Challenge
Semiconductor manufacturing demands exceptional precision and consistency across every stage of wafer fabrication. For a global semiconductor manufacturer, variability across critical processes, including deposition, etching and lithography, was affecting production yield, process stability and overall manufacturing efficiency.
Variations in chamber temperature, gas flow, pressure and other operating parameters made it difficult to maintain consistent process conditions. Differences between fabrication tools further complicated troubleshooting, contributing to higher-than-target defect rates and inconsistent performance.
Without a unified view of process behaviour, engineers struggled to identify the root causes of yield loss. Traditional manual experimentation and fragmented equipment data made it time-consuming to determine optimal operating conditions and replicate improvements across production lines.
Solution
The manufacturer implemented an integrated continuous improvement approach using Takt Kaizen, Takt Insight and Takt Optima to transform process variability into actionable operational intelligence.
Identifying critical process variation with Takt Kaizen
The engineering team used Takt Kaizen to map the complete wafer fabrication process, from front-end deposition, etching and lithography through to back-end operations.
Value stream analysis helped identify critical sources of variability, including temperature drift, gas flow fluctuations and differences between fabrication tools. This established a structured foundation for prioritising improvement opportunities and understanding their impact on defect rates and yield.
Connecting process data with Takt Insight
Takt Insight was deployed across key fabrication equipment to capture and analyse real-time operational data from legacy and modern tools.
The platform brought together chamber temperature, pressure, RF power, gas flow and cycle-time information, enabling engineers to monitor equipment performance and correlate operating conditions with defect signatures and yield loss.
This unified visibility helped the team understand process behaviour and identify the parameters contributing most significantly to manufacturing variation.
Optimising process conditions with Takt Optima
Using Takt Optima, the engineering team conducted AI-powered design of experiments to determine optimal combinations of process parameters.
By analysing variables such as RF power, gas ratios, chamber temperature and pressure, the team identified robust operating windows designed to maximise wafer yield while minimising defects.
Experiments that previously required weeks of manual effort were completed in a fraction of the time, allowing engineers to identify optimal recipes and transfer improvements more efficiently across fabrication tools.
Results
By combining structured process improvement, real-time operational intelligence and AI-driven optimisation, the manufacturer achieved measurable improvements in wafer fabrication performance.
12% Higher Wafer Yield
Improved process control and optimised operating conditions increased wafer yield by 12%, enabling more consistent production of high-quality semiconductor wafers.
45% Reduction in Defect Rate
Better understanding of process variability and the identification of robust parameter settings contributed to a 45% reduction in defects.
80% Faster Recipe Optimisation
AI-powered experimentation significantly accelerated the identification of optimal process conditions, reducing the time required for recipe optimisation by 80%.
Improved Manufacturing Efficiency
The manufacturer also reported lower energy consumption per wafer, improved equipment utilisation and reduced downtime.
Beyond these measurable improvements, the engineering team gained a repeatable, data-driven approach to continuous improvement. Optimal process recipes can now be transferred more efficiently between fabrication tools, helping the manufacturer scale improvements, reduce cost per wafer and support more sustainable semiconductor manufacturing.