A Survey on Machine Learning based Smart Maintenance and Quality Control Solutions

IF 0.9 Q4 TELECOMMUNICATIONS
Attila Frankó, P. Varga
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引用次数: 4

Abstract

Machine learning aided tasks and processes have key roles in smart manufacturing, especially in controlling production and assembly lines, as well as smart maintenance and intelligent quality control. The last two ones are those tasks that nowadays are still performed manually by employees; however, there are numerous machine learning-based solutions that can automate these fields to optimize cost and performance. In this paper, we present an overview of smart manufacturing ecosystem and define the roles of maintenance and quality control in it. Up-to-date machine learning-based smart solutions will also be detailed while addressing current challenges and identifying hot research topics and possible gaps.
基于机器学习的智能维护和质量控制解决方案综述
机器学习辅助任务和流程在智能制造中发挥着关键作用,特别是在控制生产和装配线,以及智能维护和智能质量控制方面。后两种任务现在仍然由员工手工完成;然而,有许多基于机器学习的解决方案可以自动化这些领域,以优化成本和性能。本文概述了智能制造生态系统,并定义了维护和质量控制在其中的作用。最新的基于机器学习的智能解决方案也将详细介绍,同时解决当前的挑战,并确定热点研究课题和可能的差距。
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
Infocommunications Journal
Infocommunications Journal TELECOMMUNICATIONS-
CiteScore
1.90
自引率
27.30%
发文量
0
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