Date of Award
Bernard Clark Musselman
This research investigates engineering disasters from a mathematical perspective using Complex Systems Analysis (CSA). Though engineering disasters have a technical cause by definition, there are usually organizational ones as well. Examples include management, communications, and cost-cutting issues. As coupling between these causes hinders an analysis of their individual effects, I use CSA to measure how the company's structure interacts with their combined effect. This both deals with system complexity and provides a way to broadly apply the results, using information loss as a stand-in for the likelihood of a disaster. Specifically in silico experiments on organization network models are used to correlate network properties to information loss. We find in this study that the correlation with information loss is direct for verticality and inverse for collaboration, agreeing with existing business literature. More novel results are gleaned from two other measures relating to redundancy and minimality of communication paths. For redundancy, there is a small value beyond which flow is hindered. For minimality, there is a certain value which must be reached for gains in flow to be seen. Both are unexpected results and demonstrate the utility of CSA in this application.
Palmer, Benjamin, "Disaster: A Network Analysis of When Engineering Goes Wrong" (2014). Senior Theses. 854.