An Analytical Framework for Assessing the Complexity of Human-Machine Systems

Abstract

This research explores the use of axiomatic design principles for analyzing coupling in human-machine systems. Coupling is a generic dimension of complexity, and coupling between user goals and user actions widens the gulf of execution. An analytical framework was constructed based on the concept of design domains. This framework formalizes the interaction between user goals, functional requirements, design parameters, and user actions. User goals and user actions describe tasks from a user's perspective. Functional requirements and design parameters describe system's structure from an engineering perspective. Design equations are used to as a notation for representing the interaction between these attributes, and as a tool for characterizing the degree of coupling. By providing a general and rational criterion, the proposed method is conceived as an analytical tool that design engineers can use for early evaluations.

Get full access to this article

View all access options for this article.

References

Bisantz

A. M.

Vicente

K. J.

(1994). Making the abstraction hierarchy concrete. International Journal of Human-Computer Studies, 40, 83–117.

Disnatz

(1996). The logic of failure: Why things go wrong and what we can do to make them right. New York, NY: Henry Holt.

Endsley

M. R.

(1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37 (1), 32–64.

Halford

Wilson

Philips

(1997). Abstraction: Nature, costs and benefits International Journal of Educational Research, 21–35.

Helander

M. G.

(2003). Couplings among HCI design parameters cause poor usability. In Proceedings of human factors and ergonomics society 47th annual meeting. Santa Monica, CA: Human Factors and Ergonomics Society.

Helander

M. G.

Lin

(2000). Anthropometric design of workstations. In Tate

Proceedings of the first international conference on axiomatic design - ICAD2000 (pp. 130–138). Cambridge, MA: Institute for Axiomatic Design.

Helander

M. G.

Lin

(2002). Axiomatic design in ergonomics and an extension of the information axiom. Journal of Engineering Design, 13(4), 321–339.

Hirschi

N. W.

Frey

D. D.

(2002). Cognition and complexity: An experiment on the effect of coupling in parameter design. Research in Engineering Design, 13, 123–131.

Lee

Yoon

W. C.

(2004). Coupling structural and functional models for interaction design. Interacting with Computers, 16, 144–161.

10.

Helander

M. G.

(2004). Method for analyzing the usability of consumer products. In Proceedings of the third international conference on axiomatic design - ICAD2004. Seoul, Korea: Institute for Axiomatic Design.

11.

Miller

(2000). The human factor in complexity. In Weyrauch

Sa-Mad

Automation, control and complexity: An integrated approach (pp. 35–57). Singapore: John Wiley & Sons.

12.

National Academy of Sciences. (2002). Approaches to improve engineering design. Retrieved 2 June, 2003, from http://books.nap.edu/books/;NI000469/html/R1.html.

13.

Norman

D. A.

(1988). The psychology of everyday things. New York, NY: BasicBooks.

14.

Quill

Kancler

D. E.

Revels

A. R.

Batchelor

(2001). Application of information visualization at various stages of system development. In Proceedings of the human factors and ergonomics society 45th annual meeting (pp. 1713–1717). Santa Monica, CA: Human Factors Society.

15.

Rasmussen

(1985). The role of hierarchical knowledge representation in decision making and system management. IEEE Transactions on Systems, Man, and Cybernetics, 15 234–243.

16.

Suh

N. P.

(1990). The principles of design. New York, NY: Oxford University Press.

17.

Suh

N. P.

(2001). Axiomatic design: Advances and applications. New York, NY: Oxford University Press.

18.

C.-Y.

Chen

S.-J.

Lin

(2003). A structured approach to measuring functional dependency and sequencing of coupled tasks in engineering design. Computers and Industrial Engineering, 45(1), 195–214.

19.

Vicente

K. J.

(1999). Cognitive work analysis: Toward safe, productive, and healthy computer-based work. Mahwah, NJ: Lawrence Erlbaum Associates.

20.

Whitefield

Wilson

Dowell

(1991). A framework for human factors evaluation. Behaviour and Information Technology, 10, 65–79.

21.

Woods

D. D.

(1988). Coping with complexity: The psychology of human behaviour in complex systems. In Goodstein

L. P.

Andersen

H. B.

Olsen

S. E.

Tasks, errors and mental models: A festschrift to celebrate the 60th birthday of Professor Jens Rasmussen (pp. 129–147). New York, NY: Taylor & Francis.