The work is a context-oriented analysis and synthesis of complex engineered systems to ensure continuous and safe operations under conditions of uncertainty. The book is divided in four parts, the first one comprises an overview of the development of systems engineering: starting with basics of Systems Science and Single Systems Engineering, through System of Systems Engineering to Cognitive Systems Engineering. The Cognitive Systems Engineering model was based on the concept of imperfect knowledge acquisition and management. The second part shows the evolutionary character of the dependability concept over the last fifty years. Beginning from simple models based on the classical probability theory, through the concepts of tolerating faults, as well as resilience engineering, we come to the assumptions of Cognitive Dependability Engineering (CDE), based on the concept of continuous smart operation, both under normal and abnormal conditions. The subject of the next part is analysis and synthesis of Cyber-Physical-Social (CPS) Systems. The methodology consists of the following steps: modeling CPS systems' structure, simulating their behavior in changing conditions and in situations of disruptions, and finally assessing the dependability of the entire system based on CDE. The last part of the work answers the question of how to deal with risks in CPS systems in situations of high level of uncertainty. The concept of a Cognitive Digital Twin was introduced to support the process of solving complex problems by experts, and on this basis a framework for cognitive dependability based problemsolving in CPS Systems operating under deep uncertainty was developed. The possibilities and purposefulness of using this framework have been demonstrated with three practical examples of disasters that have happened in the past and have been thoroughly analyzed.

Powerful information technologies and the complex support systems they engender are evolving faster than people’s ability to adjust to them. In the workplace, this leads to troublesome task performance, added stress on users, increased organizational inefficiency, and, in some cases, a heightened risk of wide-scale .disaster. In the marketplace, it makes for consumer dissatisfaction. Clearly, traditional human-computer interaction (HCI) and system design (SD) solutions to this dilemma have proven woefully inadequate. What is needed is a fresh multidisciplinary approach offering a broader, more dynamic framework for assessing needs and designing usable, efficient systems. Taking modeling concepts from engineering, psychology, cognitive science, information science, and computer science, cognitive systems engineering (CSE) provides such a framework. This book is the first comprehensive guide to the emerging new field of CSE. Providing equal parts theory and practice, it is based on the authors’ many years of experience with work systems in a wide range of work domains, including process control, manufacturing, hospitals, and libraries. Throughout, the emphasis is on powerful analytical techniques that enhance the systems designer’s ability to see the "big picture," and to design for all crucial aspects of human-work interaction. Applicable to highly structured technical systems such as process plants, as well as less structured user-driven systems like libraries, these analytical techniques form the basis for the evaluation and design guidelines that make up the bulk of this book. And since the proof is in the pudding, the authors provide a chapter-length case history in which they demonstrate the success of their approach when applied to a full-scale software design project. The project, a retrieval system for public libraries, is described in detail, from field studies to concept validation experiments, and, of course, the empirical evaluation of the system while in use by the library users and personnel. Computer-based information systems are rapidly becoming a fundamental part of the human landscape. How that landscape evolves over the next decade or so, whether it becomes a hostile one or one that generously supports the needs of future generations, is in the hands of all those involved with the study and design of information systems.

Nothing has been more prolific over the past century than human/machine interaction. Automobiles, telephones, computers, manufacturing machines, robots, office equipment, machines large and small; all affect the very essence of our daily lives. However, this interaction has not always been efficient or easy and has at times turned fairly hazardous.

This handbook is the first to provide comprehensive coverage of original state-of-the-science research, analysis, and design of integrated, human-technology systems.

This Handbook serves as a single source for theories, models, and methods related to cognitive task design. It provides the scientific and theoretical basis required by industrial and academic researchers, as well as the practical and methodological guidance needed by practitioners who face problems of building safe and effective human-technology s

The growing dependence of working environments on complex technology has created many challenges and lead to a large number of accidents. Although the quality of organization and management within the work environment plays an important role in these accidents, the significance of individual human action (as a direct cause and as a mitigating factor) is undeniable. This has created a need for new, integrated approaches to accident analysis and risk assessment.This book detailing the use of CREAM is, therefore, both timely and useful. It presents an error taxonomy which integrates individual, technological and organizational factors based on cognitive engineering principles. In addition to the necessary theoretical foundation, it provides a step-by-step description of how the taxonomy can be applied to analyse as well as predict performance using a context-dependent cognitive model.CREAM can be used as a second-generation human reliability analysis (HRA) approach in probabilistic safety assessment (PSA), as a stand-alone method for accident analysis and as part of a larger design method for interactive systems. In particular, the use of CREAM will enable system designers and risk analysts to: • identify tasks that require human cognition and therefore depend on cognitive reliability • determine the conditions where cognitive reliability and ensuing risk may be reduced • provide an appraisal of the consequences of human performance on system safety which can be used in PSA.

For Resilience Engineering, 'failure' is the result of the adaptations necessary to cope with the complexity of the real world, rather than a malfunction. Human performance must continually adjust to current conditions and, because resources and time are finite, such adjustments are always approximate. Featuring contributions from leading international figures in human factors and safety, Resilience Engineering provides thought-provoking insights into system safety as an aggregate of its various components - subsystems, software, organizations, human behaviours - and the way in which they interact.