Data Analytics in the Smart Factory - Digital Twins to Real Time Control José J. Pacheco CoDirector, MIT Advanced Manufacturing and Design Program (MIT AMDP)
Brian will describe the initial research collaboration between MIT Sloan HSI and Amwell Silvercloud, utilizing health analytics to enhance engagement and effectiveness.
In a rapidly expanding digital marketplace, how can we stay on top of rapid - and sometimes radical - change? How can we position our organizations to take advantage of new technologies? How can we track and combat the security threats facing all of us as we are swept forward into the future?
The manufacturing industry is undergoing a major transformation, shifting from automated to autonomous operations. This change promises to speed up the process of turning ideas into real, market-ready products. The key to making this happen is the integration of digital technologies, including sensors, data, computing power, and information systems.
At the heart of this shift are digital twins—virtual models that represent not just the products but also the materials, manufacturing processes, supply chains, and production lines. These digital replicas allow manufacturers to simulate, monitor, and improve operations in real-time using sensor data. By combining physical and digital worlds, digital twins help bridge the gap between designing a product and bringing it to life. When digital twins are combined with real-time control systems and machine learning, factories become smarter and more adaptive. Real-time data flows from sensors to digital models and ML algorithms, enabling predictive maintenance, reducing waste, and optimizing production. This connected ecosystem creates a highly efficient, data-driven manufacturing environment. We’ll explore real-world examples of these technologies in action and how they are shaping the future of manufacturing today.