RETRACTION: Prediction of energy consumption of numerical control machine tools and analysis of key energy-saving technologies

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
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引用次数: 0

Abstract

RETRACTION: H. Qiang, M.A. Ikbal, S. Khanna: Prediction of energy consumption of numerical control machine tools and analysis of key energy-saving technologies. IET Collaborative Intelligent Manufacturing 3, no. 3, 215–223 (2021). https://doi.org/10.1049/cim2.12001.

The above article, published online on 1 February 2021 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editors-in-Chief; Liang Gao and Weiming Shen; the Institution of Engineering and Technology; and John Wiley & Sons Ltd.

This article was published as part of a guest-edited special issue. Following an investigation, the IET, John Wiley & Sons Ltd and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the corresponding special issue underwent systematic manipulation. Furthermore, the manuscript contains various logical flaws as well as unrelated references that do not support the scientific statements made. Accordingly, we cannot vouch for the integrity or reliability of the content and have taken the decision to retract the article. The authors have been informed of the decision to retract.

摘要:数控机床能耗预测及关键节能技术分析
强h, M.A. Ikbal, S. Khanna:数控机床能耗预测及关键节能技术分析。IET协同智能制造第3期3, 215-223(2021)。上述文章于2021年2月1日在Wiley在线图书馆(wileyonlinelibrary.com)上发表,经主编同意撤回;高亮,沈伟明;工程技术学会;约翰·威利&;这篇文章是作为特刊的一部分发表的。经过调查,IET, John Wiley &;Sons Ltd和该杂志已经确定,该文章没有按照该杂志的同行评议标准进行评议,并且有证据表明相应特刊的同行评议过程受到了系统的操纵。此外,该手稿包含各种逻辑缺陷以及不支持所作科学陈述的不相关参考文献。因此,我们不能保证内容的完整性或可靠性,并已决定撤回该文章。作者已被告知撤稿的决定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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