Shared Data Induced Quality Control For A Chemical Mechanical Planarization Process

Shared Data Induced Quality Control For A Chemical Mechanical Planarization Process

A method for developing or improving a process for producing a product from a material comprising steps of acquiring the composition for at least two slurries as raw material data (17) for the CMP based manufacturing process and its relevant parameters (2) by using a Data Collecting computer (9); ph...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Gopal, Vid, Clarke, Ryan, Pham, Hieu, Yang, Rung-Je, Yitamben, Esmeralda, Lin, Shirley, Rose, Joseph, Murella, Krishna, Mallikarjunan, Anupama, Clavero, Cesar, Gan, Lu, Zhou, Hongjun
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:A method for developing or improving a process for producing a product from a material comprising steps of acquiring the composition for at least two slurries as raw material data (17) for the CMP based manufacturing process and its relevant parameters (2) by using a Data Collecting computer (9); physically performing specific method steps of a CMP process; measuring relevant parameters of the used slurries and the physically performed CMP process to determine the CMP process performance by using the Data Collecting computer (9); analyzing the measured data about the relevant parameters with a specific software performed on an Analyzing computer (11) by creating for the software and applying with it a predictive model using Machine Learning to understand the intercorrelation of the different parameters and using the results to improve the CMP process performance and the resulting product quality of the CMP based manufacturing process.