Abstract
Prognostic and health management (PHM) is an approach that allows real-time health monitoring of any system. With the advancement of Industry 4.0, which integrates updated technologies, such as the Internet of Things, artificial intelligence, and automation, to optimize the efficiency, productivity, and flexibility of manufacturing processes. PHM is critical for ensuring the dependability and availability of smart factory components, which due to continuous operation, are prone to wear and tear. This paper presents a comprehensive examination of the component level-based PHM in the smart factory. It introduces PHM, smart factory and its various subcomponents. Various aspects of PHM are discussed for robotic systems, sensors, electrical machines, and auxiliary components. The paper concludes with practical recommendations for researchers interested in implementing PHM in the smart factory.
| Original language | English |
|---|---|
| Pages (from-to) | 1321-1338 |
| Number of pages | 18 |
| Journal | International Journal of Precision Engineering and Manufacturing - Green Technology |
| Volume | 12 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jul 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy -
SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Artificial intelligence
- Fault detection
- Industry automation
- Prognostic health management
- Smart factory
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