The Future Of AI in Agile Manufacturing: Case Studies in Supply-Chain Level Issue Discovery and Diagnosis
Anna-Katrina Shedletsky, CEO, Instrumental
Manufacturing is in a state of upheaval as the optimization priorities of the past decade, which
focused on cost and just-in-time processes, are replaced with a need for agility and process
control in the face of significant ongoing supply chain disruptions. Where AI has historically
focused on predictive quality and maintenance, requiring large quantities of data and a relatively
stable process to be useful, the next generation of AI solutions must be focused on facilitating
real-time decision making and process agility. Instrumental CEO Anna-Katrina Shedletsky shares how manufacturers are leveraging AI to go beyond reactive quality control to actually proactively identify drift and anomalies throughout the supply chain by implementing comprehensive cloud data strategies and using AI to both prevent quality drift issues and provide correlations between outgoing quality anomalies and upstream factory or supplier data. Key takeaways of this presentation include: state of AI adoption and utilization among electronics manufacturers, including shifting concerns and trends in 2021; an overview of how AI can power increased agility and resiliency in electronics supply chains and especially in new product development, with case studies from Motorola and Lenovo.
Anna-Katrina Shedletsky is CEO and Co-Founder of Instrumental. As a trained mechanical engineer, Anna-Katrina saw first-hand how even Apple, the established leader in consumer electronics and supply chain, was using processes and tools that hadn’t been changed in decades. After six years at Apple shipping millions of units, she started Instrumental to fix these inefficiencies and give future generations of engineers access to the data she needed to stay ahead of schedules and the market. Today, Anna-Katrina speaks on a variety of topics including the future of electronics manufacturing, consumer electronics trends, sustainability, and D&I in manufacturing.