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1. WO2022008906 - CONTROL OF PROCESSING EQUIPMENT

Publication Number WO/2022/008906
Publication Date 13.01.2022
International Application No. PCT/GB2021/051725
International Filing Date 07.07.2021
IPC
H01J 37/32 2006.1
HELECTRICITY
01BASIC ELECTRIC ELEMENTS
JELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
37Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
32Gas-filled discharge tubes
G05B 19/418 2006.1
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
19Programme-control systems
02electric
418Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G05B 13/02 2006.1
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
13Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
02electric
Applicants
  • UNIVERSITY OF EXETER [GB]/[GB]
Inventors
  • DALY, Gregory Austin
  • TABOR, Gavin Randal
  • FIELDSEND, Jonathan Edward
Agents
  • APPLEYARD LEES IP LLP
Priority Data
2010471.708.07.2020GB
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) CONTROL OF PROCESSING EQUIPMENT
(FR) COMMANDE D'ÉQUIPEMENT DE TRAITEMENT
Abstract
(EN) Broadly speaking, the present techniques provide a method and system for controlling a wafer production process in real-time using a trained machine learning, ML, model. Advantageously, the ML model uses multiple sensed parameters to determine a state of a plasma used in the wafer production process, and this can be used to adjust at least one control parameter of a plasma reactor used in the wafer production process to reduce process variability.
(FR) D'une manière générale, les présentes techniques concernent un procédé et un système de commande d'un processus de production de tranche en temps réel à l'aide d'un modèle d'apprentissage automatique (ML) formé. Avantageusement, le modèle ML utilise de multiples paramètres détectés pour déterminer un état d'un plasma utilisé dans le processus de production de tranche, et ceci peut être utilisé pour ajuster au moins un paramètre de commande d'un réacteur à plasma utilisé dans le processus de production de tranche pour réduire la variabilité du processus.
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