MADE_2 - Applications of AI in Manufacturing (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

15 minutes

Proficiency:

Intermediate

Target:

Professionals

SUMMARY

This course explores the transformative applications of AI within manufacturing, including predictive maintenance, real-time monitoring, defect detection, and process optimization. This lesson delves into how AI models learn from historical data to predict machine failures, optimize supply chains, and improve production quality and efficiency.

About The Author

Carlo Ongini is the Head of Innovation at the MADE Competence Center in Milan, Italy. He holds a PhD in System and Control Automation and a master’s degree in Computer Engineering from Politecnico di Milano. With a deep expertise in Computer Vision, AI, and Machine Learning, his research focuses on their application in Automation, Robotics, and Industry 4.0.

Ongini has authored over 10 publications and a patent application. He has extensive experience across various industry sectors, having led advanced technology initiatives at Electrolux, driving intelligent automation solutions in manufacturing, and at Vodafone Business, where he managed the development of 5G and IoT solutions for industry applications. He also played a key role in Vodafone’s 5G Trials in Milan and was instrumental in the growth of Smart Robots, an Italian startup specializing in robotic and visual automation systems.

MADE is a Competence Center for Industry 4.0 created to implement Orientation, Training, and Finalization activities for technology transfer projects with companies on Industry 4.0 issues. The ultimate goal of the Competence Center is to keep the profile of companies high, competitive, and sustainable. Moreover, MADE supports manufacturing companies, especially small and medium enterprises, on the path of digital transformation to factory 4.0: smart, connected, and sustainable, by providing a wide range of knowledge, methods and tools on digital technologies.

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Learning outcomes

Identify primary applications of AI in manufacturing and how they contribute to operational improvements and innovation.
Identify practical AI applications in manufacturing and explain their value in improving productivity, quality, and flexibility in operations.
Understand how AI applications, including predictive maintenance, quality control, process optimization, supply chain management, robotics, and knowledge management systems, enhance operational efficiency, improve decision-making, and drive innovation in manufacturing.