Innovation beyond optimization: Application to cutting tool design

Abstract

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.