DocumentCode :
3246059
Title :
Predictive Maintenance in semiconductor manufacturing
Author :
Iskandar, Jimmy ; Moyne, James ; Subrahmanyam, Kommisetti ; Hawkins, Parris ; Armacost, Mike
Author_Institution :
Appl. Mater.-Appl. Global Services, Santa Clara, CA, USA
fYear :
2015
fDate :
3-6 May 2015
Firstpage :
384
Lastpage :
389
Abstract :
Over the past two years the Predictive Maintenance (PdM) capability in semiconductor manufacturing has migrated from Proof-of-Concept (PoC) and univariate Fault Detection (FD) extrapolation mechanisms to fab-wide solutions that are (1) robust to typical process and equipment disturbances, (2) extensible so as to provide solution approaches that are portable across instances of a tool type and across tool types, and (3) maintainable so as to provide solutions that are useful for long periods of time. A number of advancements have facilitated this advancement including solutions for porting modeling components across process and equipment types, mechanisms for incorporating process and equipment knowledge into models, mechanisms for determining model context (e.g., recipe) dependency, methods for model optimization to fab financials, and methods for rejecting run-time disturbances in PdM modeling. As a result of these and other innovations, the landscape of PdM in semiconductor manufacturing has rapidly advanced to the point that, from a technical perspective, solutions are now available for fab-wide PdM realization.
Keywords :
extrapolation; fault diagnosis; maintenance engineering; optimisation; semiconductor device manufacture; FD extrapolation mechanisms; PdM capability; PdM modeling; PoC; equipment disturbances; fab financials; fault detection; predictive maintenance; proof-of-concept; run-time disturbances; semiconductor manufacturing; Analytical models; Context modeling; Data models; Maintenance engineering; Mathematical model; Predictive models; Technological innovation; Equipment Health Monitoring; Mean-Time-Between-Interrupts; Mean-Time-To-Repair; Predictive Maintenance; Prognostics and Health Management; unscheduled downtime;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Semiconductor Manufacturing Conference (ASMC), 2015 26th Annual SEMI
Conference_Location :
Saratoga Springs, NY
Type :
conf
DOI :
10.1109/ASMC.2015.7164425
Filename :
7164425
Link To Document :
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