Vacuum Semi Service, Edwards
Master Degree in Physics from Katholieke Universiteit Leuven (KUL) in Leuven, Belgium, in 1986.
Global Product Manager SCADA, Edwards, 2015-present
East Coast Operations Manager and Director of Product Management, AIBT, 2009-2015
Director, Implant Technology Marketing, Axcelis, 2007-2009
Senior Member of Technical Staff, Applied Materials, 1997-2007
Research Scientist, Philips Research Labs, 1986-1997
Published 90+ peer reviewed scientific journal and conference papers and holds 7 patents
Erik Collart joined Edwards in July 2015 as Global Product Manager for Edwards’ vacuum and abatement equipment monitoring, data acquisition and integrated data management platforms. He has over 30 years of experience in the semiconductor industry. Prior to joining Edwards, he held several different positions in semiconductor R&D and process development, semiconductor equipment development, and Product Management and Marketing. He has authored and co-authored well over 90 publications in peer-reviewed scientific and industry journals and proceedings and holds several patents. He graduated with a Master Degree in Physics from Katholieke Universiteit Leuven (KUL) in Leuven, Belgium, in 1986.
AI加速Sub-fab在效率及節能上的智慧化轉型 - 從真空與減排談起
Even in the most advanced semiconductor fabs today, the availability and uptime of SubFab and clean room vacuum systems are governed by run-to-crash and preventive maintenance strategies. They tend to be less efficient and cause unnecessary waste on energy, manpower, plus lower uptime and with extra spare parts consumed.
Edwards, world leader on vacuum technology, develops Predictive Maintenance (PdM) service model which tailors to the needs of sub fab to tackle the above mentioned issues through making tens of thousands of pumps and abatements in your fab intelligent. Edwards’ Predictive Maintenance strategies are empowered by Machine Learning (ML), a subfield of Artificial Intelligence (AI) and the keys to success are the combination of robust data and computer science.
Abatement is an essential equipment to reduce environmental emission in semiconductor fab. It requires regular field service resource to maintain. We developed a ML algorithm to predict equipment health which has been applied to 500+ maintenance events. Based on the algorithm & analysis, potentially 50% of the PMs were done unnecessary. AI models can help optimize maintenance effect to when it’s needed on the condition of the tools. This helps save time, resources on field service, energy and spare parts.
Another case to share is how PdM applied to dry pumps to optimize maintenance effect and avoid waste through unnecessary swaps on harsh CVD deposition process. With our ML algorithm applied, it suggests that only 35% of preventative pump swaps were shown to be timely, and 20% of the swaps happened after an unscheduled down could have been avoided and 45% of preventative swaps were shown to be too early.
Edwards is pioneering in vacuum systems ML applications by translating our extensive vacuum systems domain knowledge into mathematical models and prediction for maintenance guidance and prioritization. We continue to develop and deploy AI solutions to your subfab to help achieve fab operational excellence, lower cost, energy consumption and manpower to address the challenges of future human resource availability and increasing significance of ESG.