Quality Checking System in Automobile Engines using Data Mining Algorithms
Keywords:Efficiency, Quality, Random Forest, Decision Tree, Four stroke engine
The Automobile industry is a billion-dollar industry. New vehicles are continuously designed while the existing ones are constantly being made better. But at its core, the entire industry runs, essentially, on engines. Engines are some of the most used pieces of technology in the world. They move the earth and the economy, thus driving towards a better tomorrow. In order to tap the maximum potential of an engine, the importance of the parameters that contribute to the working, running and maintaining the life and the efficiency of the said engine is paramount. Maintaining this efficiency of work is done by the mechanic who repairs and restores the shape of the car back to its prime condition. But, due to the nature of humans, the task of assessing the problem usually takes away precious time which can be used to enrich productivity. Thus comes the true purpose of this system. Keeping in mind the “Quality-Checking” approach where accuracy is critical, this system will compare the current conditions of the engine with the factors of the same parameters using an innovative method of assessing the quality of engine. Thus using a data mining algorithm, the factors contributing to inefficiencies of an engine and the problems lying within can be easily brought to light. This research paper, however proposes only a model for the above mentioned system. This paper highlights the usage of three data mining algorithms and compares the predictions generated by them.
How to Cite
Copyright (c) 2021 S. Devanand
This work is licensed under a Creative Commons Attribution 4.0 International License.