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A study on target Sigma Level at R&D stage and robust limits for design margins
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 Title & Authors
A study on target Sigma Level at R&D stage and robust limits for design margins
Ko, Seoung-gon;
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 Abstract
The Sigma Level, proposed by Motorola Inc., is one of the many Process Capability Index (PCI)'s that have been presented since the 1970's. It is used to evaluate process capability and unlike other PCI's, it has an advantage in that it uses population probability distribution. However, it is originally designed for mass production and is inadequate to evaluate prototypes or early products in the R&D stages. For use in such cases, we propose an R&D target Sigma Level, derived by considering 1.5 sigma shifts in traditional sigma level from a statistical point of view. We also explain the way to find robust limits for design tolerance because the sigma level or defect probability is useful to establish economical tolerance limits at the R&D stage and mass production.
 Keywords
Process Capability Index(PCI);Sigma Level;R&D Sigma Level;1.5 sigma shift;robust limits;design tolerance;
 Language
Korean
 Cited by
 References
1.
Bender, A. (1962). Benderizing tolerances-a simple practical probability method of handling tolerances for limit-stack-ups, Graphic Science, 17.

2.
Bissell, A. F. (1990). How reliable is your capability index?, Applied Statistics, 39, 331-340. crossref(new window)

3.
Bothe, D. R. (2002). Statistical reason for the 1.5 sigma shift, Quality Engineering, 14, 479-487. crossref(new window)

4.
Denniston, B. (2006). Capability indices and conformance to specification: the motivation for using Cpm, Quality Engineering, 18, 79-88. crossref(new window)

5.
Donaldson, P. D. (2004). 100 years of Juran, Quality Progress, 37, 25-37.

6.
El-Haik, B. (2005). Axiomatic Quality: Integrating Axiomatic Design with Six-Sigma, Reliability, and Quality Engineering, John Wiley & Sons.

7.
Evans, D. H. (1975). Statistical tolerancing: the state of the art, part III, methods for estimating moments, Journal of Quality Technology, 7, 1-12.

8.
Gilson, J. (1951). A New Approach to Engineering Tolerances, Machinery Publishing Co, London.

9.
Harry, M. J. (1994). The Vision of Six Sigma: Tools and Methods for Breakthrough, Sigma Academy, Phoenix, AZ.

10.
Harry, M. J. and Lawson, J. R. (1992). Six Sigma Producibility Analysis and Process Characterization, Addison-Wesley, MA, 2-3.

11.
Kane, V. E. (1986). Process capability indices, Journal of Quality Technology, 18, 41-52.

12.
Kotz, S. and Johnson, N. L. (1993). Process Capability Indices, CRC Press.

13.
Mathew, T., Sebastian, G., and Kurian, K. M. (2007). Generalized confidence intervals for process capability indices, Quality and Reliability Engineering International, 23, 471-481. crossref(new window)

14.
Munro, R. A. (2000). Linking six sigma with QS-9000, Quality Progress, 33, 47.

15.
Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product, ASQ Quality Press.

16.
Sleeper, A. (2005). Design for Six Sigma Statistics: 59 Tools for Diagnosing and Solving Problems in DFFS Initiatives: 59 Tools for Diagnosing and Solving Problems in DFFS Initiatives, McGraw Hill Professional.