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.

使用最优化方法进行公差的最优分配，对于开发成本最低、质量最高的产品有着重要的意义。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，基于优化的方法逐渐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，如“将公差定义得尽可能宽，但要尽可能紧”，从而创造了无可争议的竞争优势。在前一个融资阶段，为公差优化在工业环境中的生产性使用奠定了重要基础。然而，它还不能有效地帮助回答与实践有关的问题。这主要是由于缺乏高效、有效的优化方法，缺少跨学科方法之间的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将成本最优的零件尺寸和公差分配给实际相关的应用案例。这意味着，跨学科和高度专业化的公称尺寸和公差优化方法的实际应用障碍在很大程度上被消除。在这种情况下，开发了标称尺寸和公差优化的创新方法，解决了迄今为止尚未考虑的方面，但对于实际使用是绝对必要的，例如几何公差或丢失或不确定的成本信息的处理。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，因此本研究项目的重点也是开发和组合方法，以显着提高确定有效优化结果的效率，例如自适应采样和替代建模，包括统计公差分析方法。最后，将在一个共同的跨学科知识库的基础上，将个别开发的方法与一个软件原型联系起来，并将在用户研究中评价其适用性。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，目前开放的研究差距，防止从一个专家工具，单纯的公差优化到一个综合的，优化辅助公差管理的变化，最终关闭。