Big Data Application on Komatsu Loading Equipment

摘要

Recent advances in capabilities to transmit, process and store large quantities of data have led to a growing desire to harness this technology for the purpose of remotely monitoring the health of industrial machinery. However, handling the large volume of data produced by these machines presents many challenges. Mines with poor network coverage present a challenge for large-scale data transmission, which must be overcome. Another challenge is the development of novel strategies for efficiently processing and analyzing very large data sets post-ingest. Finally, it requires a modern data warehouse solution for meeting the competing use cases of large-scale storage and quick retrieval of highly dense data, with up to 500,000 data points ingested per second fleet-wide. Komatsu has developed applications that process and store derived metrics from the original raw control system data stream. For example, operational metrics are calculated for each loading cycle, including cycle decomposition times, Swing angles, aggregate torque and energy calculations for each motor, dipper position in 3D coordinates, average speeds.This data analytics platform enables Komatsu to tailor analysis and reports in a customized fashion, to meet the unique needs of specific customers. Additionally, the system is leveraged to improve loading operational processes and substantially decrease the cost per ton for each customer site. This is made possible by the combination of modern Big Data technology solutions and the deep experience of Komatsu's Data Analytics team.