Productivity Improvement from Using Machine Buffers in Dual-Gripper Cluster Tools

IEEE Transactions on Automation Science and Engineering, Vol. 8, No. 1, January 2011

Mays Business School Research Paper No. 2012-53

14 Pages Posted: 16 May 2012

See all articles by Neil Geismar

Neil Geismar

Texas A&M University - Mays Business School

Milind Dawande

University of Texas at Dallas - Department of Information Systems & Operations Management

Chelliah Sriskandarajah

Texas A&M University

Date Written: 2011

Abstract

Cluster tools (also referred to as robotic cells) are extensively used in semiconductor wafer fabrication. We consider the problem of scheduling operations in an m-machine cluster tool that produces identical parts (wafers). Each machine is equipped with a unit-capacity input buffer and a unit-capacity output buffer. The machines and buffers are served by a dual-gripper robot. Each wafer is processed on each of the machines, and the objective is to find a cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes the throughput.

We first obtain a tight upper bound on the optimal throughput and then use this bound to obtain an asymptotically optimal sequence under conditions that are common in practice. Next, we quantify the improvement in productivity that can be realized from the use of unit-capacity input and output buffers at the machines. Finally, we illustrate our analysis on cluster tools with realistic parameters, based on our work with a Dallas-based semiconductor equipment manufacturer.

Keywords: Cluster tools, cyclic solutions, dual-gripper robots, manufacturing

Suggested Citation

Geismar, Neil and Dawande, Milind and Sriskandarajah, Chelliah, Productivity Improvement from Using Machine Buffers in Dual-Gripper Cluster Tools (2011). IEEE Transactions on Automation Science and Engineering, Vol. 8, No. 1, January 2011; Mays Business School Research Paper No. 2012-53. Available at SSRN: https://ssrn.com/abstract=2061303

Neil Geismar (Contact Author)

Texas A&M University - Mays Business School ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

Milind Dawande

University of Texas at Dallas - Department of Information Systems & Operations Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

Chelliah Sriskandarajah

Texas A&M University ( email )

Langford Building A
798 Ross St.
77843-3137

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