文章摘要
王慧,邓志吉,刘明,吴容吉,陈明珠,王冰.动态用户需求下的产品数据体系设计与应用[J].包装工程,2024,(10):60-69.
动态用户需求下的产品数据体系设计与应用
Design and Application of Product Data System under Dynamic User Demands
投稿时间:2023-12-19  
DOI:10.19554/j.cnki.1001-3563.2024.10.007
中文关键词: 产品数据  用户需求  模糊Kano模型  模糊层次分析法
英文关键词: product data  user demands  fuzzy Kano model  fuzzy analytic hierarchy process
基金项目:
作者单位
王慧 浙江大华技术股份有限公司杭州 310053
西安电子科技大学西安 710071 
邓志吉 浙江大华技术股份有限公司杭州 310053
浙江大学 信息与电子工程学院杭州 310027 
刘明 浙江大华技术股份有限公司杭州 310053 
吴容吉 浙江大华技术股份有限公司杭州 310053 
陈明珠 浙江大华技术股份有限公司杭州 310053 
王冰 西安电子科技大学西安 710071 
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中文摘要:
      目的 为满足动态化用户对产品数据管理的需求,解决现有产品数据管理效率低下,底层数据杂乱,数据管理平台技术受限的问题,对现有产品数据体系进行设计,并开发产品数据平台,保证产品数据的规范化与个性化要求。方法 从动态客户需求的视角出发,提出结合模糊Kano模型和模糊层次分析法(FAHP)的产品数据体系设计方法,首先通过Voice of the Customer(VoC)法对用户需求进行收集与分析;其次通过模糊Kano模型对收集到的用户需求进行因子分类,找到关键需求因子;再次过FAHP模型对关键需求因子进行重要性排序;最后通过聚类分析需求关联性对因子进行修正。结果 得到产品数据体系的底层设计依据,应用于技术数据管理平台设计中,以效率指标量化评价设计成果。结论 该方法能够显著提升数据清洁度与有效性,满足多方用户对于产品数据的管理需求,同时也为产品数据管理平台国产化的建设提供一种可行且可靠的思路。
英文摘要:
      The work aims todesign the existing product data system and develop a product data platform to ensure the standardization and personalization of product data, so as to meet the demand of dynamic users for product data management and solve the problems of low efficiency of existing product data management, messy underlying data and limited technology of data management platforms. From the perspective of dynamic user demands, a product data system design method combining fuzzy Kano model and fuzzy analytic hierarchy process (FAHP) was proposed. First, the Voice of the Customer (VoC) method was used to collect and analyze the demands of interested parties. The fuzzy Kano model was used to classify the collected user demands and find the key demand factors. Then the importance of the key demand factors was sorted through the FAHP model. Finally, the factors were corrected through the clustering analysis demand correlation analysis. The underlying design basis of product data systems was obtained and applied to the design of technical data management platforms, and the design results were evaluated quantitatively by efficiency index. This method can significantly improve the data cleanliness and effectiveness, meet the demands of multiple users for product data management, and also provide a feasible and reliable idea for the construction of the localization of product data management platforms.
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