The CLH Group implements predictive maintenance for the management of its logistics network
- The project is part of the company’s digital transformation plan, which includes different projects to optimise and improve operational processes.
The CLH Group has implemented predictive maintenance in the day-to-day management of its logistics network to ensure faster, safer and more efficient operations, and to prevent any malfunction of the system.
To achieve this, the company has rolled out intelligent systems to capture information through sensors that enable the monitoring of equipment and the compilation of operational data which is then analysed and transformed into information on the condition of the equipment. The results are displayed in constantly updated online dashboards that allow the information and analyses performed to be shared throughout the entire organisation.
Accordingly, based on artificial intelligence and using machine learning techniques, models have been developed to monitor the operation of the assets, taking into account the different operating situations. This enables the prevention of possible malfunctions and the optimal scheduling of corrective actions to avoid unplanned downtime and damage to the assets and their surroundings.
The system continuously analyses the more than 700 control values used to load road tankers at CLH facilities, and close to a hundred large pumps that move the different products through the pipelines.
During the test period, it could be seen that the models developed for control valves had a very high accuracy rate and were capable of identifying malfunctions that result in a loss of efficiency, while making the operation safer.
These were developed using agile methodology intended to deliver fast developments and consistent value. The initiative also served to validate the technology before rolling it out to other infrastructure where it can be applied to optimise the entire life cycle of the equipment.