Optimizing and Shaping the Future of Mine-Site Assaying Laboratories Our expertise

Cross-belt analyzers allow direct and safe detection of ore variations as well as fast counteractions to changing ore composition. Early and accurate ore blending and sorting save millions during downstream processing. It ensures a homogenous output towards the beneficiation plant and avoids the processing of low-grade ore or waste.

This solution can be employed for continuous, non-contact monitoring of elemental and mineralogical composition as well as the prediction of process-relevant parameters. Benefits include:

• Perform resources assessment
• Monitor key components for the mining operation
• Sort ore by element(s) of interest
• Optimize crushing operation
• Optimize magnetic separation
• Optimize leach pile composition quarry life
• Minimize flotation reagent consumption

Real-time process control of elemental composition involves grading of ore early in the process. This allows low-quality feed to be excluded from downstream beneficiation processes, improving efficiency, and driving down costs, regardless of the type of ore or the ultimate commodity.

Using the latest advances in neutron activation via neutron tube, rather than an unstable radioactive source, Pulsed Fast Thermal Neutron Activation (PFTNA) technology rapidly delivers highly representative elemental analyses for safe, robust in-line process control and elemental analysis directly on the conveyor belt.

Real-time monitoring of mineral content on the conveyor allows significant cost savings to be made. These include:

• Reducing the amount of acid used in beneficiation processes
• Improving heap-leaching percolation rates by accurately determining total clay content
• Providing information on gangue minerals, which is valuable when optimizing flotation processes

A plant manager can acquire a more comprehensive understanding of ore quality using On-line Near-infrared (NIR) equipment that allows full analysis of mineral composition. This is used in conjunction with an elemental composition analyzer such as a PFTNA.

Managers and analysts in the field need to have a top-to-bottom picture of every material throughout its lifecycle, from raw materials to released cargo. They need data telling them what tests were done, how often, and at what point in the process.

They need to merge, segregate, and visualize that data to understand how one mining operation is performing compared to another and ensure compliance with increasingly stringent regulations. They need to do all of that efficiently, with no shutdowns, and without repeating costly tests unnecessarily.

However, much of this information is compartmentalized causing valuable data to be locked and difficult to access. Even when access happens, it is tedious and challenging for the analyst to analyze all the data available especially when there are hundreds of data points to be collected each day.

This is where a Laboratory Information Management System (LIMS) comes into play. Labs will have an array of instruments and software systems that are capable of integration with LIMS, be it direct analysis in the field, online sensors to predict ore grades, laboratory equipment, or complete automation solutions.

With a LIMS solution that interconnects processes within a single, central hub, this ensures that documentation generated during early explorations is consistent throughout mining and final quality assurance testing. The result is a more efficient lab with fewer opportunities for risk, increased productivity, reduction in deviations, faster closure times, a decrease of QC-lab lead times, reduction of investigation workloads, and lower operational costs.

According to estimates, 75 percent of the total operational costs of a traditional laboratory come from manpower. Hence, removing the need for manual human interaction carries the potential to significantly reduce overhead costs.  

Artificial Intelligence, data science, and automation technologies in mining are evolving rapidly. Blockchain technology is also making its way into this industry. These technologies create innovative solutions to solve operational challenges.

Data acquired and collected in a laboratory informatics solution, often unstructured and siloed from other enterprise systems, was not always accessible, at least not without a skillful data modeling exercise. That is changing as artificial intelligence and machine learning move into the lab.

Using data science algorithms, these advanced tools rapidly process all of that structured and unstructured LIMS data, integrating it with external enterprise data and serving lab managers and analysts with valuable insights and timely, meaningful recommendations.

Historic LIMS data is no longer locked away; it is put to work for the benefit of the whole enterprise, helping to drive deeper statistical analysis, advanced insights, and dynamic business intelligence. Lab managers gain a much-needed 360-degree view. They can see into the past to mine insights from historic data and use those insights to look into the future, identify potential risks, and lock in on new opportunities. This visibility not only improves speed to market, but it also drives down costs and supports smart decision-making, both inside the lab and across the company.