This book includes all of the papers presented at the NATO Symposium on Human Detection and Diagnosis of System Failures held at Roskilde, Denmark on August 4-8, 1980. The Symposium was sponsored by the Scientific Affairs Division of NATO and the Rise National Laboratory of Denmark. The goal of the Symposium was to continue the tradition initiated by the NATO Symposium on Monitoring Behavior and Supervisory Control held in Berchtesgaden, F .R. Germany in 1976 and the NATO Symposium on Theory and Measurement of Mental Workload held in Mati, Greece in 1977. To this end, a group of 85 psychologists and engineers coming from industry, government, and academia convened to discuss, and to generate a "state-of-the-art" consensus of the problems and solutions associated with the human IS ability to cope with the increasing scale of consequences of failures within complex technical systems. The Introduction of this volume reviews their findings. The Symposium was organized to include brief formal presentations of papers sent to participants about two months in advance of the meeting, and considerable discussion both during plenary sessions and within more specialized workshops. Summaries of the discussions and workshop reports appear in this volume.

Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

Due to the increasing demand for security and reliability in manufacturing and mechatronic systems, early detection and diagnosis of faults are key points to reduce economic losses caused by unscheduled maintenance and downtimes, to increase safety, to prevent the endangerment of human beings involved in the process operations and to improve reliability and availability of autonomous systems. The development of algorithms for health monitoring and fault and anomaly detection, capable of the early detection, isolation, or even prediction of technical component malfunctioning, is becoming more and more crucial in this context. This Special Issue is devoted to new research efforts and results concerning recent advances and challenges in the application of “Algorithms for Fault Detection and Diagnosis”, articulated over a wide range of sectors. The aim is to provide a collection of some of the current state-of-the-art algorithms within this context, together with new advanced theoretical solutions.

In an approach that combines coverage of safety and human error into a single volume, Safety and Human Error in Engineering Systems eliminates the need to consult many different and diverse sources for those who need information about both topics. The book begins with an introduction to aspects of safety and human error and a discussion of mathematical concepts that builds understanding of the material presented in subsequent chapters. The author describes the methods that can be used to perform safety and human error analysis in engineering systems and includes examples, along with their solutions, as well as problems to test reader comprehension. He presents a total of ten methods considered useful for performing safety and human error analysis in engineering systems. The book also covers safety and human error transportation systems, medical systems, and mining equipment as well as robots and software. Nowadays, engineering systems are an important element of the world economy as each year billions of dollars are spent to develop, manufacture, and operate various types of engineering systems around the globe. A rise in accidental deaths has put the spotlight on the role human error plays in the safety and failure of these systems. Written by an expert in various aspects of healthcare, engineering management, design, reliability, safety, and quality, this book provides tools and techniques for improving engineering systems with respect to human error and safety.

Forming connections between human performance and design, this new edition of Engineering Psychology and Human Performance examines human–machine interaction. The book is organized directly from a psychological perspective of human information processing, and chapters correspond to the flow of information as it is processed by a human being—from the senses, through the brain, to action—rather than from the perspective of system components or engineering design concepts. Upon completing this book, readers will be able to identify how human ability contributes to the design of technology; understand the connections within human information processing and human performance; challenge the way they think about technology’s influence on human performance; and show how theoretical advances have been, or might be, applied to improving human–machine interactions. This new edition includes the following key features: A new chapter on research methods Sections on interruption management and distracted driving as cogent examples of applications of engineering psychology theory to societal problems A greatly increased number of references to pandemics, technostress, and misinformation New applications Amplified emphasis on readability and commonsense examples Updated and new references throughout the text This book is ideal for psychology and engineering students, as well as practitioners in engineering psychology, human performance, and human factors. The text is also supplemented by online resources for students and instructors.

With increasing demands for efficiency and product quality plus progress in the integration of automatic control systems in high-cost mechatronic and safety-critical processes, the field of supervision (or monitoring), fault detection and fault diagnosis plays an important role. The book gives an introduction into advanced methods of fault detection and diagnosis (FDD). After definitions of important terms, it considers the reliability, availability, safety and systems integrity of technical processes. Then fault-detection methods for single signals without models such as limit and trend checking and with harmonic and stochastic models, such as Fourier analysis, correlation and wavelets are treated. This is followed by fault detection with process models using the relationships between signals such as parameter estimation, parity equations, observers and principal component analysis. The treated fault-diagnosis methods include classification methods from Bayes classification to neural networks with decision trees and inference methods from approximate reasoning with fuzzy logic to hybrid fuzzy-neuro systems. Several practical examples for fault detection and diagnosis of DC motor drives, a centrifugal pump, automotive suspension and tire demonstrate applications.