Today, condition monitoring plays a vital role in asset management and diagnostics for valuable equipment. New sensing capabilities allow for a better understanding of an organisations assets and therefore make pre-emptive and optimal maintenance decisions. By adding intelligence to existing equipment, you gain real-time access to your asset data to improve efficiency, productivity, reduce costs and prevent unplanned interruption.
Condition monitoring increases value by providing engineers with a foresight into the health and condition of engineering machines, it helps develop strong preventative maintenance strategies, and allows manufacturers to make data-driven choices to improve product quality.
Implementing condition monitoring into legacy analogue systems improves your business processes, helps your business become more cost-effective and competitive and builds a solid technological infrastructure for your future manufacturing initiatives.
Optimal’s condition-based maintenance solutions can provide your maintenance team with analytical data about the health and performance of your critical assets and provide your organisation with a much-needed edge in the competitive world we live in.
More information is available about the health and performance of your equipment than ever before, with sensors being able to communicate increased amounts of data in real time. Predictive Analysis allows you to quickly transform raw data into actionable insights to prevent equipment failure and make smarter decisions that improve operation. This enables organisations achieve the desired value from critical assets by supporting Predictive Maintenance Programs with early issue warning detection before existing operational alarms kick in.
We can utilise tools that integrate with existing data historian systems and can be combined with condition monitoring solutions to create the ideal analytics tool set for a comprehensive Asset Performance Management Programme.These tools learn an equipment’s unique operating profile, and historical asset sensor data can also be used for advanced modelling in comparison with real-time operating data to determine minor deviations from expected behaviour. If an issue is identified, root cause analysis and other diagnostics can help understand the reason and significance of the issue.
