Assembly Time Modeling through Connective Complexity Metrics

Abstract

This paper presents the development of a model for predicting the assembly time of a system based on complexity metrics of the system architecture. A convention for modeling architecture is presented, followed by ten analyzed systems. These systems are subjected to complexity metrics developed for other applications. A model is developed based on a recognizable trend and a regression of that trend. The regression is then further refined based on its similarities to additional metrics other than that used in regression. The final model uses average path length, part count, and path length density to predict assembly time to within ±16% of that predicted by the Boothroyd and Dew Hurst design for assembly analysis method.