Yield Data Analytics & AI Applications for Semiconductor Manufacturing
With increased computational capabilities, the importance of artificial intelligence (AI) and machine learning (ML) in semiconductor manufacturing is ever growing.
While there are already many reported use cases of how AI can be applied in areas such as wafer scheduling and dispatching, unit process optimization and defect classification, the application of AI looks especially promising in the field of yield data analytics.
In order to analyze the vast amounts of data coming from the test equipment of semiconductor manufacturers, a premium, powerful software solution is required. High-performing software is a must as it enables fast and efficient processing of massive amounts of data.
As companies in the semiconductor industry strive to achieve manufacturing excellence, using yield analysis software allows test and yield engineers to improve yield and throughput, significantly increase productivity, save costs, reduce waste and reduce time-to-market.
The main stages in effective yield data analysis include: obtaining the data from semiconductor equipment, data integration, data analysis and obtaining the information needed for further actions. The knowledge gained results in the lifetime quality and reliability of the smart products that shape our lives.
The AI Layer to get the Most Out of Your Semiconductor Data
Artificial Intelligence A deep learning framework based on neural networks (CNNs & GANs) and other intelligent algorithms.
Smart Pattern Recognition Profit from automatic pattern recognition and classification.
Intelligent Tool Analytics Analyze tool combinations and pinpoint process improvement possibilities.
Multidimensional View Improve your operation through multivariate data monitoring.
Deep Root Cause Analytics Smart root cause analysis enables immediate implementation of corrective measures.
Smart Decision Making Data driven decision-making leads to substantial productivity gains.
The multivariate monitoring feature of YWDXI allows you to review individual parameters and detect issues that would otherwise not be visible. Fast processing and calculation times are ensured by deploying mechanisms such as dimension reduction. Built-in Principal Component Analysis enables you to set corrective measurements immediately.
DR YIELD is the provider of YieldWatchDog and YieldWatchDogXI – smart, powerful data analysis and AI solution specifically designed for the semiconductor industry.
DR YIELD is headquartered in Austria, with a team of dedicated, experienced engineers providing outstanding customer support from demo to data integration, customization, license renewal and beyond.
DR YIELD’s Success:
DR YIELD’s YieldWatchDog (YWD) software allows one to quickly identify yield issues and correlate test results from WAT/PCM, Wafer/Die Sort and Final Assembly/test, all within one tool. Hundreds of world-wide customers use (YWD) to improve yields, reduce test times, and help to get products to market faster while improving the bottom line. Most importantly, performance does not get bogged down as the volume of data grows, so it remains fast at finding wafer signatures regardless of the number of wafers in the database.
At SEMICON West 2022, DR YIELD will present the importance of AI and machine learning in semiconductor manufacturing with a focus on yield data analytics.
CURRENT AI APPLICATIONS: Three AI applications currently being used in yield data analytics will be presented using actual recent fab data.
The future outlook includes the technology roadmap for the application of AI for comprehensive semiconductor analytics to the end of the decade.
We look forward to hearing from you.
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