ABSTRACT

Predictive maintenance is a proactive approach to maintaining industrial equipment by predicting when maintenance should be performed. It uses data analysis tools and techniques to detect anomalies and predict equipment failures before they occur. The problem statement focus on the high installation costs, incomplete data can hinder accurate analysis and prediction, integrating data from diverse sources and formats can be time-consuming, noise in the data which can lead to inaccurate predictions, maintaining predictive models requires specialized skills in data science, lack of maintenance and checking, unpredictable maintenance periods. The research focuses on the review of the predictive maintenance information system. The objective of this research was achieved by developing a platform for predictive maintenance information system, build a database structure used to store data, create a module used to login and register employee, design a platform that add equipment for maintenance, design a platform that predict maintenance, design a platform that shows maintenance prediction. The research was realized through the adoption of primary and secondary sources of data collection which includes interview, observation, questionnaire, the internet and journals. The research methodology used is spiral model. The system is implemented by using Html, PHP and java script and MYSQL for the database. The results