Real-Time Maintenance Optimization with Industrial Internet of Things
Source abstract
Abstract
Efficient maintenance management is critical to ensuring the reliability and productivity of industrial systems. This article explores how the Industrial Internet of Things (IIoT) enables real-time maintenance optimization through data-driven decision-making. IIoT technologies, such as connected smart sensors and predictive analytics, provide continuous monitoring of equipment performance and state. Within the frame of this article, a novel mathematical model is proposed to support the real-time optimization of maintenance operations in production systems. The model makes this possible by using real-time state information to optimize maintenance operations, minimize maintenance costs, and maximize the efficiency of the production system. The results highlight the potential of IIoT to transform conventional maintenance strategies into dynamic, adaptive systems. This research contributes to advancing smart maintenance solutions for modern industrial applications.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Reliability and Maintenance Optimization · Fault Detection and Control Systems · Quality and Safety in Healthcare
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Logistics, University of Miskolc, 3515 Miskolc, Hungary
References (23)
Show source-provided references
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