趙韓;朱凌云;錢德猛;;面向大規(guī)模定制產(chǎn)品設(shè)計的客戶需求處理研究[J];工程圖學(xué)學(xué)報;2008年03期

6 熊立華,王云峰,張柯;面向大規(guī)模定制的產(chǎn)品簇建模研究[J];工業(yè)工程;2005年01期

7 黃燦軍;;注塑機(jī)合模裝置的技術(shù)及研究進(jìn)展[J];塑料制造;2006年Z1期

8 吳建;;TRIZ理論在搜索引擎創(chuàng)新設(shè)計中的應(yīng)用研究[J];重慶郵電大學(xué)學(xué)報(自然科學(xué)版);2012年06期

9 王莉靜;郗濤;檀潤華;;基于LSSVC的產(chǎn)品模塊劃分方法[J];河北工業(yè)大學(xué)學(xué)報;2011年02期

10 毛韶陽;李肯立;王志和;;最小生成樹聚類方法研究[J];懷化學(xué)院學(xué)報(自然科學(xué));2007年02期

相關(guān)博士學(xué)位論文 前5條

1 王亞萍;需求驅(qū)動的個性化產(chǎn)品配置設(shè)計方法研究[D];哈爾濱理工大學(xué);2010年

2 甘得泉;柔性產(chǎn)品平臺設(shè)計理論及其應(yīng)用[D];河北工業(yè)大學(xué);2010年

3 常艷;快速響應(yīng)客戶需求的產(chǎn)品族設(shè)計方法研究[D];浙江大學(xué);2008年

4 袁際軍;大規(guī)模定制下基于約束的產(chǎn)品配置方法研究[D];湖南大學(xué);2008年

5 宋春華;高性能注塑機(jī)關(guān)鍵技術(shù)的研究[D];西南交通大學(xué);2009年

本文編號：2300865