When you hear the word “Manufacturing”, the first image that likely comes to mind is a factory filled with large machines and numerous workers. That is what manufacturing has been for decades. Since the Industrial Revolution, manufacturing has undergone significant transformation, mostly benefiting from the never-ending development of computers and software capabilities. Today, there are very few fully analog machines that you will find in a manufacturing facility, as they have all been digitized in one way or another, with low cost and accessible computing. With modern interconnected networks, internet of things (IoT) devices and the current developments in generative artificial intelligence, manufacturing is prone to a new transformation. This new model will be more distributed by nature, where manufacturing is done in local, mostly automated silos, rather than larger specialized factories that mass-produce components that would be shipped across the country or continents for assembly. By definition, distributed manufacturing is a production model that decentralizes manufacturing processes, enabling products to be designed, produced, and distributed closer to end-users.
One of the key indicators in the trend towards a distributed manufacturing world is the advancement of 3D printing technologies. Just a little over a decade ago, plastic based 3D printing was a new concept that was only useful for basic prototyping, at a high cost. Metal 3D printing was even less accessible, and machines that were being developed cost millions of dollars. These advancements have come with the developments in Computer Aided Design (CAD) software as another enabler. I attended the Rapid CTC additive manufacturing trade show in Detroit earlier this year (2025), and it was very clear that the technologies in this field are developing ‘rapidly’. There were showcases of many methods of 3D printing in both rigid materials such as metals or plastics, as well as flexible items such as rubber and other elastic materials. Furthermore, digitized manufacturing systems have the potential to unlock capabilities even beyond our planet, allowing for space manufacturing, or efficient manufacturing that would support civilization on a planet like Mars. As these new methods and processes mature and become more widely available and affordable, manufacturing decentralization will keep growing into the new norm.
The traditional supply chain model involves a significant number of wasted resources that are addressed by distributed manufacturing. From the time required to ship a product from a long distance, to shelf space being used in anticipation of it being purchased or requested, import taxes when applicable, or the fuel, environmental, and other logistical costs necessary for delivery of the product, the inefficiencies are quite obvious. In a distributed manufacturing model, the product is manufactured in very close proximity to the end user, eliminating time constraints, import taxes in most situations, shelf space as the product can be made to order, and the required logistics, as the product can be efficiently transported to the end user, or even personally picked up due to the proximity advantage. A majority of these downstream processes can be easily automated with some basic software, especially with the use of AI Agents, which are artificial intelligence entities that make decisions, and take actions autonomously to achieve specific goals. With the proper architecture, a CAD file can be digitally sent directly to a shop, where the file is reviewed by the AI agents, which would look at time, cost and other parameters, and would then send the file to a machine for printing. Additionally, AI based robotics could handle some of the more physical aspects of the process, such as material loading, retrieval of completed products, as well as packaging and shipping, which could in some scenarios require few to no humans in the loop.
What’s next with all these exciting possibilities? There are vast opportunities to build manufacturing ecosystems that would speed up production speeds, cut costs, and lower carbon footprints at a much lower barrier of entry compared to traditional manufacturing. In order to achieve this, we must look at how production data is currently handled, and find ways to digitize processes that are handled manually through technologies that are already available today. From a mechanical hardware standpoint, the starting point to digitization is with the CAD model. Transitioning from defining the final parts with a 2D print, to model based definition (MBD) takes care of some of these concerns. The more instructions and details included in the CAD file, the more streamlined the rest of the process will be. The other aspect we need to improve on is sensing devices as well as the software that collects and analyzes sensed data for robotics and other equipment, especially with AI integration, while also properly monitoring operations and maintaining security. This combination would allow highly automated processes that can be achieved in small facilities, allowing for a decentralized manufacturing supply chain ecosystem.