Quality manipulation plays an essential feature in assuring product reliability and patron loyalty. Single Sampling Plans (SSPs) are usually utilized in excellent assurance to decide whether a batch of items should be popular or rejected based on sample characteristics. Truncated SSPs are a subset of those plans that offer benefits in sampling performance and price effectiveness. However, the lifestyles of outliers in accrued information will have a substantial impact on the accuracy and reliability of estimators employed in truncated SSPs. This examination explores the impact of outliers on the overall performance of truncated SSP estimators, in addition to their implications for quality control decision-making. We begin by providing a comprehensive overview of truncated SSPs and their applications in the industry. Then, at that point, delve into outlier detection methods and investigate their effectiveness in identifying potential anomalies inside tested information. Notwithstanding theoretical insights, this exploration incorporates a practical application where we exhibit the effect of outlier detection and robust estimation techniques on real-world quality control choices. By giving rules and recommendations for practitioners, this study expects to upgrade the reliability and effectiveness of truncated SSPs within the sight of outliers, eventually adding to further developed product quality and consumer satisfaction in manufacturing and other industries.
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