Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Rahimi, Shahram
Committee Member
Falls, Terril
Committee Member
Swan, J. Edward II
Committee Member
Rahimi, Shahram
Date of Degree
5-1-2020
Document Type
Graduate Thesis - Open Access
Major
Computer Science
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Computer Science and Engineering
Abstract
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.
URI
https://hdl.handle.net/11668/16949
Recommended Citation
Kopuru, Mohan, "A machine learning framework for prediction of Diagnostic Trouble Codes in automobiles" (2020). Theses and Dissertations. 172.
https://scholarsjunction.msstate.edu/td/172