A Predictive Self-Healing Model for Optimizing Production Lines: Integrating AI and IoT for Autonomous Fault Detection and Correction

The increasing complexity of the new generation of production lines necessitates the development of intelligent, autonomous, and adaptable systems that are capable of self-diagnosis and recovery from failures and errors. A “self-healing production line” refers to a production system that integrates artificial intelligence (AI), the Internet of Things (IoT), and advanced mathematical models to identify anomalies, forecast potential failures that can occur, and implement corrective measures with minimal or no human oversight. This manuscript offers a comprehensive examination of self-healing mechanisms, encompassing IoT-enabled sensors, AI-driven predictive maintenance, and Markov Decision Processes (MDPs) for the optimization of decision-making. Also, it includes an exploration of practical implementation strategies and an automotive case study that illustrates significant enhancements in operational uptime and cost-effectiveness.

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Published
2025-06-06
DOI
https://doi.org/10.3390/engproc2025097006
Primary Topic
Digital Transformation in Industry
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article
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article

A Predictive Self-Healing Model for Optimizing Production Lines: Integrating AI and IoT for Autonomous Fault Detection and Correction

Laila El Abbadi, Salah Eddine Ayoub El Ahmadi
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Digital Transformation in Industry
article

A Predictive Self-Healing Model for Optimizing Production Lines: Integrating AI and IoT for Autonomous Fault Detection and Correction

Laila El Abbadi, Salah Eddine Ayoub El Ahmadi
article en

Abstract

The increasing complexity of the new generation of production lines necessitates the development of intelligent, autonomous, and adaptable systems that are capable of self-diagnosis and recovery from failures and errors. A “self-healing production line” refers to a production system that integrates artificial intelligence (AI), the Internet of Things (IoT), and advanced mathematical models to identify anomalies, forecast potential failures that can occur, and implement corrective measures with minimal or no human oversight. This manuscript offers a comprehensive examination of self-healing mechanisms, encompassing IoT-enabled sensors, AI-driven predictive maintenance, and Markov Decision Processes (MDPs) for the optimization of decision-making. Also, it includes an exploration of practical implementation strategies and an automotive case study that illustrates significant enhancements in operational uptime and cost-effectiveness.

Université Ibn-Tofail (MA)
Climate action
Openalex Percentile: Top 82%
Digital Transformation in Industry
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