This course offers a foundational overview and hands-on experience with the technologies of Industry 4.0—the Fourth Industrial Revolution. Participants will begin by exploring patterns and lessons from previous industrial revolutions to better understand the context and challenges of Industry 4.0. The course then transitions into discussions around I4.0 technologies—such as sensors, data analytics, and automation—and how these technologies interconnect to enable digital transformation. Cultural considerations and change management strategies for implementing I4.0 in factories will also be addressed.
Two hands-on lab activities during the training will reinforce learning:
- Lab 1: Setup and experimentation with a Raspberry Pi with a temperature sensor to collect and store data.
- Lab 2: Hands-on coding experience for data analytics with the use of Google Colab to process and visualize data from Lab 1 and additional big data sets.
By the end of the course, learners will have a practical understanding of the definitions of I4.0 technologies and how digital transformation is enabling smarter, more efficient, and connected manufacturing operations. No prior technical background or coding experience is required; however, laptops with internet access are necessary for participation in the second lab.
8:30 AM – 3:30 PM CENTRAL TIME daily
Course Instructor:
David Blondheim, Director, Global Operational Excellence and Advanced Manufacturing, Mercury Marine
David Blondheim is an engineer with a blend of academic and hands-on manufacturing experience. He holds a B.S. in Mechanical Engineering, an MBA, an M.S. in Industrial Engineering, and his Ph.D. in Systems Engineering, specializing in high-pressure die-casting data systems and machine learning applications. He has spent his 20+ year career in manufacturing, currently working at Mercury Marine as Director, Global Operational Excellence and Advanced Manufacturing. Dave is passionate about Industry 4.0 technologies, focusing on data connectivity, collection, and advanced analytics through machine learning. He is committed to leveraging data to drive change and enhance manufacturing processes.