Energy Saving Design of Gear Hobbing Machine Based on Analytical Target Cascading: Modeling, Decomposition, and Independent Optimization

Design parameters optimization is regarded as an effective way to reduce energy consumption of a machine tool, which are contributed by several subsystems with coupling relationships affecting the total energy consumption. Therefore, it is of importance to study the coupling relationships between subsystems at the design stage for energy saving. However, there are multiple key energy consuming subsystems associated with various design parameters, leading to a complex optimization model of this problem. It is rather time-consuming to optimize such a complex model and hard to obtain global optimal results. To address this challenging problem, this article proposes an energy saving design approach of a gear hobbing machine based on Analytical Target Cascading (ATC) method. Firstly, the energy consumption models of each subsystem are established and the coupling relationships are analyzed. Then, the decomposition of the energy coupling model is conducted and the comprehensive optimization model is constructed by ATC. One novel adaptive sequential sampling method is proposed with the surrogate model to achieve the collaborative optimization of both structural parameters and control parameters. Finally, three optimization algorithms are developed to comparatively study the energy-optimal schemes. Testing results indicate that the energy consumption can be reduced by 9.72%, with lighter moving component and reduced deformation.Note to Practitioners—This article provides one method for the energy saving of the gear hobbing machine at the design stage. Previous studies only focus on the influence of one design factor on energy consumption, and the optimization is under a mixed optimization model, which is hard to obtain global optimal results. This article develops an energy saving design method considering the comprehensive influence of design factors for energy saving of multiple subsystems. Based on ATC, an energy coupling model can be divided into several energy consuming subsystems and the independent optimization of each subsystem can be achieved. To ensure the lightweight and control abilities, a surrogate model and a novel sequential sampling method are applied. Results show the effectiveness of the proposed method and the energy reduction can be achieved with a good structural and control performance.