Machine Learning for Predictive Maintenance - Hitachi Construction Machines
Project scope
Categories
Data analysisSkills
data analyticsThis particular challenge focuses on helping analyze large amounts of mining equipment event data from major customers in order to determine predictive causes of machine failure.
While the project can eventually expand to multiple equipment types and brands, the scope will be around the Hitachi brand EX 5600 mining excavator and potentially other extremely large mining excavator equipment from sites in Japan and Africa, with a potential to include customers from Australia and other locations.
As part of the Machine Learning project, students are expected to:
- Learn about Asset Health priorities for Mining Industry - through discussions with Wenco and possibly self study
- Work with Wenco analyst to analyze data provided by Wenco, to determine if there are predictive indicators of machine failure
- Prepare a report and presentation delivered to executives of the company
About the company
Wenco International Mining Systems Limited (Wenco), is a major provider of data technology to the global mining industry. Since its inception in 1987, the company has acquired over 30 years of experience in developing fleet management systems and mining software technology. Wenco was acquired by Hitachi Construction Machinery in 2009. Headquartered in the Vancouver area suburb of Richmond, British Columbia, Wenco operates offices on five continents and over 150 installations worldwide, helping mining customers raise productivity, decrease operating costs, extend the running life of mining equipment, improve mine safety, and increase the efficacy of decision making. Wenco has entered a period of rapid growth, but with that growth comes a number of major strategic challenges surround all aspects of its business. The company would like your support in addressing those challenges.