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KAUSAL - Transparent Modelling of Causal Chains regarding Failure Development in Complex Systems

KAUSAL - 关于复杂系统故障发展的因果链透明建模

基本信息

批准号：
282754305
负责人：
Professorin Dr.-Ing. Petra Winzer
金额：
--
依托单位：
Fachgebiet Produktsicherheit und Qualität
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/282754305?language=en
关键词：
KAUSAL Transparent Modelling Causal Chains

项目摘要

Due to high wage costs and incidental wage costs Germany has no opportunity to beat competitors prices from low-wage countries. As the price cannot be the compelling argument for buying our products, it is essential for industrial companies to hold what the Made in Germany seal promises. But prominent examples impressively demonstrate that our existing methods for failure analysis and failure prevention are no longer sufficient. There are two relevant failure categories: On the one hand, subsystems meet their specifications, if they are considered individually. But the overall system, which combines multiple subsystems is not functioning properly, e.g. due to compounding tolerances. On the other hand, a subsystem is not okay and affects other subsystems as well as the overall system. Recent approaches in terms of industry 4.0 identify those problems, but adhere to component-based or module-based analysis. They do not consider that a system is more than the sum of its subsystems. As the complexity of modern products increases, their development requires experts from various engineering disciplines. In combination with numerous customer-supplier relations, in which system suppliers take over the development of components and subsystems, failures are difficult to trace. This is especially the case, when failure causes and consequences distribute to multiple system levels. Considering these issues, the project KAUSAL strives to establish a holistic methodology for product development of complex systems in industrial companies. The resulting methodology shall not restrict the length of causal chains of failure emergence and it shall be convenient to depict malfunctions in addition to failures. Causal chains are analyzed across the boundaries of engineering disciplines and subsystems in order to develop integral resolutions. Within the project a standardized system model will be elaborated using product examples from the fields of electromobility, intralogistics and renewable energies. This system model serves as structured information pool for the causal chains. Basing on this model, failures and malfunctions will be formulated systematically and integrated into a causal chain model. Subsequently, techniques for qualitative and quantitative evaluation from established reliability methods will be applied on the causal chains. Result of the project is a validated KAUSAL-methodology, which is suitable to trace potential failures and malfunctions regarding their causes and consequences on various system levels. Transparent depiction of failures enables a better system understanding and serves as basis for discussions between the engineering disciplines as well as customers and suppliers.

由于高工资成本和附带工资成本，德国没有机会击败来自低工资国家的竞争对手。由于价格不能成为购买我们产品的令人信服的理由，工业企业必须遵守“德国制造”的承诺。但是，突出的例子令人印象深刻地表明，我们现有的故障分析和故障预防方法已不再足够。有两种相关的故障类别：一方面，如果单独考虑子系统，则子系统满足它们的规范。但是，由于复合公差等原因，由多个子系统组成的整个系统不能正常工作。另一方面，一个子系统不好，会影响其他子系统以及整个系统。工业4.0方面的最新方法确定了这些问题，但坚持基于组件或基于模块的分析。他们不认为一个系统是子系统的总和。随着现代产品复杂性的增加，它们的开发需要来自各个工程学科的专家。结合众多的客户-供应商关系，其中系统供应商接管了组件和子系统的开发，故障很难追踪。当故障的原因和结果分布到多个系统级别时，情况尤其如此。考虑到这些问题，KAUSAL项目努力为工业公司的复杂系统的产品开发建立一个整体的方法。由此产生的方法不应限制故障出现的因果链的长度，并且除了故障之外，还应方便地描述故障。因果链分析跨越工程学科和子系统的边界，以制定整体的解决方案。在该项目中，将利用电动汽车、内部物流和可再生能源领域的产品实例，详细阐述标准化系统模型。该系统模型作为因果链的结构化信息池。在此模型的基础上，系统地制定故障和故障，并将其整合到因果链模型中。随后，从已建立的可靠性方法中进行定性和定量评估的技术将应用于因果链。项目的结果是一个经过验证的kausal方法，它适用于跟踪潜在的故障和故障，以及它们在不同系统级别上的原因和后果。对故障的透明描述能够更好地理解系统，并作为工程学科之间以及客户和供应商之间讨论的基础。