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Comparison of Process Capability Indices under AR (2) process
M. M. Deshpande1 , V. B. Ghute2
Section:Research Paper, Product Type: Isroset-Journal
Vol.6 ,
Issue.1 , pp.131-137, Feb-2019
CrossRef-DOI: https://doi.org/10.26438/ijsrmss/v6i1.131137
Online published on Feb 28, 2019
Copyright © M. M. Deshpande, V. B. Ghute . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: M. M. Deshpande, V. B. Ghute, “Comparison of Process Capability Indices under AR (2) process,” International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.6, Issue.1, pp.131-137, 2019.
MLA Style Citation: M. M. Deshpande, V. B. Ghute "Comparison of Process Capability Indices under AR (2) process." International Journal of Scientific Research in Mathematical and Statistical Sciences 6.1 (2019): 131-137.
APA Style Citation: M. M. Deshpande, V. B. Ghute, (2019). Comparison of Process Capability Indices under AR (2) process. International Journal of Scientific Research in Mathematical and Statistical Sciences, 6(1), 131-137.
BibTex Style Citation:
@article{Deshpande_2019,
author = {M. M. Deshpande, V. B. Ghute},
title = {Comparison of Process Capability Indices under AR (2) process},
journal = {International Journal of Scientific Research in Mathematical and Statistical Sciences},
issue_date = {2 2019},
volume = {6},
Issue = {1},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {131-137},
url = {https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=1149},
doi = {https://doi.org/10.26438/ijcse/v6i1.131137}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i1.131137}
UR - https://www.isroset.org/journal/IJSRMSS/full_paper_view.php?paper_id=1149
TI - Comparison of Process Capability Indices under AR (2) process
T2 - International Journal of Scientific Research in Mathematical and Statistical Sciences
AU - M. M. Deshpande, V. B. Ghute
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 131-137
IS - 1
VL - 6
SN - 2347-2693
ER -
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Abstract :
Statistical Process Control (SPC) tools are applicable in all fields. Process Capability Analysis (PCA) is one of the essential SPC tools. In Process Capability, it measures the ability of an in-control process to produce the desired product. Process Capability Indices (PCIs) are defined to measure the capability of the process. Along with in control process PCIs also assumes that the process characteristic is Normally distributed and the observations on characteristic are independent. The assumption of independent observations has violated in many industrial processes. The present paper focuses on the effect of this violation of independence which is also known as autocorrelation effect. ARMA models are appropriate for autocorrelated processes.
Key-Words / Index Term :
Autocorrelated process, Estimation, Process Capability Indices (PCIs), Statistical Process Control
References :
[1] S. Kotz, and N. L. Johnson, “Process Capability Indices – A Review, 1992-2000 Discussions”, Journal of Quality Technology, Vol 34, Issue 1, pp. 2–19, 2002
[2] H. Shore, “Process Capability Analysis when Data are Autocorrelated”, Quality Engineering, Vol. 9, Issue 4, pp. 615–626, 1997.
[3] N. F. Zhang, “Estimating Process Capability Indexes for Autocorrelated Data”, Journal of Applied Statistics, Vol. 25, Issue 1, pp. 559–574, 1998.
[4] R. D. Guevara, and J. A. Vargas, “Comparison of Process Capability Indices under Autocorrelated Data”, Revista Colombiana de Estadística, Vol. 30, Issue 2, pp. 301-316, 2007.
[5] P. J. Brockwell and R. A. Davis, “Time Series: Theory and Methods”, Springer, New York, 1991.
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