Advanced Micro Devices Corporation

R Michael Greig

Yi Cheng

Qingsu Wang

Gerald W Barnett

Robert Stone

Mark K Shackelford

A real-time hotspot detection system is disclosed. In a preferred embodiment, the real-time hotspot detection system of the present invention comprises a photolithography stepper that has been modified to output z-height focus data for each cell to a fault detection module of the present invention. After the entire wafer has been exposed by the stepper, the fault detection module computes the mean and standard deviation and/or other statistical data for the wafer data and compares the computed standard deviation with a predetermined limits for &ldquo;normal&rdquo; standard deviation, representative of a completely flat wafer having no hotspots thereon. If the computed standard deviation is outside the limits for the normal standard deviation, the fault detection module provides control signals to the stepper for halting the operation thereof and for generating an indication to the stepper operator, via a pole light associated with the stepper, that a failure has occurred. In addition, a wafer map showing the z-height data of the wafer that caused the failure may be displayed on a display associated with the module to enable a visual inspection to be performed and the cause of the hotspot to be more easily located.

System for enabling the real-time detection of focus-related defects

A system and method for detecting faults in wafer fabrication process tools by acquiring real-time process parameter signal data samples used to model the process performed by the process tool. The system includes a computer system including a DAQ device, which acquires the data samples, and a fault detector program which employs a process model program to analyze the data samples for the purpose of detecting faults. The model uses data samples in a reference database acquired from previous known good runs of the process tool. The fault detector notifies a process tool operator of any faults which occur thus potentially avoiding wafer scrap and potentially improving mean time between failures. The fault detector also receives notification of the occurrence of process events from the process tool, such as the start or end of processing a wafer, which the fault detector uses to start and stop the data acquisition, respectively. The fault detector also receives notification of the occurrence of a new process recipe and uses the recipe information to select the appropriate model for modeling the data samples. The fault detector employs a standard data exchange interface, such as DDE, between the fault detector and the model, thus facilitating modular selection of models best suited to the particular fabrication process being modeled. Embodiments are contemplated which use a UPM model, a PCA model, or a neural network model.

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Austin, TX, United States of America

R Michael Greig