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Abstract
Trends in manufacturing suggest that manual assembly will change from routine assembly line work to small-batch, non-routine work involving teams and incorporating quality control. The changing role of manual assembly in manufacturing reinforces the long-standing need to understand the properties of work that are compatible with human capabilities and limitations. Although methods engineering and principles for economizing human motion provide helpful approaches to the characterization of physical work demands, they provide limited insight into the properties of manual assembly work affecting the information processing and learning so important in non-routine work. In this paper several alternative task description models are reviewed and applied to an assembly task to illustrate its cognitive properties. The authors focus on a symbolic, computational representation of assembly task knowledge to suggest that current trends towards small-batch manufacturing place demands on workers to extend their existing assembly knowledge well beyond its original purpose, with implications for training, continuous quality improvement and the effectiveness of cell manufacturing.
