IP Library Granted Patent US 7,899,562
Granted Patent B2
US 7,899,562 · App. 11/877,242 · Granted Mar 1, 2011

Methods and systems for controlling a semiconductor fabrication process

View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 7,899,562
App. No.
11/877,242
Granted
Mar 1, 2011
Kind
B2
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.

Claims (28)

1. A system comprising:

a state machine that controls operation of a semiconductor manufacturing system to schedule processing of one or more workpieces, the state machine including a plurality of states associated by a plurality of transitions, each one of the plurality of transitions having a weight assigned thereto, wherein when the state machine is operating within one of the plurality of states, a selection of a transition from the one of the plurality of states to another one of the plurality of states is determined by evaluating the weight assigned to each one of a number of possible transitions from the one of the plurality of states; and

a plurality of sensors for sensing aspects of the semiconductor manufacturing system;

a neural network that receives as inputs data from the plurality of sensors and provides as outputs the weights for one or more of the plurality of transitions;

a graphical user interface that displays a three-dimensional model of the semiconductor manufacturing system, wherein the three-dimensional model includes one or more objects that are correlated to an inventory containing data about a physical inventory of system components, the graphical user interface being configured to graphically present the one or more of the plurality of transitions in the three-dimensional model based on the weights from the neural network output in response to the data from the plurality of sensors.

2. The system of claim 1 , wherein the semiconductor manufacturing system includes a tunnel-based cart workpiece transport facility combined with a robot-robot handoff linear processing facility.

3. The system of claim 1 , wherein the semiconductor manufacturing system comprises modularly assembled modules.

4. The system of claim 3 , wherein at least one semiconductor manufacturing module can be added to the semiconductor manufacturing system without reconfiguring existing modules.

5. The system of claim 1 , wherein processing of one or more workpieces includes at least one of heating and cooling.

6. The system of claim 1 , wherein the received data includes technical information related to a process associated with the workpiece.

7. The system of claim 1 , wherein the received data includes workpiece edge sensing data.

8. The system of claim 1 , wherein at least one of the states represents a state of an item of hardware within the semiconductor manufacturing system.

9. The system of claim 1 , wherein at least one of the states represents a position of a workpiece within the semiconductor manufacturing system.

10. The system of claim 1 , wherein at least one of the states represents a position of an isolation valve within the system.

11. The system of claim 1 , wherein the state machine is updated in substantially real time.

12. The system of claim 1 , wherein the state machine is updated every 20 milliseconds.

13. The system of claim 1 , wherein the inputs to the neural network include at least one process time for a workpiece within the semiconductor manufacturing system.

14. The system of claim 13 , wherein the at least one process time includes one or more of a target duration, a start time, an end time, and an estimated end time.

15. The system of claim 1 , wherein the inputs to the neural network 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.

16. A method comprising:

controlling operation of a semiconductor manufacturing system with a state machine to schedule processing of one or more workpieces, the state machine including a plurality of states associated by a plurality of transitions, each one of the plurality of transitions having a weight assigned thereto, wherein when the state machine is operating within one of the plurality of states, a selection of a transition from the one of the plurality of states to another one of the plurality of states is determined by evaluating the weight assigned to each one of a number of possible transitions from the one of the plurality of states; and

sensing aspects of the semiconductor manufacturing system;

calculating, with a neural network, the weight assigned to each one of a number of possible transitions from a current state of the plurality of states by applying data representing the sensed aspects as inputs to the neural network;

selecting a transition from the current state of the plurality of states by evaluating the weight assigned to each one of the number of possible transitions from the current state; and

displaying a three-dimensional model on a graphical user interface of the semiconductor manufacturing system, wherein the three-dimensional model includes one or more objects that are correlated to an inventory containing data about a physical inventory of system components, the three-dimensional model being configured to graphically present one or more of the plurality of transitions on the display based on the weights calculated by the neural network in response to applying the data representing the sensed aspects.

17. The method of claim 16 , wherein at least one of the states represents a state of an item of hardware within the semiconductor manufacturing system.

18. The method of claim 16 , wherein at least one of the states represents a position of a workpiece within the semiconductor manufacturing system.

19. The method of claim 16 , wherein at least one of the states represents a position of an isolation valve within the system.

Assignments (9)
RELEASE OF SECURITY INTEREST RECORDED AT REEL/FRAME 044142/0258 Recorded Nov 4, 2025
From: MORGAN STANLEY SENIOR FUNDING, INC.
To: AZENTA, INC. (F/K/A BROOKS AUTOMATION, INC.); AZENTA US, INC. (F/K/A BROOKS LIFE SCIENCES, INC., F/K/A BIOSTORAGE TECHNOLOGIES, INC.)
Reel/Frame 073514/0609 →
RELEASE OF SECURITY INTEREST RECORDED AT REEL/FRAME 038891/0765 Recorded Nov 4, 2025
From: WELLS FARGO BANK, NATIONAL ASSOCIATION
To: AZENTA, INC. (F/K/A BROOKS AUTOMATION, INC.); AZENTA USA, INC. (F/K/A BIOSTORAGE TECHNOLOGIES, INC.)
Reel/Frame 073446/0080 →
SECOND LIEN PATENT SECURITY AGREEMENT Recorded Feb 2, 2022
From: BROOKS AUTOMATION US, LLC
To: GOLDMAN SACHS BANK USA
Reel/Frame 058945/0748 →
FIRST LIEN PATENT SECURITY AGREEMENT Recorded Feb 2, 2022
From: BROOKS AUTOMATION US, LLC
To: BARCLAYS BANK PLC
Reel/Frame 058950/0146 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 9, 2021
From: BROOKS AUTOMATION,INC
To: BROOKS AUTOMATION HOLDING, LLC
Reel/Frame 058481/0740 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 9, 2021
From: BROOKS AUTOMATION HOLDING, LLC
To: BROOKS AUTOMATION US, LLC
Reel/Frame 058482/0001 →
SECURITY INTEREST Recorded Oct 6, 2017
From: BROOKS AUTOMATION, INC.; BIOSTORAGE TECHNOLOGIES, INC.
To: MORGAN STANLEY SENIOR FUNDING, INC.
Reel/Frame 044142/0258 →
SECURITY AGREEMENT Recorded May 31, 2016
From: BROOKS AUTOMATION, INC.; BIOSTORAGE TECHNOLOGIES
To: WELLS FARGO BANK, NATIONAL ASSOCIATION
Reel/Frame 038891/0765 →
BILL OF SALE Recorded Oct 16, 2012
From: BLUESHIFT TECHNOLOGIES, INC.
To: BROOKS AUTOMATION, INC.
Reel/Frame 029134/0283 →