Human-machine systems

Human-machine systems

Complex systems that comprise both humans and machines. Human-machine systems engineering is the analysis, modeling, and design of such systems. It is distinguished from the more general field of human factors and from the related fields of human-computer interaction, engineering psychology, and sociotechnical systems theory in three general ways. First, human-machine systems engineering focuses on large, complex, dynamic control systems that often are partially automated (such as flying an airplane, monitoring a nuclear power plant, or supervising a flexible manufacturing system). Second, human-machine systems engineers build quantitative or computational models of the human-machine interaction as tools for analysis and frameworks for design. Finally, human-machine systems engineers study human problem-solving in naturalistic settings or in high-fidelity simulation environments. See Human-computer interaction, Human-factors engineering

Thus, human-machine systems engineering focuses on the unique challenges associated with designing joint technological and human systems. Historically it has grown out of work on cybernetics, control engineering, information and communication theory, and engineering psychology. Subsequently, researchers who focus on cognitive human-machine systems (in which human work is primarily cognitive rather than manual) have also referred to their specialization as cognitive engineering or cognitive systems engineering. See Cybernetics, Information theory

The four major aspects of human-machine systems, in roughly historical order, are systems in which the human acts as a manual controller, systems in which the human acts as a supervisory controller, human interaction with artificial-intelligence systems, and human teams in complex systems. This general progression is related to advances in computer and automation technology. With the increasing sophistication and complexity of such technology, the human role has shifted from direct manual control to supervisory control of physical processes, to supervision of intelligent systems, and finally, with an increasing emphasis on the social and organizational aspects of complex systems, to teamwork in complex environments.

Aviation is an example of a human-machine system in which all of these developments have occurred. Early work in aircraft systems focused on manual control models of pilot performance. With increasing levels of automation, the pilot shifted to a more supervisory role in which tasks such as planning and programming the flight management computer became the predominant form of work. See Aircraft instrumentation, Flight controls

References in periodicals archive ?
Ironically, those boundaries may begin to fade in time, as human-machine systems become truly symbiotic.
Related problems were considered in several papers dealing with human-operator monitoring in human-machine systems (HMS).
Viewing the capabilities of autonomous systems within the context of human-machine systems recognizes a critical role for humans coupling the advantages of both allowing for operational application previously non-existent.
Also raised were issues around metrics for complex human-machine systems; user acceptance of recommendations; and efficient data management, architectures, and computational processing for large amounts of dynamic data.
Intelligent Human-Machine Systems and Cybernetics; proceedings; 2 volume set
THE LAB Intelligent Human-Machine Systems Lab, Northeastern University College of Engineering, Boston.
International Conference on Intelligent Human-Machine Systems and Cybernetics (5th: 2013: Hangzhou, Zhejiang, China)
We calculated the bandwidths and the information transmission rates of the human-machine systems using techniques developed for the study of manual control tasks [6-9,16].
The 165 papers of this 2-volume proceedings were first presented at the 2010 Internatinal Conference on Intelligent Human-Machine Systems and Cybernetics, held in Nanjing, China, in August and organized by the U.
Analysis of human-machine systems recognizes that both humans and machine elements can fail, and that human errors can have varying effects on a system.
"We've always known that behavioral and psychological research on an array of subjects, from psychopharmacology to human-machine systems design, has important implications for many organizations outside of the academic realm," said Linda Beebe, senior director of PsycINFO.

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