Situation

In the current industrial landscape, mining companies have always looked for ways to optimize their operations and improve cost efficiency – these are key factors for mining operations to stay competitive.

Challenge

The mining industry faces a number of challenges, such as extracting minerals from increasingly remote and difficult-to-access locations, ensuring worker safety, and maximizing production efficiency. Traditional methods often are not enough in addressing these challenges, leading to higher costs and increased risks.

Solution

  • One technology that has emerged as a game-changer is image analytics. By utilizing the power of computer vision and machine learning (ML), image analytics is addressing a number of mining operations challenges.
  • It starts with the collection of relevant data by capturing high-resolution images or videos of your industrial processes, equipment and workflow
  • Then, preprocess collected data by taking different steps to enhance the image quality and by labelling the images
  • Use image analytic algorithms to detect signs of wear and tear, identify potential faults, and predict maintenance needs
  • Install sensors and cameras to capture and to monitor real-time data to ensure proper calibration and synchronization between cameras and the analytics software
  • Finally, analyze and interpret data by looking for abnormalities, bottlenecks, inefficiencies within the mining operations

How a mining company analyzed and interpreted visual images using computer vision and machine learning (ML) model to predict operational issues, enhance safety and reduce environmental impact

Results

By utilizing the power of computer vision and machine learning (ML), image analytics analyze and interpret data by looking for abnormalities, bottlenecks, inefficiencies within the mining operations.

Image analytics doesn’t have one but multiple business cases:

  • Through predictive maintenance, it helps prevent costly breakdowns, reduces downtime, and optimizes maintenance schedules

  • Through operational efficiency, it helps to monitor mining processes real-time in order to reduce waste and maximize throughput

  • Through safety enhancement, it can discover potential safety hazards like, for instance, unstable rock formations

  • Through environmental impact reduction, it can discover changes in water quality and land erosion.

For more information on this case, please contact us.

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ML model also makes a recommendation on how to operate the equipment to increases up-time, lifetime and minimizes unplanned downtime.

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