Jim Davis
Vice Provost Information Technology & Chief Academic Technology Officer, UCLA
AMPc Wednesday Luncheon Keynote: Strategy for Resilient Manufacturing Ecosystems through Artificial Intelligence (AI)
Presented by:
Jim Davis, Professor Chemical & Biomolecular Engineering, UCLA
The National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST) have sponsored a three-workshop Symposium to comprehensively address the role of AI in U.S. manufacturing competitiveness and to recommend a roadmap for accelerating AI adoption throughout U.S. based manufacturing. The symposium has focused on AI adoption that is synergistic with and builds on manufacturing digitalization (a.k.a. Smart Manufacturing, Industry 4.0, Digital Manufacturing, Manufacturing 4.0). Manufacturing practitioner, industry coalition, Manufacturing USA Institute, government program, academic, AI/ML application, IT, computer science, and federal agency experts were convened through roundtables to address targeted questions about a national strategy. U.S. competitiveness was defined in terms of four national advanced manufacturing priorities: (1) manufacturing ecosystem resilience; (2) global competitiveness and economic market share; (3) addressing environmental sustainability, GHG emissions, decarbonization, and energy and material consumption; and (4) national cyber and data security and opportunity with trust, privacy, and ethics for a much broader, more diverse, and more involved manufacturing and workforce base.
Workshop 1, held in December 2020, identified the necessity of an industry strategy. Workshop 2, conducted in July 2021, identified the most important research, development, and workforce education and training priorities for industry-wide adoption. Workshop 3, held in January 2022, recommended a roadmap that organizes program strategies as a comprehensive industry, academic and government partnership. The roadmap centered on three primary goals: (1) enable the digitalization of small and medium manufacturers, (2) incentivize AI throughout established supply chains, and (3) enable new business models.