Statistical Analysis
Statistical Analysis in Semiconductor Manufacturing
Leading in Quality & Innovation
In semiconductor manufacturing, perhaps the most crucial step once the hardware and software have been developed is to test chips for any defects, before they are ready for release to the market. Chips are developed with many challenges and steps along the way, and it is inevitable that with all the processes involved, irregularities are going to pose a challenge. Here at Zener Engineering, we bring our vast amount of experience and expertise by using statistical analysis to identify microscopic issues, such as thermal warping, particle contamination, pattern distortions, chemical residues, and thickness non-uniformities. By using statistical analysis, we can identify defects even at the nanoscale level in chip development, allowing us to deliver high-quality products to our clients.
What is Statistical Analysis in Semiconductor Manufacturing?
Desiging for Excellence
Statistical analysis in the semiconductor industry is the application of statistical methods to monitor, control, and optimize the highly complex manufacturing process to ensure product quality, improve yield, and reduce costs.
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As modern chip manufacturing has become more complex, conventional process control techniques cannot identify any post-process defects because the data collected from any statistical sampling post-process is not in real-time. ​
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With statistical analysis, the enormous volume of sensor data, tracking temperature, pressure, chemical composition, vibration, and electromagnetic fields at each step is extracted, allowing algorithms to analyze terabytes of data in real-time, identifying deviations or patterns before the defects can occur. During the fabrication process, to be able to keep up with the high volume of modern fabrication, assembly workers cannot identify any microscopic irregularities, making statistical analysis an integral part of semiconductor manufacturing before products are released to the market.
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Currently, in the semiconductor industry, 12-inch wafers are the norm, with manufacturing only being done in Taiwan at Taiwan Semiconductor Manufacturing, and the testing of the wafers being done mainly in the United States. 12-inch wafers go through over 600 process steps within 8 weeks, with billions of transistors involved in each processor, demanding molecular-level precision be applied in analyzing for defects. These new processors hold more than 100 billion transistors, each of which relies on uniform execution across hundreds of interdependent parameters, so traditional process-control techniques will not be able to manage the complexity to ensure chips are released with no defects. Here at Zener Engineering, we pride ourselves on being able to deliver high-quality chips without issues, realizing the important role of accuracy in the semiconductor industry, and being the key to ensure cost effectiveness for our clients.
How We Use Applications of Statistical Analysis
Solutions with Superior Results
At Zener Engineering here is how we can help with our expertise in the applications of statistical analysis:
Predictive Yield Optimization​
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At Zener Engineering, we use historical data to build models and predict future events and performance, guiding strategic decisions and process improvements. We use data sets from wafer-level gauges, process parameters, and past performance trends to predict yield results prior to manufacturing cycles finishing. We can compare hundreds of variables simultaneously to detect small changes that can impact yields negatively or prove to be costly to clients. ​
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We extensively use JMP software to analyze the data statistically.
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Process Control & Optimization
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Statistical Process Control (SPC)​: We use statistical methods to monitor and control manufacturing processes in real-time, ensuring they operate at their optimal level to maintain consistent product quality.
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Designs of Experiments (DOE): We identify the best settings for manufacturing equipment by systematically testing different parameters to find the most effective combination.
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Quality Control & Yield Improvement
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Statistical Bin Analysis (SBA): We group chips into "bins" based on their characteristics, allowing engineers to identify trends, patterns, and defects to improve yields and prevent defective products.
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Performance & Reliability Analysis​
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Testing & Validation: We use statistical methods to validate the integrity and performance of semiconductor chips, using both parametric and non-parametric testing.
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Outlier Detection: We use statistical analysis to identify and understand outliers in the data, which can indicate manufacturing problems.
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Statistical Analysis to Drive Data
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Data Analytics:​ Once chips have been fabricated, the enormous amounts of data contained within each processor, which consists of over 100 billion transistors, using statistical analysis is extremely crucial. At Zener Engineering, we use statistical analysis combined with machine learning and artificial intelligence to consolidate data to provide a real-time view of operations to allow us to make informed decisions and avoid defects.​