Methodology for generating cross-technology metamodels (IKTINO)

生成跨技术元模型的方法（IKTINO）

• 批准号: 441745638
• 负责人: Professor Dr.-Ing. Thomas Bergs
• 金额: --
• 依托单位: Werkzeugmaschinenlabor - WZL
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/441745638?language=en
• 关键词: Methodology; generating; cross; technology; metamodels

For manufacturing companies, it is of high relevance to design the production of components in such a way that the required component characteristics are manufactured with minimized time and cost investments. Until now, the individual processes for manufacturing a component were often considered separately from each other and only merged at higher planning levels. However, the cross-technology consideration of process sequences offers a high optimization potential, because the individual processes and process parameters are thus coordinated in a target-oriented manner. At the same time, increasingly shorter product development cycles mean that process sequences have to be designed in a short time. Therefore, fundamental models and methods are needed that support the rapid determination of economically optimized process parameters for process sequences.So far, no approach has been developed to quickly determine economically optimized process parameters for process sequences, taking into account the dependencies between the individual manufacturing processes and component characteristics. In order to close this research gap, a methodology will be developed in the proposed research project to determine economically optimized process parameters for process sequences on the basis of cross-technology metamodels. Metamodels map input-output correlations for individual manufacturing processes, exclusively resorting to a selection of the most important parameters for the application and thus enabling relevant insights into the design of process sequences within a short period of time. One focus of the proposed research project is therefore the metamodeling of process sequences. Metamodels of individual manufacturing processes are linked to cross-technology metamodels via previously identified transfer variables between the individual processes. Subsequently, the effects of the parameter reductions resulting from the selection of the most important parameters on the prediction accuracy of the overall model will be investigated so that an optimized parameter selection can be made.The second focus of the research project is the economic optimization of cross-technology metamodels. On the one hand, a method will be developed that enables meta cost models to be generated in order to determine the effects of individual process parameters on the costs of the process sequence. On the other hand, a novel optimization algorithm based on genetic algorithms will be developed, which enables the determination of economically optimized process parameters based on cross-technology metamodels and required component characteristics. The developed methodology will then be implemented in software and validated using two case studies.

对于制造公司来说，设计组件的生产非常重要，这样可以用最少的时间和成本投资来制造所需的组件特性。到目前为止，制造组件的各个流程通常是相互独立考虑的，并且仅在更高的规划级别上进行合并。然而，工艺顺序的跨技术考虑提供了很高的优化潜力，因为各个工艺和工艺参数因此以目标导向的方式进行协调。与此同时，越来越短的产品开发周期意味着必须在短时间内设计工艺流程。因此，需要基本模型和方法来支持快速确定工艺序列的经济优化工艺参数。到目前为止，还没有开发出一种方法来快速确定工艺序列的经济优化工艺参数，同时考虑到各个制造之间的依赖性过程和组件特性。为了缩小这一研究差距，将在拟议的研究项目中开发一种方法，以基于跨技术元模型确定工艺序列的经济优化工艺参数。元模型映射各个制造过程的输入输出相关性，专门选择应用程序最重要的参数，从而在短时间内实现对过程序列设计的相关洞察。因此，拟议研究项目的重点之一是过程序列的元建模。各个制造过程的元模型通过先前确定的各个过程之间的传递变量链接到跨技术元模型。随后，将研究由于选择最重要的参数而导致的参数减少对整个模型预测精度的影响，以便做出优化的参数选择。该研究项目的第二个重点是经济优化跨技术元模型。一方面，将开发一种能够生成元成本模型的方法，以确定各个工艺参数对工艺序列成本的影响。另一方面，将开发一种基于遗传算法的新型优化算法，该算法能够根据跨技术元模型和所需的组件特性确定经济优化的工艺参数。然后，开发的方法将在软件中实施，并使用两个案例研究进行验证。