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3 ways predictive analytics optimises asset management

Data Analytics - Digital Transformation

Originally published by the AusIMM Bulletin

Predictive analytics has both immediate and long-term benefits for organisations when it comes to reliability and cost savings. When combined with monitoring and asset management systems, PdM can give mining companies better visibility over their assets, greatly reducing previously uncontrollable challenges such as distance and environment. The three most attractive benefits of a predictive maintenance strategy are discussed below.

  1. Improved customer satisfaction

With reliability comes increased customer satisfaction. Customers demand reliable supplies without the associated costs. By reducing operational costs while increasing performance, companies not only stay compliant with regulatory authorities but also keep customers happy by ensuring reliable supplies.

  1. Reduced total cost of ownership

By prioritising maintenance activities and using cost–benefit analysis and historical data to help employees make intelligent decisions, unexpected costs are reduced or, in best cases, eliminated. Organisations save significant amounts of money by avoiding equipment failure, a completely opposite approach to reactive maintenance. Not only do companies eliminate the cost of replacing assets, but they also eliminate the costs and penalties associated with equipment downtime, employee utilisation, environmental impact and more. Using predictive monitoring also ensures real-time visibility into the health of your assets, allowing miners to get the most out of their asset investment.

  1. Increased safety and compliance

Predictive analytics provides visibility into assets that were previously hard to manage due to distance, size, age and so on. By analysing data from multiple sources and comparing historic values with real-time input, organisations gain a clear view as to how their assets are running. This allows for proactive management of risk thanks to the ability to easily prioritise potential problems, automate responses and prevent failures.

 

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