Jim Davis
UCLA Vice Provost Emeritus
CESMII Program Oversight & Principal Investigator
Sthite Bom
Vice President
Seagate Technology
Twelve semiconductor fab operators have taken first steps toward a new business model for AI/ML with cross-company data aggregation for mutual competitive benefit. The full value of AI in manufacturing will require new business models centered around the value of data and the recognition that they derive their power from gathering data at scale to generate network effects. Cooperative engagement by small and medium sized manufacturers on AI/ML for operational productivity is a pathway to learn, scale, and draw value from data accumulated from years of experience on common problems; derive new insights on factory operations and products; lower many of the costs of entry; and attract more investment on industry specific challenges. There is line of sight to interconnectedness, network effects, and a manufacturing web as illustrated below in the NIST Report.
Sthitie Bom, Seagate Technology and I (UCLA and CESMII), as co-leaders, offer some important lessons from our experiences.
- Start by making a commitment to provide data a requirement for company participation. Participants agreed upfront that harvesting the value of currently unused operational data could potentially provide a fast and low-cost pathway to near-term benefit.
- Build alignment across business motivations…