Abstract: Systems and methods for automatically and/or systematically include more data sources and/or more detailed data in the analysis, prediction, and model building. Process data may be employed to pinpoint the process parameter excursions and domain knowledge and/or expert systems may be automatically and/or systematically incorporated into the root cause analysis, the prediction and/or the model building to improve results and/or to reduce the reliance on inconsistent and expensive human experts.

Abstract: Computer-implemented methods and systems for tool health prediction for a tool having sub-systems and components are disclosed. The method includes providing parameter values from sensors to an expert system. The method also includes providing knowledge base data from a knowledge base to the expert system. The knowledge base includes at least one of tool history, part information, domain knowledge, and model history. The method also includes generating, using the expert system, at least one tool health prediction pertaining to tool maintenance. The prediction generation employs a set of prediction models that includes at least one prediction model. The prediction generation further employs at least the parameter values and the knowledge base data.

Abstract: Integrated yield/equipment data processing system for collecting and analyzing integrated tool-related data (cause data) and material-related data (effect data) pertaining to at least one material processing tool and at least one material is disclosed. In an embodiment, the tool-related data is correlated with the material-related data, and the correlated tool-related data and material-related data is employed by logic to perform at least one of root-cause analysis, prediction model building and tool control/optimization. By integrating cause-and-effect data in a single platform, the data necessary for performing, for example, automated problem detection (e.g., automated root cause analysis) and prediction, is readily available and correlated, which for example shortens the cycle time to detection and facilitates efficient and timely automated tool management and control.