Methods and systems for controlling a semiconductor fabrication process

Abstract

Software for controlling processes in a heterogeneous semiconductor manufacturing environment may include a wafer-centric database, a real-time scheduler using a neural network, and a graphical user interface displaying simulated operation of the system. These features may be employed alone or in combination to offer improved usability and computational efficiency for real time control and monitoring of a semiconductor manufacturing process. More generally, these techniques may be usefully employed in a variety of real time control systems, particularly systems requiring complex scheduling decisions or heterogeneous systems constructed of hardware from numerous independent vendors.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This claims the benefit of U.S. App. No. 60 / 746,163 filed on May 1, 2006 and U.S. App. No. 60 / 807,189 filed on Jul. 12, 2006. This application is a continuation-in-part of U.S. application Ser. No. 10 / 985,834, filed on Nov. 10, 2004, which claims the benefit of U.S. App. No. 60 / 518,823 filed on Nov. 10, 2003 and U.S. App. No. 60 / 607,649 filed on Sep. 7, 2004. This application is also a continuation-in-part of U.S. application Ser. No. 11 / 123,966 filed on May 6, 2005, and a continuation-in-part of U.S. application Ser. No. 11 / 302,563 filed on Dec. 13, 2005.[0002]Each of the foregoing commonly-owned applications is incorporated by reference herein in its entirety.BACKGROUND[0003]1. Field[0004]This invention relates to, inter alia, methods of utilizing a wafer-centric database to improve system throughput.[0005]2. Related Art[0006]The handling of workpieces such as wafers within a semiconductor manufacturing environment can present significa...

AI Technical Summary

Benefits of technology

[0008]Software for controlling processes in a heterogeneous semiconductor manufacturing environment may include a wafer-centric database, a real-time scheduler using a neural network, and a graphical user interface displaying simulated operation of the system. These features may be employed alone or in combination to offer improved usability and computational efficiency for real time control and monitoring of a semiconductor manufacturing process. More generally, these techniques may be usefully employed in a variety of real time control systems, particularly systems requiring complex scheduling decisions or heterogeneous systems constructed of hardware from numerous independent vendors.

[0014]At least one of the plurality of states may represent a state of an item of hardware within the semiconductor manufacturing system. At least one of the states may represent a position of a workpiece within the semiconductor manufacturing system. At least one of the states may represent a position of an isolation valve within the system. The computer executable code may further perform the step of updating the neural network in substantially real time. The computer executable code may further perform the step of updating the neural network every 20 milliseconds. The inputs to the neural network may include one or more of sensor data, temperature data, a detected workpiece position, an estimated workpiece temperature, an actual workpiece temperature, a valve state, an isolation valve state, robotic drive encoder data, robotic arm position data, end effector height data, a process time, a process status, a pick time, a place time, and a control signal. The inputs to the neural network may include at least one process time for a workpiece within the semiconductor manufacturing system. The at least one process time may include one or more of a target duration, a start time, an end time, and an estimated end time. The inputs may include a transition time. The transition time may include one or more of a pump down to vacuum time and a vent to atmosphere time. At least one of the states includes a transition to itself. The computer executable code may further perform the step of updating the state machine in substantially real time. The computer executable code may further perform the step of updating the state machine every 20 milliseconds. The computer executable code may further perform the step of controlling operation of a semiconductor manufacturing system with a plurality of state machines, each one of the plurality of state machines controlling a portion of the semiconductor manufacturing system according to one of a plurality of neural networks.

Problems solved by technology

The handling of workpieces such as wafers within a semiconductor manufacturing environment can present significant computing challenges.

Hardware such as process modules, handlers, valves, robots, and other equipment are commonly assembled from a variety of different manufacturers each of which may provide proprietary or pre-compiled software unsuitable for a newly conceived process.

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