Industrial Internet of Things (IIoT) enabled predictive analytics have enabled the manufacturing sector to transition from reactive to proactive maintenance. This article discusses the use of predictive analytics in the IIoT field of preventive maintenance. The objectives consist of increased output, availability, and decreased malfunctions-research on preventive maintenance cast light on its evolution. The proposed work presents a framework for IIoT data acquisition, cleansing, feature selection, and analytical processing. Experiments and case studies validate the methodology. Utilizing predictive analytics for routine maintenance can improve the effectiveness and productivity of machinery. Data integrity, model consistency, and scalability must be resolved before implementation. The proposed work's findings and recommendations have significant implications for future research into predictive analytics for proactive maintenance in IIoT systems and for industry practitioners.
Predictive Analytics for Proactive Maintenance in Industrial IoT Applications
22.11.2023
391528 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
IuD Bahn | 2009
|Online Contents | 1996
|Track Maintenance - Applying proactive maintenance on CTRL
Online Contents | 2003
Reactive to Proactive Maintenance Journey
SAE Technical Papers | 2016
|