Abstract

This study examines the Evaluation of Measurement System Analysis (MSA) Techniques for Screw Shaft Manufacturing in a Teaching Factory Setting at Politeknik STMI Jakarta. The research investigates the precision and accuracy of the measurement system using statistical methods such as Analysis of Variance (ANOVA), Number of Distinct Categories (NDC), and metrics like Total Gauge Repeatability and Reproducibility (GRR), Repeatability, and Reproducibility. Through comprehensive data collection, including multiple appraisers across various trials measured quantitative surveys and qualitative observations, Screw Shaft dimensions and tolerances. The collected data underwent thorough statistical analysis utilizing ANOVA to explore the sources of variation in measurements. The results of the MSA analysis provided critical insights into the measurement system's performance. Repeatability variability (9.97%) and reproducibility variability (3.80%) contribute to a total GRR of 10.67%, indicating an acceptable measurement system. Part-to-part variation emerged as the primary source of variability, emphasizing the importance of addressing part differences in quality control processes. Moreover, ANOVA highlighted the influence of different factors on measurement consistency. Part variations significantly impacted measurement variability, underscoring the need to manage part differences effectively. The assessment of repeatability and reproducibility revealed insights into measurement consistency and reliability. These findings carry significant implications for both industry and education. Understanding the factors affecting measurement variability enables the implementation of corrective measures to enhance product quality and consistency. Additionally, advancements in measurement techniques and quality management practices in Teaching Factory environments contribute to improved product quality and competitiveness in industrial settings. Continued research and evaluation are crucial for further enhancing measurement systems and manufacturing processes.

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