The Uncertainty Of Measurements

The uncertainty of measurement results is drawing attention of managers, metrologists and customers. The accuracy of measurements affects all of us in trade, commerce, safety, health care environmental protection and more. The quality of these measurements are regulated by a variety of government agencies. Measurement also plays an important role in manufacturing and service organizations. Use this book to learn more about metrology and the need for reliable measurements. You can also learn about measurement system and quality of measurement systems, objectives and methods. Statistical techniques in metrology are also explained. Examples of measurement data and random variables, probability density functions, sampling distribution, statistical estimation degrees of freedom and regression are included. An entire chapter is devoted to measurement errors. The book goes in-depth into explaining national and international measurement systems and standards, and includes a complete chapter on calibration and measurement trace ability. Measurement Uncertainty will show how to evaluate various uncertainties in measurements using several approaches including international consensus. Calibration laboratories can look specifically at the chapter on that profession to guide them in their measurement improvements. Kimothi also looks at specific industries and their measurement capabilities and includes examples of R&R studies. A great resource for the CQE, CQT, CCT, CSSBB certification exams!

Measurement shapes scientific theories, characterises improvements in manufacturing processes and promotes efficient commerce. In concert with measurement is uncertainty, and students in science and engineering need to identify and quantify uncertainties in the measurements they make. This book introduces measurement and uncertainty to second and third year students of science and engineering. Its approach relies on the internationally recognised and recommended guidelines for calculating and expressing uncertainty (known by the acronym GUM). The statistics underpinning the methods are considered and worked examples and exercises are spread throughout the text. Detailed case studies based on typical undergraduate experiments are included to reinforce the principles described in the book. This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.

This book fulfills the global need to evaluate measurement results along with the associated uncertainty. In the book, together with the details of uncertainty calculations for many physical parameters, probability distributions and their properties are discussed. Definitions of various terms are given and will help the practicing metrologists to grasp the subject. The book helps to establish international standards for the evaluation of the quality of raw data obtained from various laboratories for interpreting the results of various national metrology institutes in an international inter-comparisons. For the routine calibration of instruments, a new idea for the use of pooled variance is introduced. The uncertainty calculations are explained for (i) independent linear inputs, (ii) non-linear inputs and (iii) correlated inputs. The merits and limitations of the Guide to the Expression of Uncertainty in Measurement (GUM) are discussed. Monte Carlo methods for the derivation of the output distribution from the input distributions are introduced. The Bayesian alternative for calculation of expanded uncertainty is included. A large number of numerical examples is included.

The expression of uncertainty in measurement poses a challenge since it involves physical, mathematical, and philosophical issues. This problem is intensified by the limitations of the probabilistic approach used by the current standard (the GUM Instrumentation Standard). This text presents an alternative approach. It makes full use of the mathematical theory of evidence to express the uncertainty in measurements. Coverage provides an overview of the current standard, then pinpoints and constructively resolves its limitations. Numerous examples throughout help explain the book’s unique approach.

The uncertainty of measurement results is drawing attention of managers, metrologists and customers. The accuracy of measurements affects all of us in trade, commerce, safety, health care environmental protection and more. The quality of these measurements are regulated by a variety of government agencies. Measurement also plays an important role in manufacturing and service organizations. Use this book to learn more about metrology and the need for reliable measurements. You can also learn about measurement system and quality of measurement systems, objectives and methods. Statistical techniques in metrology are also explained. Examples of measurement data and random variables, probability density functions, sampling distribution, statistical estimation degrees of freedom and regression are included. An entire chapter is devoted to measurement errors. The book goes in-depth into explaining national and international measurement systems and standards, and includes a complete chapter on calibration and measurement trace ability. Measurement Uncertainty will show how to evaluate various uncertainties in measurements using several approaches including international consensus. Calibration laboratories can look specifically at the chapter on that profession to guide them in their measurement improvements. Kimothi also looks at specific industries and their measurement capabilities and includes examples of R&R studies. A great resource for the CQE, CQT, CCT, CSSBB certification exams!

The scienti c method is based on the measurement of di erent physical qu- tities and the search for relations between their values. All measured values of physical quantities are, however, a ected by uncertainty. Understanding the origin of uncertainty, evaluating its extent, and suitably taking it into account in data analysis, are fundamental steps for assessing the global accuracy of physical laws and the degree of reliability of their technological applications. The introduction to uncertainty evaluation and data analysis procedures is generally made in laboratory courses for freshmen. During my long-lasting teaching experience, I had the feeling of some sort of gap between the ava- able tutorial textbooks, and the specialized monographs. The present work aims at lling this gap, and has been tested and modi ed through a feedback interaction with my students for several years. I have tried to maintain as much as possible a tutorial approach, that, starting from a phenomenolo- cal introduction, progressively leads to an accurate de nition of uncertainty and to some of the most common procedures of data analysis, facilitating the access to advanced monographs. This book is mainly addressed to - dergraduate students, but can be a useful reference for researchers and for secondary school teachers. The book is divided into three parts and a series of appendices. Part I is devoted to a phenomenological introduction to measurement and uncertainty. In Chap.

It is now becoming recognized in the measurement community that it is as important to communicate the uncertainty related to a specific measurement as it is to report the measurement itself. Without knowing the uncertainty, it is impossible for the users of the result to know what confidence can be placed in it; it is also impossible to assess the comparability of different measurements of the same parameter. This volume collects 20 outstanding papers on the topic, mostly published from 1999-2002 in the journal "Accreditation and Quality Assurance." They provide the rationale for why it is important to evaluate and report the uncertainty of a result in a consistent manner. They also describe the concept of uncertainty, the methodology for evaluating uncertainty, and the advantages of using suitable reference materials. Finally, the benefits to both the analytical laboratory and the user of the results are considered.

It is now widely recognized that measurement data should be properly analyzed to include an assessment of their associated uncertainty. Since this parameter allows for a meaningful comparison of the measurement results and for an evaluation of their reliability, its expression is important not only in the specialized field of scientific metrology, but also in industry, trade, and commerce. General rules for evaluating and expressing the uncertainty are given in the internationally accepted ISO Guide to the Expression of Uncertainty in Measurement, generally known as the GUM. Evaluating the Measurement Uncertainty details the theoretical framework on which the GUM is based and provides additional material on more advanced topics such as least-squares adjustment and Bayesian statistics. The book does not require previous knowledge other than elementary calculus and can be read as a complement to the GUM or as a stand-alone reference source. It stresses fundamental principles and illustrates their applications through numerous examples taken from many different fields of metrology. The book includes practical guidance as well as theoretical aspects, resulting in an invaluable resource for metrologists, engineers, physicists, and graduate students involved with measurements in academia and industry.