Parallel abstraction of software architecture and statistical principles for tighter process control

Rob Firmin

doi:10.1117/12.485306

1 July 2003 Parallel abstraction of software architecture and statistical principles for tighter process control

Rob Firmin

Proceedings Volume 5044, Advanced Process Control and Automation; (2003) https://doi.org/10.1117/12.485306
Event: Advanced Microelectronic Manufacturing, 2003, Santa Clara, CA, United States

Abstract

Process control in the fab today employs a wide range of techniques to gather data, monitor processes and adjust through feed-forward and feed-back. This paper proposes that many substantial benefits could be derived from a broad abstraction of process control statistics algorithms as well as of data collection and distribution, in a manner parallel to how software users benefit from object oriented concepts. The abstracted algorithmic approach is based on statistics fundamentals. The paper first defines abstraction and discusses the benefits of its application to process control. It then defines a statistics experiment to test EWMA as one example of how a popular contemporary process control practice can misbehave when faced with four specific data attributes. The experiment quantifies the limitations of EWMA, and indicates that its performance is greatly enhanced when the more fundamental approach pre-processes its data. EWMA is not being singled out results are generalizable to other methods. The last two sections summarize findings and draw conclusions.

Citation Download Citation

Rob Firmin "Parallel abstraction of software architecture and statistical principles for tighter process control", Proc. SPIE 5044, Advanced Process Control and Automation, (1 July 2003); https://doi.org/10.1117/12.485306

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available