Operational safety, efficiency and productivity is essential. As one of the largest port operators in the world, with an ever increasing maritime traffic presence, it is imperative for this customer to prevent any unplanned downtime causing a decrease in crane utilisation.
Excessive maintenance was performed to increase reliability resulting in higher maintenance costs and a large spare parts inventory.
The ageing equipment resulted in reduced reliability with insufficient information available to management to facilitate repair/replace decisions.
The historical data from each crane was loaded into the VROC software. VROC automatically built models to predict each of the different faults experienced by the machine. These historical models allowed engineers to identify the root causes of each of the faults as well as their predictability.
Live data was then streamed into VROC allowing it to provide real-time analytics of exactly when equipment was going to break down, and the most significant contributing factors that will cause the failure.
Moving forward The VROC predictions are going to be linked directly into the customer’s CMMS (Computerized Maintenance Management System) so that work orders can be generated to repair the item prior to the impending failure. The VROC system will also be connected to the customer’s SAP system to automatically order required parts, as well as being connected to the operations management system to enable operations personnel to schedule a shutdown at a convenient time prior to the failure.
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The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
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'OPUS, an artistic work, especially on a large scale'
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