This book provide a comprehensive set of modeling methods for data and uncertainty analysis, taking readers beyond mainstream methods and focusing on techniques with a broad range of real-world applications. The book will be useful as a textbook for graduate students, or as a training manual in the fields of calibration and testing. The work may also serve as a reference for metrologists, mathematicians, statisticians, software engineers, chemists, and other practitioners with a general interest in measurement science.

Metrology is the science of measurements. As such, it deals with the problem of obtaining knowledge of physical reality through its quantifiable properties. The problems of measurement and of measurement accuracy are central to all natural and technical sciences. Now in its second edition, this monograph conveys the fundamental theory of measurement and provides some algorithms for result testing and validation.

This book seeks to promote the structured, standardized and accurate use of software measurement at all levels of modern software development companies. To do so, it focuses on seven main aspects: sound scientific foundations, cost-efficiency, standardization, value-maximization, flexibility, combining organizational and technical aspects, and seamless technology integration. Further, it supports companies in their journey from manual reporting to automated decision support by combining academic research and industrial practice. When scientists and engineers measure something, they tend to focus on two different things. Scientists focus on the ability of the measurement to quantify whatever is being measured; engineers, however, focus on finding the right qualities of measurement given the designed system (e.g. correctness), the system’s quality of use (e.g. ease of use), and the efficiency of the measurement process. In this book, the authors argue that both focuses are necessary, and that the two are complementary. Thus, the book is organized as a gradual progression from theories of measurement (yes, you need theories to be successful!) to practical, organizational aspects of maintaining measurement systems (yes, you need the practical side to understand how to be successful). The authors of this book come from academia and industry, where they worked together for the past twelve years. They have worked with both small and large software development organizations, as researchers and as measurement engineers, measurement program leaders and even teachers. They wrote this book to help readers define, implement, deploy and maintain company-wide measurement programs, which consist of a set of measures, indicators and roles that are built around the concept of measurement systems. Based on their experiences introducing over 40,000 measurement systems at over a dozen companies, they share essential tips and tricks on how to do it right and how to avoid common pitfalls.

This volume collects the refereed contributions based on the presentations made at the Seventh Workshop on Advanced Mathematical and Computational Tools in Metrology, a forum for metrologists, mathematicians and software engineers that will encourage a more effective synthesis of skills, capabilities and resources. The volume contains articles by world renowned metrologists and mathematicians involved in measurement science and, together with the six previous volumes in this series, constitutes an authoritative source of the mathematical, statistical and software tools necessary in modern metrology. Contents: Modeling Measurement Processes in Complex Systems with Partial Differential Equations: From Heat Conduction to the Heart (M Baer et al.); Mereotipological Approach for Measurement Software (E Benoit & R Dapoigny); Data Evaluation of Key Comparisons Involving Several Artefacts (M G Cox et al.); Box-Cox Transformations Versus Robust Control Charts in Statistical Process Control (M I Gomes & F O Figueiredo); Decision Making Using Sensor's Data Fusion and Kohonen Self Organizing Maps (P S Girao et al.); Generic System Design for Measurement Databases Applied to Calibrations in Vacuum Metrology, Bio-Signals and a Template System (H Gro et al.); Repeated Measurements: Evaluation of Their Uncertainty from the Viewpoints of Classical and Bayesian Statistics (I Lira & W Woger); Detection of Outliers in Interlaboratory Testing and Some Thoughts About Multivariate Precision (C Perruchet); On Appropriate Methods for the Validation of Metrological Software (D Richter et al.); Data Analysis-A Dialogue (D S Sivia); Validation of a Virtual Sensor for Monitoring Ambient Parameters (P Ciarlini et al.); Evaluation of Standard Uncertainties in Nested Structures (E Filipe); Linking GUM and ISO 5725 (A B Forbes); Monte Carlo Study on Logical and Statistical Correlation (B Siebert et al.); Some Problems Concerning the Estimate of the Uncertainty of the Degree of Equivalence in MRA Key Comparisons (F Pavese); Preparing for a European Research Area Network in Metrology: Where are We Now? (M Kuhne et al.); and other papers. Readership: Researchers, graduate students, academics and professionals in metrology.

Metrology and Instrumentation: Practical Applications for Engineering and Manufacturing provides students and professionals with an accessible foundation in the metrology techniques, instruments, and governing standards used in mechanical engineering and manufacturing. The book opens with an overview of metrology units and scale, then moves on to explain topics such as sources of error, calibration systems, uncertainty, and dimensional, mechanical, and thermodynamic measurement systems. A chapter on tolerance stack-ups covers GD&T, ASME Y14.5-2018, and the ISO standard for general tolerances, while a chapter on digital measurements connects metrology to newer, Industry 4.0 applications.