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Innovation beyond optimization: Application to cutting tool design
Computers & Industrial Engineering ( IF 7.9 ) Pub Date : 2021-01-23 , DOI: 10.1016/j.cie.2021.107139
Hicham Chibane , Sébastien Dubois , Roland De Guio

During the development of a product, several steps and iterations are necessary for meeting specifications and optimizing performance criteria. This article addresses machining problem, that are faced to increasing constraints and performance criteria. A multi-objective optimization approach is a common approach for determining a solution that meets all these constraints. The Design of Experiments (DoE) is used for modeling and understanding of the process with a minimum of experiences. When the multi-objective optimization approach demonstrates that, for a given design, no single solution exists that optimizes all objectives, the best partial solutions belong to the set of Pareto optimal solutions. In this study, a global approach for determining the optimal solution from a DoE and overcoming this optimum by the complementary use of TRIZ-based methods is proposed. In the proposed approach, optimization and inventive methods are linked. The proposed approach aims to exploit the data from multi-objective optimization and the concept of Pareto optimums to identify ways of modifying a system to respond to more objectives. A new definition of the system of generalized contradictions, which is more complete than previous definitions, is used in the proposed method. This proposal is an illustration of a global research project that aims at linking optimization and inventive methods. An application of this method is proposed for the design of a new cutting tool for the machining of composite materials. Furthermore, the limitations of the method, which proves to be satisfactory in comparison with previously proposed methods, are discussed.



中文翻译:

超越优化的创新:应用于切削刀具设计

在产品开发过程中,要满足规格和优化性能标准,必须执行几个步骤和迭代。本文解决了机械加工问题,这些问题面临着越来越多的约束和性能标准。多目标优化方法是确定满足所有这些约束的解决方案的常用方法。实验设计(DoE)用于以最少的经验对过程进行建模和理解。当多目标优化方法表明,对于给定的设计,不存在优化所有目标的单个解决方案时,最佳的部分解决方案属于Pareto最优解决方案集。在这项研究中,提出了一种从DoE确定最佳解决方案并通过互补使用基于TRIZ的方法来克服该最优方案的全局方法。在所提出的方法中,优化和发明方法是链接在一起的。所提出的方法旨在利用多目标优化和帕累托最优概念的数据来确定修改系统以响应更多目标的方法。所提出的方法使用了广义矛盾系统的新定义,该定义比以前的定义更加完整。该提案说明了旨在将优化与发明方法联系起来的一项全球研究项目。提出了该方法的应用,以设计一种用于加工复合材料的新型切削刀具。此外,该方法的局限性

更新日期:2021-02-15
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