OptNeTol: Integrated, optimization-based parameter and tolerance design

OptNeTol：基于优化的集成参数和公差设计

• 批准号: 362421942
• 负责人: Professor Dr.-Ing. Sandro Wartzack
• 金额: --
• 依托单位: Lehrstuhl für Konstruktionstechnik (KTmfk)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/362421942?language=en
• 关键词: OptNeTol; Integrated; optimization; based; parameter

The usage of optimization methods for optimal tolerance allocation significantly contributes to the development of least-cost and high-quality products. By formulating suitable optimization problems and solving them with the aid of powerful algorithms, nominal dimensions and tolerance values can be allocated in a way that the cost potential is fully exploited while ensuring that the stringent requirements on robustness, function and aesthetics are fulfilled. In this way, optimization-based methods successively replace purely qualitative approaches, such as simple rules of thumb or well-known theorems like "define tolerances as wide as possible, but as tight as necessary", and thereby create an undisputed competitive advantage.In the preceding funding phase, an important basis for the productive use of tolerance optimization in the industrial environment was established. However, it cannot effectively contribute to answering practice-relevant questions yet. This is mainly due to the deficits of efficient, valid optimization methods, the missing link between the interdisciplinary methods and their lack of focus on practical problems.Therefore, the aim of this research project is to enable the product developer to assign cost-optimal part dimensions and tolerances to practically relevant application cases. This implies that the obstacles to the practical application of the interdisciplinary and at the same time highly specialized methods of nominal dimension and tolerance optimization are largely eliminated. In this context, innovative methods of nominal dimension and tolerance optimization are developed addressing aspects that have not been considered so far, but are absolutely necessary for practical use, such as geometrical tolerances or the handling of missing or uncertain cost information. However, since the optimization problems can only be solved by powerful, sampling-based optimization algorithms, the focus of this research project is also on the development and combination of methods to significantly increase the efficiency in the determination of valid optimization results, such as adaptive sampling and surrogate modelling, including statistical tolerance analysis methods. Finally, the individually developed methods will be linked in a software prototype based on a common, interdisciplinary knowledge base and their applicability will be evaluated in user studies. This ensures that product developers without in-depth knowledge of optimization are supported in defining and solving practical problems as automatically as possible. Thus, currently open research gaps preventing the change from an expert tool for mere tolerance optimization to an integrated, optimization-aided tolerance management are finally closed.

优化方法的最佳耐受性分配方法可显着有助于开发最低成本和高质量的产品。通过制定合适的优化问题并借助强大的算法来解决它们，可以以完全利用成本潜力的方式分配名义维度和公差值，同时确保满足鲁棒性，功能和美学的严格要求。通过这种方式，基于优化的方法依次替换了纯粹的定性方法，例如简单的拇指规则或众所周知的定理，例如“定义尽可能宽的公差，但尽可能紧密”，从而创造出无可争议的竞争优势。在先前的筹资阶段，在工业环境中具有生产力优化的重要基础。但是，它无法有效地回答与实践相关的问题。这主要是由于有效，有效的优化方法的缺陷，跨学科方法与他们对实际问题的缺乏联系。因此，该研究项目的目的是使产品开发人员能够将成本优化的零件维度和容忍度分配给实际相关应用程序案例。这意味着，跨学科的实际应用障碍，同时在很大程度上消除了高度专业化的名义维度和耐受性优化方法。在这种情况下，开发了象征性维度和耐受性优化的创新方法，以解决迄今尚未考虑的方面，但对于实际使用，例如几何公差或处理缺失或不确定的成本信息是绝对必要的。但是，由于优化问题只能通过强大的，基于抽样的优化算法来解决，因此该研究项目的重点还在于开发和组合，以显着提高确定有效优化结果的效率，例如自适应采样结果，例如统计耐受性分析方法。最后，将基于常见的跨学科知识库的软件原型链接单独开发的方法，其适用性将在用户研究中评估。这样可以确保在尽可能自动定义和解决实际问题时，支持没有深入优化知识的产品开发人员。因此，目前开放的研究差距阻止了专家工具的变化仅仅是耐受性优化，以至于综合，优化的耐受性管理最终被关闭。