Methods of modelling systems or performing predictive maintenance of systems, such as lithographic systems and associated lithographic systems

This invention describes a way to pinpoint the root causes of system failures in industrial processes. It analyzes data collected over time to spot unusual events, like spikes or control limit violations, and actual failures. It then uses a statistical technique to map out which events lead to others, ultimately identifying specific events as the root causes of failures.

Why it matters: Since 2018, advancements in machine learning and causal inference have made it significantly easier to automatically derive complex causal relationships from large time series datasets. This makes implementing such a system more feasible and robust.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, data analysis algorithms, machine learning models

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