The present invention provides maintenance recommendation system and method that improve the accuracy of estimating a failure mode of equipment and thereby reduce frequency of replacement operations, shorten a time of examination, and decrease a recovery time of equipment from a failure. A maintenance recommendation system of the present invention identifies a failure mode of a machine and comprises an information input element to input one or more inspection results required to identify a failure mode, a temporary storage unit to store the inspection results, a failure mode probability calculating unit to estimate probabilities of failure modes from results of inspection performed one or more times, and an estimation-accuracy determining unit to calculate uncertainty of the probabilities of the failure modes. The system presents inspection items based on the uncertainty of the probabilities of the failure modes.

A real-time control system includes a faulty variable identification technique to implement a data-driven fault detection function that provides an operator with information that enables a higher level of situational awareness of the current and likely future operating conditions of the process plant. The faulty variable identification technique enables an operator to recognize when a process plant component is behaving abnormally to potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a stall of the process control system or a failure of the process plant component.

A manufacturing condition output apparatus of an embodiment is a manufacturing condition output apparatus which outputs a manufacturing condition of a product. The manufacturing condition output apparatus outputs change degree information which is information regarding degrees of change of values regarding defect probabilities for a plurality of variables relating to manufacturing of the product from model information of a model generated through machine learning on a basis of manufacturing data of the product and inspection result data of the product, as a manufacturing condition.

Implementations described herein generally relate to improving silicon wafer manufacturing. In one implementation, a method includes receiving information describing a defect. The method further includes identifying a critical area of a silicon wafer and determining the probability of the defect occurring in the critical area. The method further includes determining, based on the probability, the likelihood of an open or a short occurring as a result of the defect occurring in the critical area. The method further includes providing, based on the likelihood, predictive information to a manufacturing system. In some embodiments, corrective action may be taken based on the predictive information in order to improve silicon wafer manufacturing.

A real-time control system includes a faulty variable identification technique to implement a data-driven fault detection function that provides an operator with information that enables a higher level of situational awareness of the current and likely future operating conditions of the process plant. The faulty variable identification technique enables an operator to recognize when a process plant component is behaving abnormally to potentially take action, in a current time step, to alleviate the underlying cause of the problem, thus reducing the likelihood of or preventing a stall of the process control system or a failure of the process plant component.

Implementations described herein generally relate to improving silicon wafer manufacturing. In one implementation, a method includes receiving information describing a defect. The method further includes identifying a critical area of a silicon wafer and determining the probability of the defect occurring in the critical area. The method further includes determining, based on the probability, the likelihood of an open or a short occurring as a result of the defect occurring in the critical area. The method further includes providing, based on the likelihood, predictive information to a manufacturing system. In some embodiments, corrective action may be taken based on the predictive information in order to improve silicon wafer manufacturing.

A method for analyzing test results. The method includes selecting a first subset of tests from a plurality of tests. Test results are gathered from the plurality of tests in real-time. A first statistical analysis is performed on test results from the first subset of tests. At least one process control rule is initiated as determined by results of the first statistical analysis performed on the test results from the first subset of tests.