An enhanced EWMA chart with variable sampling interval scheme for monitoring the exponential process with estimated...

Area of Science:

• Industrial Engineering
• Statistical Quality Control
• Healthcare Analytics

Background:

• Control charts are essential for monitoring manufacturing processes.
• Exponential distribution is widely applied in healthcare and product lifetime analysis.
• Existing methods may lack efficiency for certain process monitoring tasks.

Purpose of the Study:

• To propose a novel control chart for monitoring exponential processes.
• To introduce the variable sampling interval exponentially weighted moving average (VSIEWMA-exp) chart.
• To enhance the performance of statistical process control for exponential data.

Main Methods:

• Development of the VSIEWMA-exp control chart.
• Performance evaluation using Markov chain methods.
• Algorithm development for optimal parameter selection.
• Comparative analysis against existing control charts.

Main Results:

• The VSIEWMA-exp chart demonstrated superior performance compared to competing methods.
• The proposed algorithm effectively identified optimal parameters for the control chart.
• Markov chain analysis provided robust performance measures.

Conclusions:

• The VSIEWMA-exp chart is an effective tool for monitoring exponential processes.
• This method offers improved statistical process control, particularly in healthcare settings.
• The study provides a valuable advancement in quality control methodologies.