Why Predictive Maintenance
Your maintenance model has a significant impact on your costs and customer experience. Existing maintenance models fail to deliver optimal experiences for a minimal cost. Whether you use Run-to-Failure, Preventive Maintenance or Interval Servicing, we go one by one to intuitively explain why Predictive Maintenance achieves the best Customer Experience for the lowest cost.
Using Run to Failure, the asset is operated until it fails. Consequently, Maintenance is difficult to plan and mostly improvised. This often causes additional frustration as spare parts and mechanics need to be organised last minute.
Using Preventive Maintenance, assets are replaced long before they break. Therefore, you never experience unexpected downtime. However, this shortens the lifetime significantly and increases the service frequency.
Using Interval Servicing, assets are regularly inspected. Parts are only replaced when deemed necessary. You benefit additional lifetime at the expense of servicing costs.
The Internet of Things, or Industry 4.0, provides a data infrastructure that enables many companies to remotely monitor each individual asset. The sensor data from your machinery reveals the Failure Probability.
We at Amplo use state of the art Machine Learning algorithms to estimate the Failure Probability and predict the Failure point. You never experience downtime, without having to replace your assets prematurely or have an extensive service network.