Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing

24Artificial Intelligence Techniques in Predictive Maintenance, Their Applications, Challenges, and Prospects

Akriti Rai, Jyotika shastri and Hina Bansal^*

Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India

Abstract

Predictive maintenance refers to a preventative care technique which finds flaws or issues before they lead to equipment failures. Using data gathered from sensors on equipment, predictive maintenance builds models that anticipate when the component of equipment is likely to break. Preventive measures can be implemented to avert an issue after a failure is anticipated. By preventing unanticipated failures and the expenses that come with them, predictive maintenance can assist businesses in becoming more cost-effective. There are several predictive maintenance techniques that can be used, depending on the available type of data. Some common techniques include time-series analysis, probability forecasting and artificial intelligence that is linked to the internet of things (IoT). Time-series analysis looks at how past values of a variable change over time. It can be used to predict future values of the variable. Probability forecasting uses historical data to calculate the probability that a particular event will occur. This can be used to predict when a particular component is likely to fail. Artificial intelligence can also be used to create models that learn how equipment behaves ...