According to this report from Deloitte, the global 3D printing industry is expected to reach $5.2 billion in 2020 and the largest opportunities for corporations in near future will be in home improvement and the life sciences sectors.
Yet, today there are still several hurdles in the additive manufacturing process that need to be overcome for widespread adoption in the industry.
For example, additive manufacturing involves numerous and complex variables to be monitored and controlled in the process to achieve an acceptable level of accuracy in printing. Trial and error methods for finding the correct lattice positions or design of appropriate support structures are not a sustainable or fast solution. Machine learning is currently being used to solve this problem by using generative design and testing in the pre-fabrication stage, with the aim of improving printing efficiency and cost savings. Artificial intelligence is currently finding applications in 3D printing and additive manufacturing for creating intelligent service-oriented production processes for the industry.
Agile Metal Technology Software by Sculpteo
Sculpteo is a french company which specializes provides online 3D printing services for prototyping and manufacturing. The company launched a new software suite called Agile Metal Technology at the CES 2017 and claims that the ‘Business Case’ tool in the software suite (which contains 6 tools of which only 1 is currently available at the time of writing) uses machine learning to evaluate and optimize CAD files for metal 3D printing.
According to Sculpteo, the Business Case tool takes inputs from users who want to design and manufacture a particular part in the form of CAD files and desired output parameters, and uses machine learning to evaluate if additive manufacturing would be the appropriate process for producing the part. The tool can also potentially assist in optimizing lattices in the CAD files and evaluate the most efficient printing paths.
Interestingly, the knowledge barrier threshold for 3D printing can be potentially minimized through smart 3D printing software which use machine learning and AI assistants (like Sculpeo’s offering) intending to make adoption in the industry easier although, the software is new to the market and its impacts aren’t clear at this time.”
Netfabb 2018 by Autodesk
According to Autodesk: “Generative design mimics nature’s evolutionary approach to design. Designers or engineers input design goals into generative design software, along with parameters such as materials, manufacturing methods, and cost constraints. Then, using cloud computing, the software explores all the possible permutations of a solution, quickly generating design alternatives. It tests and learns from each iteration what works and what doesn’t.”
Autodesk recently announced the launch of its first generative design product which after development as Project Dreamcatcher, has been named Autodesk generative design tool. The company launched the product as a part of their Netfabb 2018 software suite. Autodesk’s Netfabb additive manufacturing software claims to use machine learning to generate and evaluate digital models for industrial 3D printing production.
Autodesk claims to have successfully completed projects in generative design with customers like Airbus and Under Armour. […]