22,900 total views
22,901 total views
3D printing has come a long way from its origins as a novelty item creator to a high-performance machine for creating complex and intricate parts. Thanks to the advent of Industry 4.0 and the digitization of the manufacturing sector, 3D printing has graduated into a data collection hub that gathers vast amounts of information about how different parts are built during the fabrication process. As connected 3D printers become increasingly sophisticated, they can use the collected data to power artificial intelligence (AI) and machine learning algorithms, resulting in more automated and data-driven decision-making processes that benefit the entire supply chain.
With the ability to connect to digital catalogs of existing parts, data-driven 3D printers can detect which specific parts are the best candidates for additive manufacturing techniques. By using machine learning, they can automatically generate tooling jigs or fixtures to hold the parts they print, eliminating the need for time-consuming manual tasks. In addition, AI is employed in additive manufacturing to detect print failures and inspect parts as they’re being printed, ensuring quality and conformance.
As manufacturers increase the quality of information collected during fabrication, and build modes of collecting data about how each 3D printed part performs on the field, the manufacturing process is approaching a fully automated “closed-loop” printing process. With a real-world manufacturing problem to solve, 3D printers can design and build a part using the specific digital fabrication technology that makes the most sense given the defined time, cost, and performance constraints.
This closed-loop automation of fabrication lifts a massive burden off manufacturers by substantially increasing their outputs and production speeds. While additive manufacturing inherently streamlines the process of building parts, the savvy application of data collected by the printers helps streamline distinct points within the additive manufacturing process. Engineers can move away from manual tasks that are now automated, and focus instead on innovating and solving more interesting problems. Meanwhile, machinists are freed up to focus on fabricating the parts that contribute the most business value, or can only be made through machining.
The benefits of data-driven 3D printing are particularly significant for the global supply chains of manufacturers, which often struggle to address ongoing disruptions in an agile manner. Just-in-time (JIT) manufacturing processes created a world of brittle supply chains that were unable to keep pace during the supply chain disruptions of the pandemic. The state of global supply chains has not meaningfully improved in subsequent years, and manufacturing in 2023 is still not for the faint of heart. However, with the introduction of federal initiatives like the U.S. government’s Additive Manufacturing Forward program, global supply chains are increasingly turning to 3D printing for fast lead times that can be delivered at points of need.
Smarter 3D printers are more precise, incorporating their closed-loop learnings to add another layer of insurance against untimely hold-ups and failures. Considering today’s labor shortages, the newer smart automation features that vendors are bringing to market will make 3D printing more attractive than ever for labor-strapped manufacturers, fueling additive manufacturing adoption, and ultimately stabilizing supply. Moreover, augmenting human decision-making in the critical problem-solving stages, and fully automating many manual processes snips off even more of part lead times, on top of the time saved from fabrication speeds and convenient point-of-need delivery.
AI’s presence in additive manufacturing has transformed the way parts are produced, with machine learning algorithms improving printing speeds and accuracy, reducing material waste, and optimizing manufacturing efficiency. The ability to automate the fabrication of parts — in a manner that is both quick and reliable — substantially increases manufacturers’ outputs and production speeds. The adoption of smarter 3D printers also provides a layer of security and flexibility, as manufacturing lines can quickly adapt to changes in demand or supply chain disruptions.
Data-driven 3D printing provides a significant boost to the efficiency and productivity of the supply chain, helping manufacturers respond more quickly and effectively to disruptions, and ensuring reliable and timely delivery of parts. As the technology continues to evolve and becomes more sophisticated, it’s clear that the future of manufacturing lies in the application of data-driven AI and machine learning algorithms to optimize and streamline the production process. By embracing this trend and investing in the latest technology, manufacturers will be ready for the future.
Author: Doug Kenik