文章摘要
陈国强,戴成,申正义,张鹏,唐子琛.基于QFD与FBS的可移动电力检测设备创新设计[J].包装工程,2021,42(2):43-50.
基于QFD与FBS的可移动电力检测设备创新设计
Design of Movable Electric Testing Station Based on QFD and FBS
投稿时间:2020-08-10  
DOI:10.19554/j.cnki.1001-3563.2021.02.007
中文关键词: 创新设计  QFD  FBS  可移动电力检测设备
英文关键词: innovative design  QFD  FBS  movable power testing equipment
基金项目:河北省社会科学基金(HB19YS004)
作者单位
陈国强 燕山大学 艺术与设计学院秦皇岛 066004 
戴成 燕山大学 艺术与设计学院秦皇岛 066004 
申正义 燕山大学 机械工程学院秦皇岛 066004 
张鹏 燕山大学 艺术与设计学院秦皇岛 066004 
唐子琛 燕山大学 艺术与设计学院秦皇岛 066004 
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中文摘要:
      目的 为了客观准确地将目标用户认知需求转化为产品技术特性的设计要求,提升可移动电力检测设备目标用户认知需求满意度及明确产品创新方向,提出QFD和FBS集成的创新设计模式。方法 首先,通过访谈和问卷调研获取用户需求,借助AHP法求解用户认知需求权重;其次,运用QFD法构建质量屋,明确可移动电力检测设备待改进的关键技术特性指标;最后,将用户旅程图引入FBS的功能—行为—结构展开模型中,以解决可移动电力检测设备的关键技术特性问题,指导产品创新设计。结论 QFD与FBS理论的融合应用能够将用户认知需求精准转化为技术特性层面的设计要求,对可移动电力检测设备的人机、造型、功能、收纳等方面的不足提出了相应的解决方案,实现了用户认知需求与产品技术特性之间的映射转换,证明了该方法具有可行性。
英文摘要:
      The work aims to objectively and accurately transform target user cognitive demands into product technical characteristic design requirements, improve the satisfaction of target user cognitive demands of movable power testing equipment and clarify the direction of product innovation, and propose an innovative design model based on QFD and FBS integration.Firstly, the user demands were obtained through interviews and questionnaire surveys, and the AHP method was used to solve the weight of user cognitive demands; secondly, the QFD method was used to build a house of quality and identify the key technical characteristics to be improved for the movable power testing equipment; finally, the user journey map was introduced into the FBS expansion model to solve the key technical characteristics of movable power testing equipment and guide product innovation design.The converged application of QFD and FBS can accurately transform user cognitive demands into design requirements at the technical characteristic level, propose corresponding solutions to the deficiencies of movable power testing equipment in man-machine, shape, function, storage, etc., and realize the mapping and conversion between user cognitive demands and product technical characteristics, proving the feasibility of the method.
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