ASML: Accelerating Microchip Manufacturing with Google Cloud AI and Machine Learning

• Analytics & Modeling - Machine Learning
• Infrastructure as a Service (IaaS) - Cloud Computing

• Education
• Equipment & Machinery

• Predictive Maintenance
• Tamper Detection

• Cloud Planning, Design & Implementation Services
• Training

ASML, a global leader in the semiconductor industry, faced a significant challenge with its new breed of machine learning product. The product, designed to predict process performance per device layer, needed to train itself due to frequent changes in device layer and manufacturing processes. Furthermore, the product had to monitor its own accuracy and retrain accordingly without any connection to ASML. The company needed a powerful, secure platform for building AI-driven products to meet customer demands. However, the semiconductor industry had been resistant to cloud solutions due to fears of compromising security in a field where intellectual property protection is critical.

ASML is a Dutch firm that has grown into a global leader in the semiconductor industry. The company's machines enable giants such as Intel, Samsung, and TSMC to mass produce patterns on silicon that make up the integrated circuits that are reinventing our world. ASML's photolithography technology touches most people's lives, whether they realize it or not, through smartphones, medical devices, and visions beamed from the Hubble telescope. The company commands 85% of the global market in lithography machines that expose device patterns on silicon wafers using ultraviolet light.

ASML found its solution in Google Cloud. The company partnered with Google Cloud Partner Rackspace to implement the architecture and extend its secure environment into the cloud, a process completed within weeks. ASML also collaborated with machine learning specialist ML6, which provided Google Cloud experts to train staff on products such as BigQuery, Google Kubernetes Engine, and Cloud Datalab. The transition to Google Cloud has been transformative for ASML, significantly reducing time spent on data parsing and preprocessing, and improving overall engineering efficiency. Google Cloud also provided enhanced security measures, assuaging fears of compromising intellectual property.

• The transition to Google Cloud has been transformative for ASML. The company has seen significant improvements in engineering speed, security, time to market, and competitive advantage. The move has also inspired data scientists with open-ended Google Cloud collaboration and DevOps with Cloud Build and Kubernetes architecture. ASML has been able to make a powerful case to clients about Google Cloud security advantages through its own example. The company is now exploring ways to be a beta tester for the Google Brain Team deep learning initiative, further strengthening its partnership with Google Cloud.

• Shortened product release cycles from monthly to biweekly

• Saved four hours per day in data querying by ending the need for data parsing and preprocessing

• Reduced encryption, build, and test time from hours to just 10 minutes