上海大学学报(自然科学版) ›› 2020, Vol. 26 ›› Issue (2): 292-300.doi: 10.12066/j.issn.1007-2861.2034

• 研究论文 • 上一篇    下一篇

基于区间值直觉模糊集的技术创新风险评价方法

田永超, 于丽英()   

  1. 上海大学 管理学院, 上海 200444
  • 收稿日期:2018-02-21 出版日期:2020-04-30 发布日期:2020-04-29
  • 通讯作者: 于丽英 E-mail:yuliying@shu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(11671250)

Technology innovation risk evaluation based on interval value intuitionistic fuzzy sets

TIAN Yongchao, YU Liying()   

  1. School of Management, Shanghai University, Shanghai 200444, China
  • Received:2018-02-21 Online:2020-04-30 Published:2020-04-29
  • Contact: YU Liying E-mail:yuliying@shu.edu.cn

摘要:

降低企业技术创新风险是提高企业技术创新绩效的关键.首先以技术创新六阶段模型为基础,针对技术创新的全生命周期识别了 18 项潜在风险.之后基于区间值直觉模糊集构建了应用于企业技术创新风险评价的模糊失效模式与影响分析 (failuremode and effect analysis, FMEA) 方法.该方法利用区间值直觉模糊集来评价技术创新各潜在风险的严重度、发生度和检测度,通过基于逼近理想解排序法 (technique for order preference bysimilarity to ideal solution,TOPSIS) 的非线性规划模型获得风险优先级并进行排序,以此为依据确定潜在风险的优先处理次序.最后以 D 公司的座椅开发项目为例, 验证了该模糊 FMEA 方法的可行性.

关键词: 技术创新, 区间值直觉模糊集, 失效模式与影响分析, 风险评价

Abstract:

Reducing the risks of technological innovation in enterprises is the key to improving the technological innovation performance. This paper first identifies 18 potential risks based on the six-stage model of technological innovation, and then constructs the fuzzy failure mode and effect analysis (FMEA) method applied to the risk assessment of technological innovation based on the interval value intuitionistic fuzzy set. The method evaluates the severity, occurrence and detection of each potential risk by the interval valued intuitionistic fuzzy set. Risk priority numbers are obtained and sorted by the technique for order preference by similarity to ideal solution (TOPSIS)-based nonlinear programming solution, which can be used as a basis for prioritizing potential risks. At last, the feasibility of the fuzzy FMEA method is verified by an example of D-company's seat development project.

Key words: technological innovation, interval valued intuitionistic fuzzy set, failure mode and effect analysis (FMEA), risk assessment

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