| This research identifies the causes of engineering change propagation during the development and production phases of the product lifecycle using a statistical method applied to large engineering change data sets from the locomotive and mining vehicle industries. Little research has been undertaken to understand propagation, using large data sets or looking at propagation across several industry projects. Specific hypotheses were developed to examine the significant difference and/or the relationships between engineering change propagation and four possible influencing variables, including the engineering subsystem issuing the change, the subsystem interface complexity, the product designer experience, and the frequency of change. Quantifiable methods for variable measurements were developed to allow for hypothesis testing. This research identified three key influencing variables that were found to be related to engineering change propagation, namely: the engineering subsystem issuing the change, the subsystem interface complexity, the designer experience, and the frequency of change. This research contributes to the Systems Engineering body of knowledge by predicting key influencing variables, which can reduce change propagation and provides important insights to practicing systems engineers and engineering managers. In particular, the results of this study can be used to improve engineering change decision-making processes and the utilization of resources. Similar complex systems composed of multiple subsystems can also benefit from the findings of this research. |
