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For semiconductor fab users, components manufacturers and materials suppliers, PAICe Monitor® allows you to achieve far beyond advanced process control. PAICe Monitor discovers sources of variance that are too complex for standard SPC charts and other linear methods. With PAICe Monitor, you have the power to immediately identify complex and non-linear multivariate relationships between process variables and target metrics, automatically generate analytics to monitor for complex process deviations, and prevent future occurrences. PAICe Monitor empowers your team to consistently increase yield and engineering productivity and reduce resource consumption.
PAICe Monitor takes in all available MES, SPC, FDC, equipment trace data and metrology data you are collecting, and automatically uncovers complex interactions between measured process variables and selected target variables. With the power of Machine Learning, PAICe Monitor actively learns the nuances of your equipment, configurations and processes in order to autonomously detect process variations that lead to any deviation in product quality for your manufacturing run or batch.
Using our proprietary library of machine learning algorithms, the PAICe Monitor application compiles a list of evidence-based causes for the process deviation of interest. It predicts wafers with critical dimensions outside of acceptable specifications.
PAICe Monitor provides clear and explainable visualizations to aid your process engineers in gaining insight into each identified cause. Your team can review the trace data of different process variables or a comparative summary of the variables of interest.
PAICe Monitor uses our patented low code Digital Twin Query Language to put the power of machine learning in the hands of your process engineers. It features an easy-to-use editor enabling your team to create and modify analytics for their custom processes. This expedites the path of identifying complex root causes and converting them into ongoing analytics solutions, ultimately making a more robust and stable manufacturing process.
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