What is Predictive Maintenance?
Predictive Maintenance (PdM) is the use of on-line monitoring to estimate the condition of machines.
It is much more than applying condition monitoring in your maintenance strategy as you might be doing with Condition Based Maintenance (CBM) in conjunction with manual route based monitoring. Importantly, PdM sources data during normal operations, hence minimizing disruption to operations for sampling or measuring. Traditional condition monitoring comes with a human burden on data collection and analysis. PdM removes this dependence, hence removing barriers for the application of cost effective condition monitoring to a much wider range of asset criticality.
PdM extends a Condition Based Maintenance (CBM) strategy to:
Cover a greater number of machines (balance of plant)
Reduce preventative maintenance burden
Enable the planning of opportunistic corrective maintenance
Prevents unexpected failures
PdM and CBM are complementary disciplines. If you already have a CBM program then culturally your organization understands the benefits of monitoring machines to optimize your maintenance policy. PdM takes that to the next level.
PdM utilizes a much higher level of data driven approaches than traditional condition monitoring as the data is from on-line sources opposed to irregular manual readings. The ability to be data driven enables PdM to exploit techniques form the domains or artificial intelligence and machine learning.
Read more on how it works
What are the benefits?
Senseye PdM, the industry leading Predictive Maintenance solution, is cloud based and automates data analysis. Also the Senseye PdM user interface is set up for operations and maintenance teams, rather than requiring specialist analysts. This approach of automating the analysis and simplifying the reporting of the resulting actions streamlines a complex task, saving time and costs, and allows maintenance teams to multiply their efforts, reacting with increased speed and accuracy.
Another benefit of automated analysis is that Senseye PdM is scalable, so it can grow with the requirements. This means that, in addition to critical machines, the wider non-critical population can now be monitored. These subsidiary machines may not be as expensive to replace, but their downtime could still be costly.