Control chart design strategies for skewed data

Steven T. Mandraccia; Galen D. Halverson; Youn-Min Chou

doi:10.1117/12.250904

13 September 1996 Control chart design strategies for skewed data

Steven T. Mandraccia, Galen D. Halverson, Youn-Min Chou

Proceedings Volume 2876, Process, Equipment, and Materials Control in Integrated Circuit Manufacturing II; (1996) https://doi.org/10.1117/12.250904
Event: Microelectronic Manufacturing 1996, 1996, Austin, TX, United States

Abstract

Individual measurements and moving-range control charts are applied when the quality characteristic follows a normal distribution. In the semiconductor industry, certain quality characteristics are monitored where the data do not follow a normal distribution. In this paper we consider alternative design strategies for control charts where the distribution of the data is skewed. Although we use skewed data, these techniques are also applicable to other non-normally distributed data. We discuss using a 'state of the art' curve-fitting method, data transformations, and nonsymmetrical limits for the control charting of skewed data. This paper provides alternatives for the design, implementation, and maintenance of process control for non- normal or skewed data.

Citation Download Citation

Steven T. Mandraccia, Galen D. Halverson, and Youn-Min Chou "Control chart design strategies for skewed data", Proc. SPIE 2876, Process, Equipment, and Materials Control in Integrated Circuit Manufacturing II, (13 September 1996); https://doi.org/10.1117/12.250904

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