Swan, J. Edward II
Date of Degree
Graduate Thesis - Open Access
Master of Science
James Worth Bagley College of Engineering
Department of Computer Science and Engineering
Predictive Maintenance is an important solution to the rising maintenance costs in the industries. With the advent of intelligent computer and availability of data, predictive maintenance is seen as a solution to predict and prevent the occurrence of the faults in the different types of machines. This thesis provides a detailed methodology to predict the occurrence of critical Diagnostic Trouble codes that are observed in a vehicle in order to take necessary maintenance actions before occurrence of the fault in automobiles using Convolutional Neural Network architecture.
Kopuru, Mohan, "A machine learning framework for prediction of Diagnostic Trouble Codes in automobiles" (2020). Theses and Dissertations MSU. 172.