Autonomous Maintenance, one of the cornerstones of Total Productive Maintenance (TPM), is undergoing a revolution thanks to the integration of artificial intelligence (AI) agents and automation technologies. This process, which initially focused on self-management by operators to oversee and care for machines, has evolved to leverage digital tools that enhance efficiency, reduce errors, and transform labour relations in modern industry.

The automation of tasks through artificial intelligence is deeply linked to autonomous maintenance. Technologies such as the Internet of Things (IoT), machine learning, and predictive diagnostic systems have transformed repetitive and manual inspection tasks into automated and more precise processes. AI agents play a critical role by monitoring equipment in real time, identifying wear patterns, and predicting failures before they occur. This not only increases system reliability but also enables operators to concentrate on higher-value activities.

The implementation of these technologies is transforming the role of operators in autonomous maintenance. Traditionally, these tasks required a high degree of manual intervention, but workers now need to acquire advanced technological skills to interact with digital systems and intelligent agents. Training in data analysis, the use of digital platforms, and the interpretation of predictive algorithms has become a critical necessity. This transition also entails a significant cultural shift. Resistance to change, fuelled by fears of job obsolescence, must be addressed with clear communication and an emphasis on the complementary value of artificial intelligence.

Collaboration between humans and machines not only benefits industrial operations but also increases employee engagement. By eliminating repetitive tasks and providing tools that enhance safety and accuracy, workers can focus on more challenging and rewarding activities. This approach helps create a more satisfying work environment, where operators feel valued and recognised as key contributors to the organisation’s success.

Labour relations are also evolving in this new context. Supervisors are no longer merely task managers but facilitators of digital transformation. They need to develop leadership and change management skills alongside advanced technical competencies. This shift in workplace dynamics demands effective communication to foster collaboration between human teams and automated systems, ensuring a smooth and effective transition to a hybrid working model.

In conclusion, the integration of artificial intelligence into autonomous maintenance represents an opportunity to profoundly transform the industry. By optimising processes, improving productivity, and fostering a more collaborative and technology-driven work environment, these technologies can redefine labour relations and business competitiveness. However, it is crucial to maintain a people-centred approach, prioritising training, cultural change, and communication to maximise the benefits of this technological revolution.

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