PRESS RELEASE: Powered by Cloudera Enterprise and Microsoft Azure, the IIoT platform enables Komatsu teams to help mining customers around the world continuously monitor the performance of some of the largest equipment used in surface and underground mining, and increase asset utilisation and productivity.
Komatsu’s JoySmart Solutions is an IIoT-based service that helps customers optimise machine performance using machine data and analytics. The JoySmart platform ingests, stores and processes a wide variety of data collected from mining equipment operating around the globe, often at very remote locations in harsh conditions. Types of equipment monitored include longwall mining systems, electric rope shovels, continuous miners and wheel loaders. Their data includes time-series metrics – machine pressures, temperatures, currents, etc. – alarm and event data, and other information from third-party systems. A single machine can have hundreds to multiple thousand data metrics and generate 30,000-50,000 unique time-stamped records per minute.
“With increasing customer demand and more connected machines, we were looking at data growth reaching 30 terabytes per month. Our former environment limited our ability to scale, grow and innovate,” said Anthony Reid, senior manager of analytics at Komatsu. “With Cloudera’s modern platform, we use advanced data analytics and machine learning to power our IIoT success. We now provide customers with better recommendations on machine utilisation and deliver services faster. In one example, we were able to make recommendations for a large coal mining company that enabled them to double the daily utilisation of their Joy longwall system.”
Reid continued: “By deploying Cloudera Enterprise on Microsoft Azure, our teams make the invisible visible, gaining valuable insights to help customers optimise productivity and mining efficiencies. Cloudera delivered the fast performance, data security and customer support that allowed our teams to access machine data analytics and collaborate with different user groups across the world.”
Komatsu data scientists can now build and deploy machine-learning models faster to understand equipment operation, provide better insights for customers and ultimately influence future mining equipment design. Utilising components such as Apache Kudu and Apache Spark, Komatsu can drive real-time processing, machine learning and analytics on all of their IoT data, including data in motion and data at rest.
