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Robotics & Computer Vision, Cognitive Science, Engineering - Safety & Reliability, Cognitive Psychology
Cognitive Reliability And Error Analysis Method (Cream)Cream by E. Hollnagel β€” book cover

Cognitive Reliability And Error Analysis Method (Cream)Cream

by E. Hollnagel
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Overview

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:
β€’ identify tasks that require human cognition and therefore depend on cognitive reliability
β€’ determine the conditions where cognitive reliability and ensuing risk may be reduced
β€’ provide an appraisal of the consequences of human performance on system safety which can be used in PSA.

Synopsis

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.

About the Author, E. Hollnagel

Dr. Erik Hollnagel is Principal Advisor at the OECD Halden Reactor Project (Norway) and Adjunct Professor of Human-Machine Interaction at the University of Linköping (Sweden). He has many years of experience with man-machine systems acquired in both industry and universities, and has worked extensively with the problems of human reliability and human-machine interaction in the fields of nuclear power, aerospace and computer systems.

Dr. Hollnagel is the author of more than 200 papers and five books in the fields of man-machine systems, interface design, expert systems, cognitive engineering and human reliability. He is currently Chairman of the European Association for Cognitive Ergonomics (EACE).

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Book Details

Published
January 1, 1998
Publisher
Elsevier Science
Pages
304
Format
Hardcover
ISBN
9780080428482

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