Economic-statistical design of synthetic np chart with estimated process parameter

Area of Science:

• Industrial Engineering
• Statistical Quality Control

Background:

• Traditional synthetic np charts often assume known process parameters.
• Parameter estimation in quality control charts can impact economic design.
• Limited preliminary subgroups are a practical constraint in many industrial settings.

Purpose of the Study:

• To present an economic-statistical design for synthetic np charts with estimated process parameters.
• To investigate the effect of process parameter estimation on the expected cost of synthetic np charts.
• To determine the minimum preliminary subgroups needed for cost similar to the known parameter case.

Main Methods:

• Economic-statistical design principles applied to synthetic np charts.
• Investigation of the impact of estimated process parameters on expected cost.
• Optimization of synthetic np chart parameters considering practical subgroup limitations.

Main Results:

• Parameter estimation can lead to lower expected costs for synthetic np charts.
• The minimum number of preliminary subgroups is determined for near-optimal cost.
• Optimal chart parameters computed with practical subgroup numbers yield lower expected costs.

Conclusions:

• Synthetic np charts with estimated parameters offer economic advantages.
• Practical limitations on preliminary subgroups should be considered for cost optimization.
• The proposed design provides a more cost-effective approach in real-world applications.