Using design equations to identify sources of complexity in human–machine interaction

Abstract

A coupled design is generally more difficult to use than an uncoupled design. It should therefore be replaced by an uncoupled design. The problem described in this paper is to identify sources of couplings and propose new design parameters that uncouple the design. A method based on Suh's axiomatic design (AD) was developed. There are two axioms in AD. The first axiom proclaims that design parameters should be selected so that functional requirements become independent. Based on this, a method for Human Factors Design was devised. It is called Design Equations for Systems Analysis (DESA). Several case studies of human factors design problems were analysed: a refrigerator, hand tools and a driver's compartment. As demonstrated in the case studies, DESA is useful for analysis of existing design solutions as well as for synthesis of new design alternatives. The second axiom in AD aims at minimizing information in design. It should be noted that this is in agreement with Hick's law and Fitts’ law. The calculation of information or entropy in design was demonstrated for an adjustable workstation. The second axiom was adapted to human factors design by taking into account the variability of human attributes, in this case anthropometric measures. If the manufacturer's supplied adjustability range and the users’ desired range are known, the entropy or information of an adjustable workstation can be quantified. In comparing several workstations, the workstation with the least information should be selected.

Keywords:

• Complexity
• Axiomatic design
• Coupled design
• Information theory
• Entropy
• DESA

Acknowledgement

This research was funded in part by a grant from the US Air Force Research Laboratory, under agreement number FA5209–04-P-0320. The US Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Research Laboratory or the US Government.