Department of Management, Faculty of Economics, University of South Bohemia in Ceske Budejovice, Studentska 13, 370 05 Ceske Budejovice, Czech Republic.
Sensors (Basel). 2021 Feb 20;21(4):1470. doi: 10.3390/s21041470.
With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems' decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper's main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.
随着现代智能工厂新技术的到来,自动化预测性维护也与生产机器人化相关。智能传感器使得获取越来越多的数据成为可能,这些数据必须经过高效、有效的分析,以支持日益复杂的系统的决策和管理。本文旨在回顾有关智能工厂中预测性维护和智能传感器的现有文献。我们专注于当代趋势,提供未来研究挑战和分类的概述。本文使用了突发分析、系统综述方法、关键词共现分析和聚类分析。结果表明,与关键研究概念相关的论文数量不断增加。随着时间的推移,预测性维护相对于工业 4.0 技术的重要性日益增加。我们提出了基于相关论文全文分析的智能和智能预测性维护 (SIPM)。本文的主要贡献是总结和概述了智能工厂中用于预测性维护的智能传感器的当前趋势。