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Quality Management
Infosys Semiconductor practice offers comprehensive services for quality management at foundries, packaging facilities, and assembly and testing companies. Our team ensures that silicon chips produced at in-house fabs and by contract manufacturers as well as subsidiaries meet quality standards and comply with design specifications in terms of performance, power, security, and reliability. Infosys cloud-based QMS solutions capitalize on computer vision and ML-based image analytics to avoid contamination in clean rooms and storage locations, and accelerate wafer inspection. ML solutions predict post-process metrology variables, eliminate human error, and significantly reduce defective parts per million (DPPM).
Infosys solutions incorporate real-time monitoring to enforce quality mandates across production processes and wafer sizes. Our approach minimizes variance in multi-die production systems, and mitigates manufacturing defects in advanced technology nodes with high transistor densities. ML-driven techniques detect anomalies by analyzing variations in real-time tool, process and product data. In addition, ML tools undertake causal analysis of variations and recommend modifications to components, assemblies and subsystems to eliminate defects and deviations.
Infosys approach monitors the behavior of semiconductor systems across their lifetime, thereby ensuring prompt fault / failure detection. Further, AI-driven analytics facilitates in-design, in-production and in-field optimization as well as quality control. Notably, our solutions empower teams to leverage pre-silicon verification knowledge to streamline post-silicon system validation. This also reduces the effort and cost of circuit testing services.
Our automated silicon validation methodologies boost testing efficiency and quality by detecting defects early and classifying them accurately. It enables cross-functional teams to troubleshoot incidents, debug issues, and mitigate system-level failures. Significantly, our framework for rigorous testing and validation ensures compliance with global regulations for quality and product safety.
PoV: Capitalizing on digital twin technology
Semiconductor manufacturers should use digital models to reevaluate their value chains for process optimization and value realization.
Case Study
Case Study
Point of View
Point of View