Sequencing the features to minimise the non-cutting energy consumption in machining considering the change of spindle rotation speed

Hu, L., Liu, Y. , Lohse, N., Tang, R., Lv, J., Peng, C. and Evans, S. (2017) Sequencing the features to minimise the non-cutting energy consumption in machining considering the change of spindle rotation speed. Energy, 139, pp. 935-946. (doi: 10.1016/j.energy.2017.08.032)

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Abstract

A considerable amount of energy consumed by machine tools is attributable to non-cutting operations, including tool path, tool change, and change of spindle rotation speed. The non-cutting energy consumption of the machine tool (NCE) is affected by the processing sequence of the features of a specific part (PFS), because the plans of non-cutting operations will vary based on the different PFS. This article aims to understand the NCE between processing a specific feature and its pre- or post- feature, especially the energy consumed during the speed change of the spindle rotation. Based on the developed model, a single objective optimisation problem is introduced that minimises the NCE. Then, Ant Colony Optimisation (ACO) is employed to search for the optimal PFS. A case study is developed to validate the effectiveness of the proposed approach. Two parts with 12 and 15 features are processed on a machining centre. The simulation experiment results show that the optimal or near-optimal PFS can be found. Consequently, 8.70% and 30.42% reductions in NCE are achieved for part A and part B, respectively. Further, the performance of ACO for our specific optimisation problem is discussed and validated based on comparisons with other algorithms.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Liu, Dr Ying
Authors: Hu, L., Liu, Y., Lohse, N., Tang, R., Lv, J., Peng, C., and Evans, S.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Energy
Publisher:Elsevier
ISSN:0360-5442
ISSN (Online):1873-6785
Published Online:13 August 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Energy 139: 935-946
Publisher Policy:Reproduced under a Creative Commons License

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