Optimized Predictive Models in Health Care Using Machine Learning

17Machine Learning Approach to Predicting Reliability in Healthcare Using Knowledge Engineering

Kialakun N. Galgal¹, Kamalakanta Muduli¹ and Ashish Kumar Luhach²*

¹Mechanical Engineering Department, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea

²Department of Electrical and Communication Engineering, Papua New Guinea University of Technology, Lae, Morobe Province, Papua New Guinea

Abstract

Reliability, in machine learning, refers to using data analytics to forecast an asset’s deterioration or failure rate so that it can be repaired or replaced before it completely breaks down. Manufacturing facilities, automobile facilities, or any facility that owns assets with rotating or moving parts where wear and tear of components are frequent and costs a fortune to maintain or replace can use Machine Learning approaches to predict Reliability. These approaches can be used in manufacturing facilities as well as automobile facilities. Machine learning algorithms have recently been utilized worldwide to anticipate maintenance. This is because this method has a superior accuracy rate compared to the traditional predictive maintenance strategy, which engineers have demonstrated to be true. At this point in PNG, most maintenance activities consist of corrective or preventative maintenance, which is an expensive endeavor for the company. As a result, the information used in this article comes from online research that other authors conducted on a similar ...