Despite concerns that new technologies will displace workers, the more common outcome is that they transform the jobs we do—and how we do them. The question is: how can we use these technologies to make work more enjoyable and more productive? Drawing on historical examples and recent data, MIT’s Ben Armstrong will outline strategies and opportunities for “positive-sum automation” that benefit both firms and workers. 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.