Engineering Performance Optimization

As advanced technology continues to evolve and the geometry keeps shrinking, the need for tighter process control and quality requirement becomes extremely challenging for manufacturing. TSMC’s unique manufacturing infrastructure is tailored to handle a diversified product portfolio, which uses strict process control to attain tightened specs and meet higher product quality, performance and reliability requirements. To achieve excellence in both quality and manufacturing, TSMC’s process control systems have been integrated with numerous intelligent functions to assist self-diagnosis, self-learning and self-reacting. These, in turn, have demonstrated remarkable results in yield enhancement, quality assurance, workflow improvement, fault detection, cost reduction and shortening of the R&D cycle.

TSMC has developed systems for precise fault detection and classification, intelligent advanced equipment control and intelligent advanced process control to monitor the manufacturing process in a timely manner and adjust conditions precisely. To achieve quality-first and ensure highly efficient and effective production, the Company has developed precision equipment matching and yield mining to minimize process variations and potential defects and excursion.

With the advent of the 5G era’s stricter quality requirements for mobile, high performance computing, automotive and the Internet of Things, TSMC has further established big data, machine learning and artificial intelligence architecture to systematically integrate foundry know-how and data science methodology in order to develop knowledge-based engineering analysis and realize engineering performance optimization.