We first encountered PMS way back in 1999 which was DOS based. It did make life easier for all the ship staff as we were able to now concentrate on the jobs that need to be done rather than relying entirely on our memory, breakdown, experience and just instinct.
Technology has evolved many fold and the systems now are very different and very versatile. There is gigs and gigs of data lying in the company PMS systems, but is it being used smartly?
Almost all the maintenance on board is bound the concept of fixed intervals. These interval definitions are controlled by various sources:
Even with so much of control we have not been able to eliminate the downtime and unexpected breakdowns.
Though many of these intervals cannot be changed due to compliance and certification requirements, there is still scope of looking at the remaining ones smartly, utilising the data that already exists in the PMS systems.
We know that there is a high operational risk due to unexpected breakdowns, downtime and offhire. Data driven insight can be used to minimise this further.
This can be achieved by the smart use of this data in PMS, using modern tools like Machine Learning, Prediction Models, Random Forests.
Some of questions hounding the business and operations are detection of anomalies in equipment and system performance. Setting and predicting of the warning life of any component, very similar to distance to empty in our cars. Finally if failures do occur, then we can use the data for cause identification, thus improving the predictions as we go ahead.
At PiscesER1 we compare the gains very similar to many high value industries like Finance and Production.
There will be just in time maintenance thus reducing the overall maintenance cost. Even purchase can be made just in time and inventory maintained based on predicted maintenance.
The customer satisfaction and retention will be enhanced by providing them with KPIs and health scores of the vessel systems.
Discover patterns with maintenance related issues and develop solutions for the same.
We would like to call is CPPMS – controlled, predicted, planned maintenance system.