Cutting Path-Associated Energy Consumption of Milling Machining Process

Manufacturing industries face numerous challenges, such as reducing their energy consumption. Minimising energy usage is one of the initiatives towards sustainable manufacturing. Many researches have studied the surface quality of machined part, but studies on energy consumption during machining pro...

Full description

Bibliographic Details
Published in:IOP Conference Series: Materials Science and Engineering
Main Author: Rahman Hemdi A.; Md Ali U.F.; Mohamed Noor R.; Irwan Yahaya M.; Mahadzir M.M.; Faiz Zubair A.; Othman M.; Yola M.; Mat Saman M.Z.; Sharif S.
Format: Conference paper
Language:English
Published: IOP Publishing Ltd 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098893417&doi=10.1088%2f1757-899X%2f1003%2f1%2f012071&partnerID=40&md5=f9c0934e6e24e1bb9d9772e8b8bc310f
Description
Summary:Manufacturing industries face numerous challenges, such as reducing their energy consumption. Minimising energy usage is one of the initiatives towards sustainable manufacturing. Many researches have studied the surface quality of machined part, but studies on energy consumption during machining process are limited. Different cutting paths operations may influence energy consumption during machining. The objective of this research was to investigate the effect of cutting tool paths and parameters on energy consumption during machining. Aluminium 6061 alloy was face-milled using high-speed steel tool with different tool paths, namely, morphed spiral, parallel and spiral paths. The design of experiment technique was applied to optimise the experimental work, and response surface methodology was used to analyse the experimental result. Results showed that feed rate is the most influential parameter on the energy consumption of machining. Machining energy models were also generated for morphed spiral, parallel and spiral cutting paths. The R 2 of each model was higher than 0.92, which indicates that the model equations are applicable in predicting the energy consumption of a milling operation. © Published under licence by IOP Publishing Ltd.
ISSN:17578981
DOI:10.1088/1757-899X/1003/1/012071