Qua2Pro Quality feature based quantification of production risks

由于更短的产品开发周期，更大的变型范围和不断增加的产品复杂性，制造公司面临着越来越多的技术风险，这些风险强烈地影响了产品的质量，可靠性，从而影响了产品的成功和竞争力。对风险概率和风险的潜在经济后果进行量化和有效的分析和评估是确保产品和过程安全的关键挑战。目前，风险管理的量化方法主要集中在金融部门和公司领域，对操作风险即价值链风险的拓展尚未建立。现有的识别和评估技术风险管理的方法，如FMEA，没有将定性评估联系起来。除了对潜在失败的量化之外，当过程中只发生很小的变化时，代表高风险的“差点失败”的影响也被低估了。目前还没有合适的方法和方法来识别、分析和系统地处理生产中的这些“未遂事件”。本研究项目的总体目标是发展方法，以对发生的可能性和相关的金钱后果进行量化评估的形式，得出描述生产中失败风险的综合关键绩效指标。出发点是以质量特征的形式对产品和过程的需求进行分类。因此，开发了一个程序来识别和表征这些质量特征。作为次要目标，将开发模型以确定风险的概率和确定风险的货币损失的部分成本函数。对于建模，将研究统计评估方法的使用，例如过程能力指数和描述罕见事件的方法（极值理论）。其中，通过基于仿真的验证，保证了科学结果的可转移性。通过涡轮叶片对所开发的方法进行了验证。技术风险的量化评估是质量管理面临的最大科学挑战之一。调查统计方法对技术风险评估的可转移性是研究项目中的主要挑战。通过对故障事件和相关财务后果的量化可预测性，为产品和工艺创新的成功延续提供了更好的基础。可以更有针对性地实施风险处理的预防措施，更准确地评价其效果。由于缺乏关于发生概率和成本的精确陈述，以前很难证明技术风险管理的好处，但这项研究项目的结果使之成为可能。

Due to shorter product development cycles, higher range of variants and increasing product complexity manufacturing companies are facing increasing technical risks that strongly affect the quality, reliability, and thus the success of a product as well as the competitiveness. A quantified and valid analysis and assessment of risk probability and potential monetary consequences of risks represents a key challenge to ensure the safety of products and processes. So far, quantifying approaches of risk management mainly concentrate on the financial sector and areas of a company, so that the expansion on operational risks, i. e. risks along the value chain is not established yet. Existing approaches for identification and assessment of technical risk management, such as FMEA, do not link the qualitative assessment. Besides the quantification of potential failures, the effect of Near-Misses, that represent high risks when only small changes in a process occur, are underestimated. Suitable approaches and methods for identification, analysis and systematic handling of these Near-Misses in production are missing.The overall objective of this research project is the development of methods to derive aggregated key performance indicators describing a failure risk in production, in the form of quantified assessment of the probability of occurrence and the associated monetary consequences. Starting point is the classification of requirements on product and process in form of quality features. Therefore, a procedure is developed to identify and characterize these quality features. As a secondary objective, models will be developed to determine the probability of risk and partial cost functions for determination of the monetary losses of a risk. For modeling, the use of statistical evaluation methods will be investigated, such as process capability indices and approaches for describing rare events (extreme value theory). Amongst others, through a simulation-based validation the transferability of the scientific result is assured. The validation of the developed methods is performed by means of a turbine blade.The quantified assessment of technical risks is one of the biggest scientific challenges of quality management. The investigation of the transferability of statistical approaches to the assessment of technical risks represents the main challenge within the research project. Through quantified predictability of a failure event and the connected monetary consequences, a better-grounded basis for the successful continuance of product and process innovations is provided. Preventive measures of risk treatment can be implemented more focused and their effect can be evaluated more precisely. The previously hard demonstration of the benefit of technical risk management, due to the lack of precise statements about the probability of occurrence and costs, is made possible by the results of the research project.