SPGo! insights¶
Michael Mella Navarro, Nixon David Monge Calle, Hernán Lionel Cianfagna
January 31, 2023
5 min read, 55 min watch
SPGo! builds systems for the mining industry for monitoring material conveyor belt idlers.
About
The objective of SPGo! is to improve the profitability of their clients’ businesses in the mining industry by applying IIoT technology with a predictive maintenance model to equipment inspection through the management of big data.
CrateDB is a trustful partner that supports us on this journey.
– Patricio Quezada, General Manager and Founder of PETROMIN
See also
SPGo!, by PETROMIN, has developed a system that allows monitoring mining material conveyor belts with more than 40,000 sensors in real-time, processing 760 million records per day, or 120 billion records each year.
By using a predictive algorithm, SPGo! alerts their clients when to conduct maintenance work on specific equipment (that is set to fail). This helps the mining customer save resources, costs, and losses due to downtime.
SPGo!: Monitoring and predictive maintenance
SPGo! switched from MongoDB to CrateDB for performance and interoperability reasons.
The speakers will share many details of this solution, including real-time component monitoring, predictive failure analysis, management of operations, data-driven predictive maintenance, large daily data intakes, and KPIs that help the mining businesses save resources, workforce, and losses, due to decreased downtime.
You will learn
How the mining industry business struggles to predict potential issues with critical equipment.
How SPGo! planned to improve the profitability of their client’s business by applying IIoT technology with a predictive maintenance model.
How SPGo! verified a 30%-increase in data-driven predictive maintenance with CrateDB.
How SPGo! manages large data intakes daily.
- Industry:
Engineering Mining Production
- Tags:
Sensor Data Acquisition Machine Monitoring Predictive Maintenance
- Technologies:
BLE Wireless MQTT