Proceedings of the
9th International Conference of Asian Society for Precision Engineering and Nanotechnology (ASPEN2022)
15 – 18 November 2022, Singapore

An Experimental Investigation into Anisotropic Energy Efficiency of Milling Process

Zhuo Liu1,2, Ning Liu1,a, Kaining Shi3, Biyao Qiang3, Miaolong Yuan1 and Shanshan Yang1

1Smart Manufacturing Division, Advanced Remanufacturing and Technology Centre, 3 Cleantech Loop, #01-01, CleanTech Two, 637143, Singapore

2School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

3Key Laboratory of High Performance Manufacturing for Aero Engine, Ministry of Industry and Information Technology, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China


Machining sector is one of the largest energy consumers in the world, but with relatively low energy efficiency. To achieve sustainable manufacturing, it is a prerequisite to have a comprehensive understanding of the process-specific energy consumption behavior. This study investigates the anisotropic energy consumption behavior in one of the most extensively applied machining processes, i.e., milling process. In this study, an interesting phenomenon is reported that the energy consumption behavior is highly correlated to the feed direction, clearly exhibiting the anisotropic energy efficiency performance of the milling process. To analyze this, the power model is firstly established with zero feed angle cutting experiments, following which another set of cutting experiments were performed with varying feed angles. The influence of feed angle on the energy efficiency is comprehensively studied from viewpoints of both specific energy consumption as well as cutting force coefficients. Finally, an anisotropic energy consumption model is proposed, consisting of 1) a feed angle-independent component characterizing the baseline energy consumption and 2) a feed angle-dependent component to indicate the anisotropic energy efficiency. The established model has been validated to high accuracy. Therefore, it could shed light on sustainable manufacturing topics such energy efficient machining parameter selection and toolpath planning.

Keywords: Anisotropic energy efficiency, Cutting power, Cutting force, Green manufacturing, Milling

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