For many manufacturers, the consumption of fuel, oil and lubricant for onsite vehicles is a major expense. Other significant costs include electricity consumption and CO2 production. In the mining industry, for example, a fleet of trucks travelling between the excavation site and the processing area can use hundreds of millions of liters in fuel. It's therefore no wonder that controlling and optimizing these consumption rates has become a concern for many companies.The challenges of managing these consumption rates can be summed up in 3 questions:
How can we visualize and explore consumption in order to analyze it?
e.g.: measuring the consumption of each vehicle on a site.
How can we detect anomalies?
e.g.: identifying an increase in consumption on a specific part of the journey.
How can we optimize consumption?
e.g.: changing the journey of vehicles depending on their load or weather conditions.
Managing consumption depends on identifying and handling a wide range of different data
Data produced by industrial systems.
e.g.: the number of tons of material handled
Data from IoT sensors.
e.g.: the weight of vehicle loads, the number of liters of fuel put into a vehicle, stock levels of lubricant, etc.
Data from the vehicles themselves
beginning with GPS tracking of journeys
By combining these data streams, we can create indicators to follow the consumption per ton transported, by vehicle category, by journey type, etc. This information can then be geolocalized to optimize processing and analysis.
The ForePaaS solution
Capable of integrating diverse sources of data
whether they come from files, API or IoT sensors
Platform as a Service is backed up by cloud resources
to handle any load without technical complexity
Possibility of integrating existing algorithms
to capitalize on previous work
Capable of handling high volumes of data in real time
thanks to cutting-edge technology
Alerts are issued when pre-defined limits are passed,
keeping you informed in real time of potential malfunctions
Information is displayed differently depending on each person’s role
for improved operational efficiency
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