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Title: Advanced Predictive Analytics
Organization: Vale - The University of Queensland
Duration: 2015 to 2017
Business Challenges
In the current economic climate, minimizing costs is critical. Equipment reliability must be stepped up to increase production and reduce delays. Equipment reliability requires effective maintenance. Maintenance expenses in the mining, oil, and gas industries are commonly between 30% -50% of total operating costs. Shutting down the process and potential injuries are two critical challenges in sites that advanced predictive analytics can potentially solve. The competitive market has forced companies to find a practical solution to decrease the total product cost; moreover, improving safety has always been one of the important concerns for companies, and advanced analytics can be a good solution for that.
Suggested Solution
The overall goal is the application of Advanced Analytics to reduce unscheduled maintenance delays, prevent equipment machine damage, avoid catastrophic failures, and provide a platform for ongoing predictive maintenance. In a deep dive, outcomes and benefits can be categorized into two mine haul truck disastrous brake failure examples; distinguish between "Real" versus "Spurious" alarms, and evaluate which proactive diagnostics are the best predictors of haul truck equipment damage, unscheduled maintenance.
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