• Transformed semiconductor wafer quality management by unifying NCR, MRB, and CAPA(8D) onto a single platform with automation — eliminated quality escapes, increased CAPA completion rates, and recovered 15+ engineering hours weekly previously lost to Excel tracker maintenance.

• Developing supervised machine learning models for detecting a critical reliability defect (electrical short), integrating it with SPC and interactive dashboards for rapid response.

• Developed a RAG-based chatbot using open-source LLMs (LLama) to interact with quality records (NCR, MRB, 8D, etc.), streamlining information retrieval and improving accessibility.

• Automated QA teams's 3 daily tasks (workflow) with custom-built web apps (Python, Flask, JavaScript, React) cutting manual work by 8+ engineering hrs/week.

• Engineering interactive Tableau dashboards that transformed KPI monitoring from manual reporting to real-time analytics, enabling data-driven decisions, and reclaiming 4 engineering hours weekly.

• Implementing unsupervised (clustering) anomaly detection on semiconductor manufacturing parametric data to identify outlier wafers.

• Developed foundational quality control systems (PFMEA, Control Plans, Inspections, SPC) for a battery energy storage system (BESS) for two product lines (power conversion & battery pack). Championed quality issues during launch and led a successful ramp-up for both lines.

• Solved the company’s biggest customer issue—battery leaks—by implementing a two-factor Design of Experiments (DOE) to validate root causes and developed effective PCAs collaborating with cross-functional groups, reducing the battery leak failure rate to 0%.

• Trained an ML classification model to automatically classify (~ 80% accuracy) operator-entered MES defects into 4M (Man, Method, Machine, Material) categories providing real-time analytics.

• Developed 4 top-of-class Tableau dashboards to monitor key quality metrics - Torque, NCR, Battery Test, Cpk and provide real time email alerts.

• Joined as the first QE in the team. Engineered foundational quality control measures for a $400M battery material manufacturing facility, ensuring a seamless launch and robust production handoff.

• Led APQP activities (Product Quality Plan) from scratch to finish by deploying PFDs, PFMEAs, control plans, SOPs, records of material, qualified lab documentation, MSA studies, packaging specifications, and initial process capability studies.

My time at Redwood was short-lived due to changing geographies, but it provided an immense learning experience.

• Led the development of a window seal trim supplier process capability by identifying and verifying root causes through an on-site visit and implementing corrective actions that included standardizing work and adding more detection controls.

• Conducted a comprehensive 10-vehicle door attribute study and used statistical analysis to implement corrective actions that improved door gap and flush measurements from 60% to 85% on-spec at the R1T Bodyshop/Closures station.

• Validated ultrasonic weld inspection tool for assembly line use through linear regression and Gauge R&R, statistically comparing it against destructive testing to confirm its efficacy, thereby reducing inspection time and cost by 90%.