Development of an automated ontology generator for analyzing customer concerns

General Motors Company (GM) service representatives and service technicians generate large volumes of information related to customer concerns. These records are then stored for further analysis by GM Quality engineers. The challenge faced by quality engineers is efficiently processing this data to provide actionable insights to the Product Development staff in a timely manner. The overarching goal of this project is to save the quality engineers time and effort by automating the process of identifying and categorizing trends in product issues and customer concerns. Toward reaching this goal, this James Madison University capstone design team has developed the tool, OnGen, to assist quality engineers with analyzing this data to provide meaningful information with minimal time and labor. OnGen is built using Microsoft Excel and contains embedded macro features in order to run with minimal input from GM Quality engineers. Validation of this system was completed through testing with four functionally dissimilar systems. When comparing the GM-current process to the team's automated process, the required preprocessing time has been reduced from days to minutes. GM Quality engineers will evaluate a prototype of the system prior to implementation.