How Additive Manufacturing Has Been Energized by AI and Machine Learning

When the COVID 19 pandemic hit, global supply chains came to a standstill, all but halting production lines. Manufacturing companies turned to 3D printers, combined with artificial intelligence and machine learning, to create a new wave of digital engineering and manufacturing.
According to the Wohlers Report 2021 the additive manufacturing industry grew despite the COVID-19 pandemic expanding by 7.5% nearly $12.8 billion in 2020. While the equipment sales saw a decline, the manufacturing of 3D printed parts rose dramatically to battle the pandemic and overcome supply chain disruption.
The recent Additive Manufacturing Trend Report 2021 from 3D Hubs determined a 34% increase in engineering firms using 3D printing to produce functional and use parts in 2020 compared to 2019. According to the report, the largest increase was seen in biotechnology, transportation, and automotive.
GE has invested over $3 billion in additive manufacturing processes and uses it in many of its products including jet engines, medical devices, and home appliance parts. The company's GE NX jet engine was manufactured using an advanced technique called direct metal laser melting. Boeing's Dreamliner. 787 is the first commercial aircraft to fly using parts made with 3D printing technology, resulting in around two to $3 million savings per plane.
3D printing has become invaluable for manufacturers when producing on demand spare parts, resulting in less operational downtime and significant cost savings. In February 2020, Etihad Airways formed a partnership with the German mechanical engineering firm, BigRep to install their edge 3D printer at its facility in Abu Dhabi. This made it possible to print both flying and non-flying parts on demand. 3D printing is shifting the manufacturing of expensive medical equipment to a lower cost point and with higher precision in the medical field. For example, the open hand project used AM technology to produce prosthetic hands for just 1000 US dollars, with the price of the units otherwise going up to 100,000 US dollars.
From online ordering, part design, build preparation, production planning and delivery, 2020 saw an increase in digital engineering as many were forced to work remotely. As a result, companies realize the investment needed in IoT and industry 4.0 solutions. Many of the current AM software processes are inefficient and create production gaps. For both material costs and software processes. Artificial intelligence can be a solution.
Generative design, the ability for computer aided design programs to produce parts autonomously and organically, has already seen increased adoption among part manufacturers. AI and machine learning can accelerate generative design by designing parts free of traditional manufacturing restrictions.
AI can provide inspection benefits for AM systems in the hardware space to ensure greater process control and repeatability. AI can use pattern recognition to form best practices for error handling. AI driven hardware can spot defects in part production and report it to the cloud. Workers on the line immediately pulled the defective units before reaching final assembly, saving time and money on recalls and repairs.
The use of artificial intelligence and additive manufacturing can cut the production time of 3D printed parts from 30 minutes to mere seconds per individual job. AI can increase printer utilization, optimize the material selection, reproduce production errors, and catch production defects along the way.
Additive manufacturing today requires a high degree of specialized knowledge and highly trained engineers to be executed correctly. AI can help engineers ensure the rules of 3D printing are followed and helped produce large amounts of data along the production process. By providing automated assistance. Additive Manufacturing enhanced by AI can be the manufacturing solution of the future.
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