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Jamie Potter | Flexciton

Jamie Potter

CEO and Co-founder

Managing Conflicting KPIs in the Diffusion and Photolithography Areas with AI-driven Autonomous Scheduling

Photolithography and diffusion remain among the most challenging areas of a fab to optimise, with many conflicting KPIs to balance. Our presentation will discuss how Flexciton’s AI-driven scheduling can handle tough scheduling challenges in these areas.

The first case study takes us to a 200mm US fab that is a large automotive supplier. The key challenge was the manual batching process at the diffusion area. Traditionally, operators made batching decisions based on the dispatching system and their best judgement. We’ll explore the outcomes of applying the AI-driven scheduler to conflicting KPIs: batching and cycle time, while additionally constrained by timelinks.

The second case study shifts our attention to the photolithography area of a leading data storage manufacturer. Photolithography is central to their operations, and as the bottleneck area, its efficiency directly influences the overall fab throughput. The challenge was to increase throughput without risking damage to auxiliary resources—reticles. Minimising the reticle movements, on the other hand, helps mitigate the risk of damage but may consequently sacrifice the fab’s fundamental objective of reducing cycle time. These KPIs are extremely difficult to optimise, but we have seen encouraging results since deploying the AI-driven scheduler.

About Jamie Potter

Jamie is passionate about solving the hardest industrial problems. For the past 10 years, he has been developing optimisation solutions for various sectors, with a focus on semiconductor manufacturing.

As an entrepreneur at heart, after spending a few years working in an industrial consultancy, Jamie co-founded Flexciton in 2016. He was initially directly involved in developing and implementing the first release of Flexciton scheduling software at the Seagate Springtown wafer fab. Along with his role as the company’s CEO, Jamie leads the commercial and operations teams. Over the past 7 years, Jamie has worked on over a dozen operational improvement projects with various semiconductor manufacturers. Jamie is a smart manufacturing enthusiast with an ambition to bring new technology to the semiconductor industry to enable new levels of efficiency.

Jamie has graduated with honours in Math from Oxford University, UK. In 2018, he was featured in Forbes’ “30 under 30 list”.