The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Jun. 21, 2011
Filed:
Jul. 31, 2007
Yuri Kokotov, Maaleh Adumim, IL;
Efim Entin, Jersusalem, IL;
Jacques Seror, Jerusalem, IL;
Yossi Fisher, Jerusalem, IL;
Shalomo Sarel, Maaleh Michmas, IL;
Arulkumar P. Shanmugasundram, Sunnyvale, CA (US);
Alexander T. Schwarm, Austin, TX (US);
Young Jeen Paik, Campbell, CA (US);
Yuri Kokotov, Maaleh Adumim, IL;
Efim Entin, Jersusalem, IL;
Jacques Seror, Jerusalem, IL;
Yossi Fisher, Jerusalem, IL;
Shalomo Sarel, Maaleh Michmas, IL;
Arulkumar P. Shanmugasundram, Sunnyvale, CA (US);
Alexander T. Schwarm, Austin, TX (US);
Young Jeen Paik, Campbell, CA (US);
Applied Materials, Inc., Santa Clara, CA (US);
Abstract
A method, system, and medium of modeling and/or for controlling a manufacturing process is disclosed. In particular, a method according to embodiments of the present invention includes calculating a set of predicted output values, and obtaining a prediction model based on a set of input parameters, the set of predicted output values, and empirical output values. Each input parameter causes a change in at least two outputs. The method also includes optimizing the prediction model by minimizing differences between the set of predicted output values and the empirical output values, and adjusting the set of input parameters to obtain a set of desired output values to control the manufacturing apparatus. Obtaining the prediction model includes transforming the set of input parameters into transformed input values using a transformation function of multiple coefficient values, and calculating the predicted output values using the transformed input values.