摘要
传统的产品审核方法用对汽车缺陷项打分的方式来标识缺陷对用户满意度影响程度的大小,然后,审核团队通过讨论主观地确定纠正措施。这种方法本质上是一种事后纠正的方式,且主观性强,可操作性差。本文将FMEA技术引入到产品审核阶段(简记为PAFMEA),以便定量地分析汽车缺陷对用户满意度的影响程度;在PAFMEA的纠正措施中引入了费用成本、时间成本和纠正后风险优先度3个指标及其相关信息,并以优化此三指标为目标,提出了基于多目标优化的纠正措施决策方法;应用嵌套的SAMOACOMV算法,出色地完成了多目标决策问题的优化计算。PAFMEA及其纠正措施决策方法更强调事前的风险预防,可操作性好。
Product audit is widely applied to increasing the satisfactory degree of customers. We introduce failure mode and effects analysis into product audit（PAFMEA） for quantitative analysis of the impact of car defects on cus- tomers＇ satisfactory degree. Then, we define three indices, i. e. , the cost of expense, the cost of time and the risk priority number（RPN） after correction and their relative information into PAFMEA. After that, we present a meth- od for corrective action decision-making by using multi-objective optimization algorithm with the three indices as the objectives. Finally, corrective action decision-making is realized by using the nested self-adaptive mixed-variable multi-objective ant colony optimization algorithm（ SAMOACOMv）. An example is given for corrective action deci- sion-making, and the result shows that our method is feasible and effective.
出处
《机械科学与技术》
CSCD
北大核心
2009年第2期176-181,共6页
Mechanical Science and Technology for Aerospace Engineering
基金
国家863高技术研究发展计划项目(863-511-910-403)
南京名爵(MG)汽车有限公司QCS项目资助
关键词
失效模式及后果分析
产品审核FMEA
风险优先度
自适应混合变量多目标蚁群优化算法
failure mode and effects analysis
product audit FMEA
risk priority number
self-adaptive mixed-variable multi-objective ant colony optimization algorithm
