TY - JOUR
T1 - Comprehensive Analysis of Current Developments, Challenges, and Opportunities for the Health Assessment of Smart Factory
AU - Raouf, Izaz
AU - Kumar, Prashant
AU - Khalid, Salman
AU - Kim, Heung Soo
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Korean Society for Precision Engineering 2025.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Fault detection
KW - Industry automation
KW - Prognostic health management
KW - Smart factory
UR - http://www.scopus.com/inward/record.url?scp=85217219360&partnerID=8YFLogxK
U2 - 10.1007/s40684-025-00694-4
DO - 10.1007/s40684-025-00694-4
M3 - Review article
AN - SCOPUS:85217219360
SN - 2288-6206
JO - International Journal of Precision Engineering and Manufacturing - Green Technology
JF - International Journal of Precision Engineering and Manufacturing - Green Technology
M1 - 108757
ER -
