SBIR Phase I: An artificial intelligence system for autonomous numerical control programming for advanced manufacturing

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The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to address the challenge of reshoring manufacturing given the technical skills gap crisis in the U.S. by helping increase the productivity of precision machinists and sparking greater interest in the field of precision manufacturing among new workforce entrants. Computer Numerical Control (CNC), the computer-automated management of machining tools’ operations, is a key process in precision manufacturing. Programming CNC machines requires professionals with vast and specialized technical skills. With fewer graduates of trade schools, CNC programming know-how has become a bottleneck to manufacturing operations, creating an urgent unmet need for a radically simplified and automated CNC programming workflow to improve accessibility to precision manufacturing. This project aims to develop an artificial intelligence tool to automate the CNC programming process, thereby helping ease the CNC programming bottleneck and fill the skills gap at reduced manufacturing time and costs. This project will expand research on the use of Artificial Intelligence (AI) for generative CNC programming in precision manufacturing. AI has the potential to automate various steps in the CNC programming workflow; however, this research has been limited to constrained machining conditions and has not focused on optimization procedures, thereby limiting its real-world applicability. This project expands this research to develop a commercially viable solution for the optimal cutting tool and machining parameter selection stage of CNC programming. Briefly, this project will address technical challenges of algorithm development and optimization to improve accurate selection of tool and machining parameters. The results will be validated on CNC machines. At the end of Phase I, a proof-of-concept solution will be developed to automate the optimal cutting tool and machining parameters selection for CNC drilling and milling.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.