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所在平台: Udemy |
课程主页: https://www.udemy.com/course/tabtrainer-minitab-msa-gage-stability-and-bias-study/
课程评论：没有评论
课程名称：Minitab中的量具偏差与线性 - Tabtrainer大师班 课程概述： 欢迎参加Tabtrainer®大师班系列，这是一个专注于数据驱动质量保证与高级测量系统分析的专业平台。该培训课程将使您掌握使用Minitab进行的量具线性和偏差研究，特别关注超声波无损检测（NDT）等实际工业应用。基于Smartboard公司的真实案例，您将分析在探头更换后如何出现系统测量偏差，并学习如何通过统计方法检测、量化和纠正这些偏差。 该课程由TÜV认证专家、Tabtrainer®的创始人穆拉特·莫拉教授主讲，提供实践方法确保测量的准确性、仪器稳定性，以及符合AIAG标准，帮助您在质量关键环境中做出自信决策。 主要学习目标： 本课程提供了对测量系统准确性和可靠性评估的全面实践培训，着重于超声波无损检测（NDT）中的稳定性和偏差分析。通过Smartboard公司实际工业案例，课程演示了如何在超声波检测仪器探头更换后验证和纠正系统测量偏差。 参与者将探索量具线性和偏差研究的基础知识和高级应用，应用AIAG指南评估仪器在整个操作范围内是否提供准确、一致和统计有效的结果： - 理解超声波检测物理原理及其在滑板轴承中空洞检测的工业应用。 - 定义并区分测量系统中的稳定性、偏差和线性。 - 使用100个值（10个部件×10次重复）的结构化数据集进行完整的测量系统分析（MSA）。 - 使用统计软件执行量具线性和偏差研究，结合过程变化基准（如6σ）。 - 解读分析输出，包括绝对/百分比偏差、回归斜率和假设检验的p值。 - 使用散点图、置信区间和条形图可视化偏差，并将发现与现实世界的质量影响相关联。 - 量化并区分测量行为中的常量、变量和非线性失真。 - 使用平均偏差值应用纠正策略，统计消除系统测量错误。 - 通过在修正数据上重新进行偏差和线性研究，评估纠正因子的有效性。 - 理解最大限度减少废料、确保测量完整性和避免由于仪器偏差引起的错误拒绝的业务相关性。 实践相关性： 本课程模拟真实的测试环境，在该环境中使用超声波技术评估金属部件中的空洞。未检测到或测量不当的空洞可能导致早期故障和昂贵的废料。因此，确保测量系统的可靠性对于质量控制、成本效率以及符合工业标准至关重要。 通过数据处理、统计解释和图形评估的结合，培训建立了数据驱动决策和测量系统优化的能力。 目标受众： 本培训专为以下人员设计： - 质量工程师和技术人员 - 生产和工艺工程师 - 六西格玛从业者 - 计量和测试工程师 - 任何负责确保制造环境中准确可追溯测量的人士 使用工具： - Minitab或等效的统计软件 - 数据集：MSA_Ultrasonic.xls - 基于实际生产的测量示例 - 图形工具（散点图、回归、偏差分析）
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)
