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The Measurement Analysis topic will provide the participant with the knowledge and skills necessary to effectively and efficiently examine the capability and capacity of measurement system. This field of study is often referred to as Measurement Systems Analysis, or MSA in short. The purpose of an MSA study is to establish the statistical potential of a measurement system, its short-term capability and its long-term capability. In this sense, the aim of a MSA study is to define and improve the extent of statistical uncertainty inherent to a given measurement system and its related operators, equipment, tools and procedures.
Through such a study, the underlying sources of measurement error can be identified, tracked down and ultimately eliminated or minimized; thereby, improving the capability and capacity to detect change in the performance variable of interest. When a measurement system lacks validity, reliability, repeatability or reproducibility, it is often difficult (if not impossible) to detect consequential changes in the product or service under investigation. In other words, positive or negative change in a product or service can go undetected if the measurement system error is too large or inconsistent. Hence, it is often necessary to improve the system of measurement prior to undertaking a process improvement project.
Of interest, a MSA study often calls upon the knowledge and skills associated with such things as descriptive statistics, basic charting and graphing, parametric methods, control charts, and design of experiments, just to mention a few. Specifically, the participant of this topic will learn how to plan, design, execute and report the results of a MSA study. In this context, it is easy to see why the study of measurement systems and related analytical methods is so important to a process improvement initiative. By way of this training, the participant will gain tremendous insight into the logic and reasoning which underlies Six Sigma and the process of breakthrough improvement.
Reinforcement of major concepts, techniques, and application is realized through exercises, scenarios, and case studies. The following prerequisite topics are listed in sequential learning order: Basic Statistics, Hypothesis Testing, Confidence Intervals, Parametric Methods and Experimental Methods. Total instructional time for this topic is 1 hour and 16 minutes.