Dergiler / Hacettepe Journal of Mathematics and Statistics / 2015 / Cilt: 44 - Sayı: 1

Non-dominated sorting genetic algorithm (NSGA-II) approach to the multi-objective economic statistical design of variable sampling interval T2 control charts

Sayfa
203–214
Yayın Tarihi
2022-10-18
DOI
—
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, thereby bolding the advantage of flexibility and adaptability. 2000 AMS Classifi cation:

📌 3 Maddede Bu Makale

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Amaç & Hipotez:T2 control charts are used to primarily monitor the mean vector of quality char- acteristics of a process.
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Temel Bulgular & Veri:Recent studies have shown that using variable sam- pling interval (VSI) schemes results in charts with more statistical power for detecting small to moderate shifts in the process mean vector.
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Sonuç & Katkı:Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, thereby bolding the advantage of flexibility and adaptability. 2000 AMS Classifi cation:
🔬Tür:Araştırma Makalesi
📍Kapsam:2000 Verileri
⚙️Değişkenler:Alan Parametreleri

Abstract

T2 control charts are used to primarily monitor the mean vector of quality char- acteristics of a process. Recent studies have shown that using variable sam- pling interval (VSI) schemes results in charts with more statistical power for detecting small to moderate shifts in the process mean vector. In this study, we have presented a multiple-objective economic statistical design of VSI T2 control chart when the in-control process mean vector and process covariance matrix are unknown. Then we exert to find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the Non-dominated sorting genetic algorithm. Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, thereby bolding the advantage of flexibility and adaptability. 2000 AMS Classifi cation:

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Bu Makaleye Atıf Yap

SEIF, A., SADEGHIFAR, M. (2022). Non-dominated sorting genetic algorithm (NSGA-II) approach to the multi-objective economic statistical design of variable sampling interval T2 control charts. Hacettepe Journal of Mathematics and Statistics, Cilt: 44 - Sayı: 1, 203–214. https://ajindex.com/articles/528627

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