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首页> 外文会议>Reliability and Maintainability Symposium (RAMS), 2012 Proceedings - Annual >OMSP: Failure detection based on small field part and data volumes
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OMSP: Failure detection based on small field part and data volumes

机译：OMSP：基于小字段部分和数据量的故障检测

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Increasing functionality and complexity of technical products result in complex damage symptoms and failure modes within the customer use phase. Especially in automotive industry, complex damage symptoms are often the result of multiple failure modes. Therefore the importance of continuous field product observation and field data analysis is an important way for analyzing product reliability in the use phase. For the manufacturer, the goals are the accurate and economic identification of possible failure modes and the knowledge of the product failure behavior based on field complaints at an early stage after product market launch. In addition to statistical reliability analysis based on field data (e.g. Weibull distribution analysis, RAW Concept), the technical analysis of damaged field components is an essential point for the detection and verification of individual failure modes. Especially for this technical analysis, the manufacturer needs damaged field components, which represent the whole supposed failure spectrum in the field. The goals for the manufacturer include: (1) Early and detailed detection and identification of critical failure modes, with the objective of targeted response to critical failure modes (2) Conjunction of requirements for the determination of the regress rate and detection of the critical failures in a comprehensive approach (cf. chapter 2) (3) Optimization of economic aspects of the reliability analysis in terms of sampling procedure, sampling analysis and technical analysis costs (4) Integration into existing technical analysis processes to establish and support an industry-specific standard The temporal aspect results in reduced field monitoring periods and therefore results in small damaged field part and data volumes. This requirement restricts the use of parametrical statistical methods and requires the use of nonparametric statistical methods. The results of field data and technical analysis generate the basis for a targeted roll- out of further actions, for example field failure rectification or product optimization. Moreover the initiation of concentrated development-approaches /-strategies for failure prevention with respect to the subsequent product generations (e.g.: COP strategy) is feasible. An industry-wide or cross-industry approach for economic and optimized sampling procedures of damaged components out of the field does not exist. The Chair of Safety Engineering / Risk Management at the University of Wuppertal - in cooperation with manufacturers of the automotive industry - developed the Optimized Multi-Stage Sampling Procedures (OMSP) concept. The OMSP concept is a proposal regarding to analyzing standard for the automotive industry. Key aspects of the OMSP concept are as follows: (1) Early identification and analysis of critical failure modes with reduced amount of analyzed damaged components but with similar detection rate and resolution accuracy (2) Reducing costs of the technical analysis reduce the scope of analyzed damaged components with comparable detection rate of critical failure modes (3) Deselection of selected data areas to reduce the amount of data and the request of considered damaged components allows the verification of the reliability of technical component changes while drawing constant sample sizes (4) Recognition of critical failure modes allows targeted actions for troubleshooting, for example in the field or in the current product generation (5) Integration of the OMSP concept in the FDA process allows the verification of the potential failure modes detected by the statistical reliability analysis This paper outlines the effectiveness and use of the OMSP concept in a near reality case study of the automotive industry. The focus of the case study is the analysis of a shift by wire actuator module (consisting of an electric motor and electrical control unit) including different failure modes. The application of the OMSP concept shows the following essential r
机译：技术产品的功能和复杂性的提高导致在客户使用阶段出现复杂的损坏症状和故障模式。特别是在汽车工业中，复杂的损坏症状通常是多种故障模式的结果。因此，连续现场产品观察和现场数据分析的重要性是在使用阶段分析产品可靠性的重要方法。对于制造商而言，目标是在产品市场启动后的早期阶段，根据现场投诉准确，经济地识别可能的故障模式，并了解产品故障行为。除了基于现场数据的统计可靠性分析（例如Weibull分布分析，RAW Concept）之外，对损坏的现场组件进行技术分析也是检测和验证单个故障模式的关键点。特别是对于此技术分析，制造商需要损坏的现场组件，这些组件代表了整个假定的现场故障范围。制造商的目标包括：（1）对关键故障模式进行早期和详细的检测和识别，目标是对关键故障模式做出有针对性的响应（2）结合确定回归率和检测关键故障的要求（参见第2章）（3）在抽样程序，抽样分析和技术分析成本方面优化可靠性分析的经济方面（4）集成到现有技术分析过程中以建立并支持特定行业标准时间方面会减少现场监视时间，因此会导致损坏的现场部分和数据量较小。该要求限制了参数统计方法的使用，并要求使用非参数统计方法。现场数据和技术分析的结果为有针对性地推出进一步措施（例如现场故障纠正或产品优化）奠定了基础。而且，针对随后的产品世代（例如：COP策略）发起用于预防失败的集中的开发方法/策略是可行的。目前还没有一种针对整个行业或跨行业的方法，可以对损坏的组件进行经济有效的优化采样。伍珀塔尔大学安全工程/风险管理主席与汽车行业的制造商合作，制定了“优化多阶段抽样程序”（OMSP）的概念。 OMSP概念是有关分析汽车行业标准的建议。 OMSP概念的关键方面如下：（1）早期识别和分析关键故障模式，减少了分析的受损组件数量，但检测率和分辨率精度相近（2）降低了技术分析的成本，缩小了分析范围具有相当高的关键故障模式检出率的损坏部件（3）取消选择数据区域以减少数据量，并考虑考虑到损坏部件的要求，从而可以在绘制恒定样本量的同时验证技术部件更改的可靠性（4）识别关键故障模式的使用可以针对性地采取措施进行故障排除，例如在现场或在当前产品中进行故障排除（5）将OMSP概念集成到FDA流程中，可以验证通过统计可靠性分析检测到的潜在故障模式。 OMSP概念在近乎现实的案例研究中的有效性和使用f汽车工业。案例研究的重点是通过线致动器模块（由电动机和电气控制单元组成）分析换档，包括不同的故障模式。 OMSP概念的应用显示了以下基本要求

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