Columbia Shipmanagement (CSM) has implemented a new digital twin process for one of the jack-up barges under its management, to assess the technology’s potential in supporting performance optimisation.
The project was undertaken by the team at Columbia’s Performance Optimisation Control Room (POCR), headed up by Captain Pankaj Sharma, and employs a wireless IoT infrastructure with machine learning capabilities to provide equipment health monitoring and engine diagnostics.
“The vessel is fully digitised and digitalised in a totally cyber secure environment. Smart cameras onboard the ship take analogue images of the systems which are then digitised,” said Capt Sharma.
“By combining and analysing data from the sensors, the crew and the onshore technical department have direct access to all information about the health of specific items of equipment. The smart vessel solution capitalises on the machine learning, self-correcting and early warning systems for asset preservation and the solutions are scalable, modular and OEM agnostic.”
The system on the vessel is able to look for any anomalies while monitoring the vessel’s diagnostics and predictive warning systems, with its software able to identify data trends and anomalies, providing early indicators to avoid potential failures or downtime and to help with decision making for crew and shoreside personnel.
“While vibration and temperature monitoring have been used successfully on ships for many years to reduce breakdowns and improve equipment functionality and reliability, our vessel links sensor data to an onboard server from which the crew can immediately spot any abnormalities or problems,” adds Capt Sharma.
“The generator condition monitoring technology installed onboard, for instance, constantly takes measurements and can recognise abnormalities in the generators as well as the engines and gearboxes.”
