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A Machine Learning Framework for Prediction of Diagnostic Trouble Codes in Automobiles
by Kopuru, Mohan Sri Krishna, M.S., Mississippi State University, 2020, 97; 27837965
Abstract (Summary)
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
| Advisor: | Rahimi, Shahram |
| Commitee: | Falls, Terril C, Swan, Edward J |
| School: | Mississippi State University |
| Department: | Computer Science and Engineering |
| School Location: | United States -- Mississippi |
| Source: | MAI 81/11(E), Masters Abstracts International |
| Source Type: | DISSERTATION |
| Subjects: | Computer science |
| Keywords: | Trouble codes in automobiles |
| Publication Number: | 27837965 |
| ISBN: | 9798643196952 |
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