A Predictive maintenance solution is designed to monitor the condition and performance of equipment over time to detect any potential issues. By utilising TITAN CMMS – a predictive maintenance system software, businesses can identify early warning signs of equipment malfunction and proactively schedule maintenance before it's too late. Even minor temperature, vibration, or sound fluctuations can be immediately identified and evaluated to prevent machine breakdowns.
Anticipating a problem before it happens can be difficult. However, accessing past and real-time data from different operational areas can help solve this issue. Typically, maintenance plans are scheduled based on the asset's current condition. On the other hand, predictive maintenance (PdM) tracks the asset's condition and cautions against potential equipment failures. PdM's ability to do this is based on several key elements.
We have installed real-time sensors for condition monitoring of the assets.
The IoT technology enables communication between machines, software solutions, and cloud technology for collecting and evaluating work order data.
It is essential to have predictive data models that can anticipate equipment breakdowns and failures. Before installing sensors, observing the conditional asset baseline and organising your data is a good idea. By collecting dependent data, you can detect abnormalities and take control of the situation. The sensor activates the predictive maintenance protocol when the equipment functions outside standard parameters. This leads to a CMMS system generating a work order for technicians to perform the necessary repairs.
Predictive maintenance has different scopes in almost every industry, depending on their specific requirements.
Manufacturing: The manufacturing industry relies heavily on predictive maintenance to keep its production lines running smoothly without interruptions. In the manufacturing industry, there are several applications for predictive maintenance.