Abstract

In these last few decades, control charts have received a growing interest because of the important role they play by improving the quality of the products and services in industrial and non-industrial environments. Most of the existing control charts are based on the assumption of certainty and accuracy. However, in real-life applications, such as weather forecasting and stock prices, operators are not always certain about the accuracy of an observed data. To efficiently monitor such processes, this paper proposes a new cumulative sum (CUSUM) chart under the assumption of uncertainty using the neutrosophic statistic (NS). The performance of the new chart is investigated in terms of the neutrosophic run length properties using the Monte Carlo simulations approach. The efficiency of the proposed neutrosophic CUSUM (NCUSUM) chart is also compared to the one of the classical CUSUM chart. It is observed that the NCUSUM chart has very interesting properties compared to the classical CUSUM chart. The application and implementation of the NCUSUM chart are provided using simulated, petroleum and meteorological data.

Highlights

  • Control charts play an essential role in monitoring processes in the production and manufacturing sectors

  • Shewhart-type charts are inefficient in detecting small to moderate process shifts

  • The performance of the proposed neutrosophic CUSUM (NCUSUM) X control chart is evaluated in terms of different RL criteria, i.e. NARLs, NSDRL and the percentiles of the run length (PRL), i.e. the 25th, 50th and 75th percentiles which are denoted by P25 (i.e. P252[P25L, P25U]), P50 (i.e. P502 [P50L, P50U]) and P75 (i.e. P752[P75L, P75U])

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Summary

Introduction

Control charts play an essential role in monitoring processes in the production and manufacturing sectors.

Results
Conclusion
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