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Post at 24 Aug 2017

The reliability and efficiency of the train load out process at coal mines can be a ‘make or break’ when it comes to meeting production timelines and profitability.

Anglo American is the world’s third largest exporter of metallurgical coal. The company uses the latest technology to run their operations in the best possible way and strive for continuous improvement at existing assets.

Train loading stations are often considered a bottleneck, as these facilities are typically operated manually resulting in variable performance, wagon over or under loading and poor reliability.

As a result, companies are often faced with heavy fines and in some cases substantial costs to obtain additional trains to meet required throughput.

MRA Electrical & Automation Engineering (MRA) was initially involved in the first automation of a train load out (TLO) in Australia more than fifteen years ago. As such, the company has a detailed understanding of the systems required.

At that time there were some limitations in the technology that resulted in some shortcomings of the early systems.

These limitations culminated in issues with accuracy and environmental conditions. To address this, MRA conducted extensive research and development, using the latest technologies to overcome these shortfalls and develop an efficient and reliable automated TLO solution.

When Anglo American tasked MRA with automating their TLO process at the German Creek coal mines, the result exceeded expectations and provided an intelligent and intuitive system that not only improved efficiency and reliability but also delivered a state of the art solution with an unrivalled return on investment.

Challenge
  • To automate the train load out process at German Creek for improved reliability and profitability
Results
  • The automated TLO provides efficient and reliable loading
  • Detailed simulation prior to commissioning reduces downtime
  • Remote commissioning by accessing the controller online provides increased efficiency and flexibility
  • ROI of less then four months for the system
  • Solution provides significant ROI per month