A New Attribute Control Chart Using Multiple Dependent State Repetitive Sampling

Mansour Sattam Aldosari · Muhammad Aslam · Chi‐Hyuck Jun

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Advanced Statistical Process Monitoring Probability and Statistical Research Fault Detection and Control Systems

Abstract

In this paper, a new attribute control chart using multiple-dependent state repetitive sampling is designed. The operational procedure and structure of the proposed control chart is given. The required measures to determine the average run length for in-control and out-of-control processes are given. Tables of ARLs are reported for various control chart parameters. The proposed control chart is more sensitive in detecting a small shift in the process as compared with the existing attribute control charts. The simulation study shows the efficiency of the proposed chart over the existing charts. An example is given for illustration purpose.

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References

2007Introduction to Statistical Quality Control 2002Design of double- and triple-sampling X-bar control charts using genetic algorithms 2011On Proper Choice of Variability Control Chart for Normal and Non‐normal Processes 2014A new attribute control chart using multiple dependent state sampling 2009A Group Acceptance Sampling Plans for Lifetimes Following a Generalized Exponential Distribution 2015Attribute Control Charts for the Weibull Distribution under Truncated Life Tests 2014New Attributes and Variables Control Charts under Repetitive Sampling 2015A mixed control chart to monitor the process

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2020A hybrid homogeneously weighted moving average control chart for process monitoring 2019A new variable control chart using neutrosophic interval method-an application to automobile industry 2023A re-evaluation of repetitive sampling techniques in statistical process monitoring 2019A Variable Control Chart Based on Process Capability Index Under Generalized Multiple Dependent State Sampling 2017New Cumulative Sum Control Chart for Monitoring Poisson Processes

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