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Integrating the Fault Detection Method and Run-to-Run Control for Improving Semiconductor Process Control
Author(s) -
ChihHung Jen,
Jiaming Wang
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2011.04.142
Subject(s) - computer science , semiconductor device fabrication , fault (geology) , process (computing) , fault detection and isolation , chemical mechanical planarization , control system , process control , construct (python library) , real time computing , reliability engineering , artificial intelligence , engineering , actuator , polishing , electrical engineering , mechanical engineering , seismology , wafer , geology , operating system , programming language
Recently, detailed investigations of various ‘run-to-run’ (R2R) control schemes for semiconductor manufacturing have been conducted. However, the R2R control scheme has a major problem that needs to be solved, namely, how to detect and differentiate the faults in the control system. In view of this consideration, the objective of this research was to construct a novel module for fault diagnosis so that the R2R control system can operate smoothly. In this study, a fault diagnostic module is added to the multiple-input multiple-output (MIMO) R2R self-tuning control system. The proposed system integrates the R2R selftuning control, weighted sum of squared residuals (WSSR), and joint angle analysis (JAA) methods to detect the system faults, and executes the process control. First, the WSSR is applied to detect whether the system has generated the fault characteristics. If the process is judged to exhibit an obvious fault, the system then uses JAA to define the faulty controllable variable. Finally, a critical step, the chemical mechanical planarization (CMP) in semiconductor manufacturing, is used to illustrate the procedure of fault diagnosis in order to verify the feasibility in practical application

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