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Advancing manufacturing ‘smartly’

| By Dorothy Lozowski

It is an exciting time to be involved in science and technology. Advances across many scientific disciplines are being made at an ever increasing rate. Drivers such as the urgent push toward decarbonization, global competition, the need for medical advances (as seen with the critical need for vaccine development in recent years) and an improved supply chain, along with associated governmental funding are fueling these technological advances.

One of the fastest growing areas that affects all the others, is automation. Advances in data collection and analytics, machine learning, artificial intelligence, robotics, quantum computing and more are enabling new innovations that were not possible even a short time ago. One quick example is additive manufacturing, where customized parts can now be made on demand. It struck me, for instance, in reading our Cover Story on distillation that the authors mention the possibility of fabricating metal trays by additive manufacturing for specialized applications (p. 26). This would not have been possible a relatively short time ago.


Smart manufacturing

The use of advanced and cutting-edge technologies, such as those mentioned above, to improve all aspects of manufacturing is often called “smart” manufacturing. Opportunities exist in increasing efficiency, in helping to meet sustainability goals, in improving the supply chain and much more. While many industrial manufacturers are reaping the benefits of cutting-edge technologies, such progress may be difficult for smaller companies that do not have the resources to do so. A recent report from the National Academies of Sciences, Engineering, and Medicine [1] advises that a national effort is needed to advance smart manufacturing in the U.S. The report acknowledges that moving forward with smart manufacturing requires input from a wide breadth of disciplines of science, engineering and social sciences and it recommends that the U.S. Dept. of Energy (DOE) and other federal agencies fund programs to work at the intersections of these disciplines. Specifically, the report identifies six high-demand interdisciplinary technologies where funding is recommended: 1) human-machine co-piloting; 2) sensing; 3) artificial intelligence and machine learning; 4) platforms; 5) digital twins; and 6) uncertainty quantification. The report also recommends education-focused initiatives for the manufacturing workforce, noting that manufacturers cite a lack of a skilled workforce as a leading bottleneck for implementing these emerging technologies.

The National Academies addressed the topic of digital twins in a separate recent report [ 2]. Citing the great potential that digital twins have to accelerate innovation across multiple disciplines, the report outlines recommendations for multiple federal agencies to support development of this technology.

To read how some of the latest technologies are being used in process control, see this month’s Newsfront: Process Control: Optimization at the Edge (pp. 13–16).

Dorothy Lozowski, Editorial Director






1. National Academies of Sciences, Engineering, and Medicine, Options for a National Plan for Smart Manufacturing, Washington, D.C., The National Academies Press, 2023,

2. National Academies of Sciences, Engineering, and Medicine, Foundational Research Gaps and Future Directions for Digital Twins, Washington, D.C., The National Academies Press, 2023,