An empirical model for predicting energy consumption of manufacturing processes: a case of turning process

Author:

Li W1,Kara S1

Affiliation:

1. Life Cycle Engineering & Management Research Group, University of New South Wales, Sydney, Australia

Abstract

Optimizing the energy efficiency of processes has become a priority in the manufacturing sector; driven by soaring energy costs and the environmental impact caused by high energy consumption levels. The energy consumed by a machine tool performing a turning process consists of not only the energy required by the tool tip for material removal but also the energy used for auxiliary functions. Traditionally, the energy required for the cutting process is estimated based on cutting force prediction equations. However, this estimation is limited to the energy consumption of the tool tip. Thus, the aim of this paper is to develop a reliable method to predict the total energy consumption of a selected machine tool performing a turning operation. In order to compare the energy consumption under different cutting conditions, the specific energy consumption is defined as a functional unit: the energy consumed to remove 1 cm3 of material. An empirical model is obtained based on power measurements under various cutting conditions, and it is able to provide a reliable prediction of energy consumption for given process parameters. Additional investigations are conducted in order to understand and explain each coefficient in the energy consumption model.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Reference17 articles.

1. Life cycle engineering: Applying life cycle knowledge to engineering solutions

2. Cecimo. Concept description for Cecimo's self-regulatory initiative (SRI) for the sector specific implementation of the directive 2005/32/EC, 2009, available from: http://www.ecodesign-info.eu/documents/Machine_tools_VA_20Oct09.pdf accessed 1 July 2010.

3. Impact of energy efficiency on computer numerically controlled machining

Cited by 265 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3