Preface: Cognitive engineering in automated systems design

David B. Kaber, John M. Usher
<span title="">2000</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/z5a4apwv3rhnbjz6btv45hikoa" style="color: black;">Human Factors and Ergonomics in Manufacturing</a> </i> &nbsp;
This special issue was motivated by an apparent paucity of research on applications of cognitive engineering principles in the design of complex systems including maintenance, manufacturing, and transportation systems. Cognitive engineering, in simple terms, is the discipline of considering human thinking (or cognition) in designing humanmachine systems. It has been formally defined as the intersection of human factors engineering and experimental psychology (Wickens, 1992) . It involves
more &raquo; ... ing a knowledge base on human information processing capabilities and formulating humancentered system design alternatives. Cognitive engineering applies a human behavior and performance perspective to system design. Aspects of human cognition found to be critical in designing human interfaces for complex systems include perception, attention, memory, situation awareness, and decision making or response selection. Ancillary factors include cognitive workload, stress, and personality factors. Substantial empirical research has been conducted to describe human cognitive performance capabilities in laboratory experiments involving low-fidelity simulations of, for example, flexible manufacturing system (FMS) control, aircraft flight tasks, air traffic control, and so forth. Unfortunately, little fieldwork has been done to describe the impact of real-world system design on human performance. Applied cognitive engineering research is important because prior to the 1990s the majority of errors and failures of complex human-machine systems, such as catastrophic airliner crashes, were attributed primarily to operator error (Heinrich, Petersen, & Ross, 1980) . A new paradigm has developed within the recent past, however, identifying poor system design as the root cause of human errors and malfunctions, which are merely a symptom of greater design flaws. With this in mind, there is a need to describe methods for improving real, complex system design based on human information processing capacity and to document successes and failures in the application of cognitive engineering principles to automated systems. The purpose of this special issue is to provide a sample of current methods and empirical studies related to the application of cognitive engineering to the design and operation of complex systems. Our goal for the special issue is that it will provide researchers and practitioners working in the field of manufacturing with insight into the need for, and potential effectiveness of, considering human cognition in designing advanced manufacturing technologies. We also hope that the special issue will promote cross-fertilization of the two broad research areas of manufacturing engineering and cognitive engineering. Recent research (Kaber & Usher, 1998) has demonstrated that many methods developed through manufacturing science with the objective of reflecting human information processing in, for example, supervisory control workstation design for a FMS have previ-
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