Large ships or vessels consists of heavy machinery prone to defects and failures. Failure of any machinery or component can incur heavy repair costs, labour costs and logistical costs. Untimely deliveries due to unplanned downtime also affect the revenues considerably.
To avoid unplanned equipment failure, the shipping industry has been employing a periodic or planned maintenance practice wherein inspection, component replacement and lubrication are performed at periodic intervals. This method prevents breakdown but is rather expensive. Preventive maintenance requires a large number of personnel along with availability of spare parts, which increase the holding costs. Also, routine maintenance also limits the availability of ships.
To prevent breakdowns as well as to limit the routine maintenance tasks, it is essential to monitor machines continuously, predict failures and perform maintenance only when necessary.
Vegam’s predictive maintenance platform along with smart IoT sensors enables continuous monitoring of shipping components. Machine failures and fault conditions can be predicted using predictive analytics, thus optimizing the whole maintenance in shipping industry.
Large ships or vessels sail for a really long time and their engines involve heavy machinery with highly complex and critical components that keep the ships in the sea. It is highly critical that the ship engine run at an optimal running condition and any issues that may occur be predicted before the outcomes are life threatening.
Predict ship engine failures before they occur with vMaint4.0 Vegam Predictive maintenance solution, which has offline prediction. With Vegam platform, the maintenance team gets Industrial grade IP68 certified IoT sensor packaged maintenance management solution
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