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Diagnose Yield with Metrology Basics

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Overview

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Semiconductor yield excursions demand rapid diagnosis. This course equips early-career data analysts and technicians with three core diagnostic capabilities: selecting the right electrical characterization method (I-V, C-V, continuity) for device-level failure symptoms; interpreting statistical process control (SPC) charts to distinguish random contamination from systematic process misalignment; and executing a five-step structured triage workflow to isolate root causes using data-driven reasoning and Pareto analysis. Through hands-on scenarios, learners develop the rigor and communication skills needed to serve as connectors between fab floor observations and process engineering decision-making. By the end of this course, you will be able to: - Select an appropriate electrical characterization method (I-V, C-V, or continuity) to investigate a specified leakage or open-circuit symptom. - Interpret inline inspection charts to distinguish particle contamination from pattern misalignment anomalies. - Execute a structured triage workflow to narrow root cause of a yield excursion using provided pareto and binning data. Basic understanding of semiconductor device physics (PN junctions, MOSFETs, basic I-V characteristics); familiarity with statistical thinking (trends, anomalies, data patterns); experience reading technical charts and data visualizations. Wafer fab environment experience is helpful but not required.

Syllabus

  • Selecting Electrical Characterization Methods for Device Failure Diagnosis
    • Apply knowledge of three electrical characterization techniques (I-V sweep, C-V measurement, continuity testing) to select the most appropriate diagnostic method for a given device failure symptom. Through guided practice, learners develop the judgment to match test methods to failure modes.
  • Interpreting Inline Inspection Charts to Distinguish Defect Root Causes
    • Interpret statistical process control (SPC) charts and defect-binning data to distinguish between random particle contamination and systematic pattern-misalignment anomalies. Learners develop visual pattern recognition and data-literacy skills essential for communicating defect root causes to process engineers.
  • Executing a Structured Triage Workflow to Isolate Yield Excursion Root Causes
    • Execute a five-step structured triage workflow—segment, prioritize via Pareto, map to process, design experiments, document findings—to narrow the root cause of a yield excursion. Learners apply data-driven reasoning to transform raw binning and equipment-trace data into actionable hypotheses.

Taught by

Professionals in the Industry and Ritesh Vajariya

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