Overview

Welcome to the Tabtrainer® Masterclass Series - your expert platform for data-driven quality assurance and advanced measurement system analysis.In this training, you will master Gage Linearity and Bias Studies using Minitab, focusing on real industrial applications such as ultrasonic non-destructive testing (NDT). Based on a real case from the Smartboard Company, you will analyze how systematic measurement deviations can emerge after probe replacement - and how to detect, quantify, and correct them statistically.Led by Prof. Dr. Murat Mola, TÜV-certified expert and founder of Tabtrainer®, this course provides hands-on methods to ensure measurement accuracy, instrument stability, and compliance with AIAG standards - enabling confident decisions in quality-critical environments.Key Learning ObjectivesThis course provides a comprehensive, hands-on training in evaluating the accuracy and reliability of measurement systems, focusing on stability and bias analysis in the context of ultrasonic non-destructive testing (NDT). Based on a real-world industrial case from Smartboard Company, the course demonstrates how to verify and correct systematic measurement deviations after a probe replacement in an ultrasonic testing instrument.Participants will explore the fundamentals and advanced applications of Gage Linearity and Bias Studies, applying AIAG guidelines to assess whether the instrument delivers accurate, consistent, and statistically valid results across the entire operating range:Understand the physical principles and industrial application of ultrasonic testing for void detection in skateboard axles.Define and distinguish between stability, bias, and linearity in measurement systems.Conduct a full measurement system analysis (MSA) using a structured dataset of 100 values (10 parts x 10 repetitions).Use statistical software to execute Gage Linearity and Bias Studies, incorporating process variation benchmarks (e.g., 6σ).Interpret analysis outputs including absolute/percentage bias, regression slope, and p-values for hypothesis testing.Visualize deviations using scatterplots, confidence intervals, and bar charts, and relate findings to real-world quality implications.Quantify and differentiate constant, variable, and nonlinear distortions in measurement behavior.Apply correction strategies using mean bias values to statistically eliminate systematic measurement errors.Evaluate the effectiveness of correction factors by re-running bias and linearity studies on corrected data.Understand the business relevance of minimizing scrap rates, ensuring measurement integrity, and avoiding false rejections due to instrumentation bias.Practical Relevance:This course simulates a real testing environment in which voids in metallic components are evaluated using ultrasonic techniques. Voids, when undetected or mismeasured, may cause early failure and expensive scrap. Ensuring the reliability of the measurement system is essential not only for quality control but also for cost efficiency and compliance with industrial standards.Through a combination of data handling, statistical interpretation, and graphical evaluation, the training builds competence in data-driven decision making and measurement system optimization.Target Audience:This training is designed for:Quality engineers and techniciansProduction and process engineersSix Sigma practitionersMetrology and test engineersAnyone responsible for ensuring accurate, traceable measurements in manufacturing environmentsTools Used:Minitab or equivalent statistical softwareDataset: MSA_Ultrasonic.xlsReal production-based measurement examplesGraphical tools (scatterplot, regression, bias analysis)

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