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Measurement System Analysis provides a formal method to evaluate the accuracy and precision of a measurement gauge. Although it is an important topic, it is typically omitted in introductory statistics classes, and often only receives cursory coverage in lab. This paper describes how this topic is introduced through experiential learning to ChE sophomores at Oregon State University (OSU). The introductory concepts are presented in class where a “text book” example allows students to learn how to decompose the variance components of a measurement gauge. In a homework assignment, students are asked to work through a case study from industry. This analysis leads to the quantification of the gauge’s precision in terms of repeatability and reproducibility. They are then asked to perform a similar analysis on measurements that they take in the lab from a different gauge. In this lab, they make a series of thickness measurements of silicon dioxide films using an ellipsometer; however, in principle, this approach can be applied to any measurement system available in the undergraduate lab. In their report, they are required to calculate the repeatability and reproducibility of the gauge “by hand” in Excel. The experimental results and calculations are assessed by the instructor with output from commercial statistics software package, StatGraphics; thus, the accuracy of the numerical results of each group can be checked even though they all have independent data sets. In Spring 2004, 49 students completed this case study/lab project. Introduction As educators are well aware, the customary educational setting in which students develop problem solving skills is one where the numerical values presented are specific and absolute. The deterministic nature of the end-of-chapter type problems is imbedded in their minds well before students even matriculate. However, as practicing engineers, they will confront the variation associated with measured data in the real world. Statistics can be defined as the science of how to collect, analyze, interpret and present data with the purpose of understanding variation in a system. A key objective of integrating statistics into the ChE curriculum is to have students recognize variation is inevitable, and teach them skills to quantify the variation and make engineering decisions which account for it. Indeed, the importance of statistics is well recognized

Introducing Che Sophomores To Measurement System Analysis And Analysis Of Variance Through Experiential Learning