Leveraging Big Data to predict and prevent downtime using predictive analytics.
What is Predictive Maintenance
Avoid costly down times and reduce the cost of maintaining your equipment. Predictive maintenance accesses multiple data sources in real time to predict the failure of your equipment and detects issues relating to quality. Using predictive analytics, this solution detects the most minor irregularities and failure patterns to determine the equipment and operational processes that are at the greatest risk of problems or failure. This early identification of potential concerns helps you deploy limited resources more cost effectively, maximize equipment uptime and enhance quality and supply chain processes, ultimately improving customer satisfaction.
How it works?
Predictive Maintenance assesses the condition of equipment by performing sporadic or constant/online equipment condition monitoring. The main aim of Predictive Maintenance is to perform maintenance at a time where the maintenance activity is going to be most cost effective and before the loss of performance effects the organisations bottom line.
The goal of predictive maintenance is to detect operational anomalies/degradation and forecast them to point of failure.
Most inspections are performed while equipment is in use, this minimises disruption to normal system operations. Adopting Predictive Maintenance within an organisation can result in significant cost savings and a more reliable operational system going forward.
Benefits of Predictive Maintenance
A predictive maintenance solution can help your organisation:
- Predict when, where and why equipment failures are likely to occur.
- Quickly identify the primary variables as part of root-cause analysis.
- Reduce operations costs by enhancing sales and operations planning
- Foresee any upcoming issues and inform planning and budgeting teams before costly event failures occur.