By Topic

Statistical Process Control for e-Diagnostic Prediction of Cluster-Tool Equipment

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wen-Ren Jong ; Chung Yuan Christian Univ., Jhongli ; Tzu-Wei Lin

The main assignment of wafer transport automation in cluster-tools equipment is to transfer wafer between chambers and cassettes automatically. However, the operation of cluster-tools must be done in the clean room in consideration of the cleaning requirement, technology support of operator, and maintenance of equipment. With remote monitoring and e-diagnostics technology, an operator can monitor the procedures of wafer transport, the statuses of equipment, and more remote diagnosing/control of cluster-tools via Internet. Thus, it will be useful for maintenance, diagnosis, and productivity improvement. Besides, it can also use statistical process control system to predict the status of equipment. This system will know in advance whether the equipment is going to fail or not. The operator can handle the problems earlier with the prediction of the status of equipment. This research discusses the capability requirement of remote monitoring and diagnosing system for cluster-tools equipment. The CCD camera can take a picture when the arm goes into chamber. The data will be saved into SQL Server after program recognize the image and calculate the height of front arm. Then, use statistical process control to get capability of accuracy, capability of process, and process capability of the equipment. These three indexes will show the operator the status of equipment. Operator can call the engineer to check and fix the equipment ahead of time to avoid an accident when the index displayed a failing tendency. It will achieve the capability of e-diagnostics prediction.

Published in:

Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE

Date of Conference:

5-8 Nov. 2007