Traditional root cause analysis in manufacturing uses summary data, which is ineffective in the face of complex issues stemming from subtle defects in a process. Full trace analytics, backed by powerful Artificial Intelligence (A.I.) algorithms, uses the entirety of all the sensor and tool data available in a production line for analysis, enabling fabrication engineers to quickly and accurately focus on the causes of issues that negatively affect yield, large and small.
Full trace analytics allows for comprehensive examination of process data, combing through all the information available on the factory floor to detect abnormalities and defects down to the finest level. The current industry standard of analyzing summary data is dated and ineffective, sometimes taking weeks to find a root cause.