中国机械工程学会生产工程分会知识服务平台

期刊


ISSN0951-192X
刊名International Journal of Computer Integrated Manufacturing
参考译名国际计算机集成制造杂志
收藏年代1998～2024



全部

1998 1999 2000 2001 2002 2003
2004 2005 2006 2007 2008 2009
2010 2011 2012 2013 2014 2015
2016 2017 2018 2019 2020 2021
2022 2023 2024

2018, vol.31, no.1/3 2018, vol.31, no.10/12 2018, vol.31, no.4/6 2018, vol.31, no.7/9

题名作者出版年年卷期
Evaluation of product recyclability at the product design phase: a time-series forecasting methodologyLi, Zhi; He, Jiadong; Lai, Xinjun; Huang, Yunbao; Zhou, Tao; Barenji, Ali Vatankhah; Wang, W. M.20182018, vol.31, no.4/6
A Physical Internet-enabled Building Information Modelling System for prefabricated constructionChen, Ke; Xu, Gangyan; Xue, Fan; Zhong, Ray Y.; Liu, Diandian; Lu, Weisheng20182018, vol.31, no.4/6
An Internet of things and cloud-based approach for energy consumption evaluation and analysis for a productZuo, Ying; Tao, Fei; Nee, A. Y. C.20182018, vol.31, no.4/6
IoT-enabled real-time energy efficiency optimisation method for energy-intensive manufacturing enterprisesYang, Haidong; Wang, Wenbo; Zhang, Yingfeng; Xu, Jianxue20182018, vol.31, no.4/6
Implementation of lean manufacturing and lean audit system in an auto parts manufacturing industry - an industrial case studyDhiravidamani, P.; Ramkumar, A. S.; Ponnambalam, S. G.; Subramanian, Nachiappan20182018, vol.31, no.4/6
State space modelling carbon emission dynamics of machining workshop based on carbon efficiencyLi, Hongcheng; Yang, Haidong; Cao, Huajun; Zhu, Chengjiu20182018, vol.31, no.4/6
Special issue on smart energy efficient manufacturingZhong, Ray Y.; Yang, Haidong; Huang, George Q.20182018, vol.31, no.4/6
A process parameters selection approach for trade-off between energy consumption and polishing qualityYang, Haidong; Li, Hongcheng; Zhu, Chengjiu; Fang, Hua; Li, Jun20182018, vol.31, no.4/6
Feature-based carbon emission quantitation strategy for the part machining processZhou, Guanghui; Zhou, Ce; Lu, Qi; Tian, Changle; Xiao, Zhongdong20182018, vol.31, no.4/6
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networksLiang, Peng; Yang, Hai-Dong; Chen, Wen-Si; Xiao, Si-Yuan; Lan, Zhao-Ze20182018, vol.31, no.4/6
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