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.

使用优化方法进行最佳公差分配极大地有助于开发成本最低且高质量的产品。通过制定合适的优化问题并借助强大的算法解决这些问题，可以以充分利用成本潜力的方式分配标称尺寸和公差值，同时确保满足对坚固性、功能和美观的严格要求。通过这种方式，基于优化的方法相继取代了纯粹的定性方法，例如简单的经验法则或众所周知的定理，例如“定义尽可能宽的公差，但尽可能严格”，从而创造了无可争议的竞争优势。在之前的融资阶段，为工业环境中宽容优化的生产性利用奠定了重要基础。然而，它还不能有效地回答与实践相关的问题。这主要是由于缺乏高效、有效的优化方法、跨学科方法之间缺乏联系以及缺乏对实际问题的关注。因此，本研究项目的目的是使产品开发人员能够分配成本最优的部分尺寸和公差与实际相关的应用案例。这意味着跨学科且同时高度专业化的标称尺寸和公差优化方法实际应用的障碍已基本消除。在此背景下，开发了标称尺寸和公差优化的创新方法，解决迄今为止尚未考虑但对于实际使用绝对必要的方面，例如几何公差或处理缺失或不确定的成本信息。然而，由于优化问题只能通过强大的、基于采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方法，以显着提高确定有效优化结果的效率，例如自适应抽样和替代建模，包括统计公差分析方法。最后，单独开发的方法将链接到基于通用跨学科知识库的软件原型中，并且它们的适用性将在用户研究中进行评估。这确保了没有深入优化知识的产品开发人员能够尽可能自动地定义和解决实际问题。因此，目前阻碍从单纯的公差优化的专家工具转变为集成的、优化辅助的公差管理的研究差距最终得以解决。