Alert calibration maintenance (AlertCaLM) application for condition based maintenance

Maintenance of equipment to prevent failures has become increasingly important. Maintenance technology has evolved over time based on condition-based. Faults and failures of induction machines can lead to excessive downtimes and generate large losses in terms of maintenance and lost revenues, and this motivates the examination of on-line condition monitoring. The idea of condition-based maintenance (CBM) is to monitor equipment using several sensors to allow real-time diagnosis of impending failures and prediction of equipment condition. Condition based Maintenance (CBM) is a maintenance process used by industry to actively manage the health condition of equipment or machine in order to perform maintenance only when it is needed and at the time. This paper presents a neuro-fuzzy modeling approach for condition based maintenance as to achieve the result in investigating the CBM function in reducing the inventory cost, reduce the number of failures by analyses the data collection of the machine vibration based on condition based maintenance and develop android system to implement in maintenance process. The process of developing this project is to understand the concept of condition based maintenance use in controlling the lifetime of the machine