A rational sequential probability ratio test control chart for monitoring process shifts in mean and variance

Ou, Yongsheng; Wu, Zhang; Khoo, Michael B. C.; Chen, Nan

doi:10.1080/00949655.2014.901327

Cited by 16 publications

(6 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many publications show novel methods for optimized change detection using CUSUM as can be seen in references [2,19] or analyse work efficient parallel scan solutions to get CUSUM values [20]. As in the case of these papers, the focus of our work has been to develop a general framework that offers scalable performance and operates in limited memory and in real-time.…”

Section: Calculation Of Thementioning

confidence: 99%

“…In the literature, several theories have been already proposed to extend the applicability of the mathematical background or to optimize calculation. However, new methodologies [1][2][3][4] and applications [5][6][7][8][9][10] of statistical hypothesis tests are published every year. The so-called Bayes' theorem in probability theory has been established by Thomas Bayes in the early 1700s.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Enhanced Evaluation Method of Sequential Probability Ratio Test

Gardonyi

Por

Samu

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Accurate event detection has high priority in many technical applications. Events in acquired data series, their duration, and statistical parameters provide useful information about the observed system and about its current state. This information can be used for condition monitoring, state identification, and many kinds of forecasting as well. In some cases background noise covers the events and simple threshold or power monitoring methods cannot be used effectively. A novel method called Scaled Sequential Probability Ratio Test (SSPRT) produces 2D array of data via special cumulative sum calculation. A peak determination algorithm has also been developed to find significant peaks and to store the corresponding data for further evaluation. The method provides straight information about the endpoints and possible duration of the detected events as well as shows their significance level. The new method also gives representative visual information about the structure of detected events. Application example for thermomechanical fatigue test monitoring and another for vibration based rotational speed estimation of a four-cylinder internal combustion engine is discussed in this paper.

show abstract

Section: Calculation Of Thementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Enhanced Evaluation Method of Sequential Probability Ratio Test

Gardonyi

Por

Samu

2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…For very recent papers on joint monitoring, readers may refer to, among others, Haridy et al ,. Ou et al ., and Mukherjee et al …”

Section: Introductionmentioning

confidence: 96%

Design and Implementation of Two CUSUM Schemes for Simultaneously Monitoring the Process Mean and Variance with Unknown Parameters

Mukherjee

et al. 2016

Quality & Reliability Eng

View full text Add to dashboard Cite

Designing joint monitoring schemes for the mean and variance of a Gaussian process (normal distribution) using a single combined statistic instead of the traditional approach of using two separate statistics has gained many attention in recent years. Most of the existing one-chart schemes, however, assume that the true process parameters (standards) are known which is usually not practical and will lead to problems because of improper choices of statistic and control limits. In this paper, we propose two CUSUM control schemes that instinctively work well for the joint monitoring in the case of the unknown parameters by correcting the influence of the reference sample on the plotting statistic. We provide the control limits of the proposed control charts for practical implementation and also offer follow-up procedures for post-signal detection of the nature of shifts. We carry out a comprehensive simulation study to examine the performance of the schemes. When the true population parameters are unknown, we observe clear and distinct performance advantages of the proposed schemes. The empirical design issues regarding the optimal choice of the reference value of the proposed CUSUM schemes are systematically investigated. We provide beneficial recommendations for the practitioners. We also provide an example to illustrate the practical relevance of the proposed schemes.

show abstract

“…developed the economic design of the SPRT chart. Ou et al 18 . introduced some modifications to simultaneous monitoring.…”

Section: Introductionmentioning

confidence: 99%

On designing efficient sequential schemes to monitor non‐normal processes

Riaz

Khaliq

Abid

et al. 2021

Quality & Reliability Eng

View full text Add to dashboard Cite

The process monitoring techniques play an essential role to improve the overall performance of processes. The control chart is an essential monitoring tool used to detect changes in the process parameters. The Shewhart charts are famous for detecting larger shifts, while exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are famous for detecting small‐to‐moderate shifts. The separate control schemes are required for the quick identification of the changes in the process parameters because sometimes testing is too expensive or time taking and a practitioner may not afford any kind of defects or loss. With this motivation, the dynamic feature of this article is to introduce an efficient sequential probability ratio test (SPRT) decision‐based Tukey CUSUM design. The performance of the proposal is judged by using several run lengths (RLs) performance measures such as average, median, standard deviation, and percentile RLs. Based on the comparative analysis, it is revealed that the proposed chart offers more sensitivity towards the changes in process location than its competitor's charts for several probability models. The study proposal may find applications in packaging, manufacturing, decision‐making, finance and economics modeling, image processing and automation. A case study from steel rods manufacturing is included to demonstrate the application of the proposed design.

show abstract

A rational sequential probability ratio test control chart for monitoring process shifts in mean and variance

Cited by 16 publications

References 41 publications

An Enhanced Evaluation Method of Sequential Probability Ratio Test

An Enhanced Evaluation Method of Sequential Probability Ratio Test

Design and Implementation of Two CUSUM Schemes for Simultaneously Monitoring the Process Mean and Variance with Unknown Parameters

On designing efficient sequential schemes to monitor non‐normal processes

Contact Info

Product

Resources

About