Mining Study
Overview of BrainiAll Actual Mining Study Test Results
The BrainiAll AI industrial test was conducted in collaboration with a leading Canadian mid-tier gold producer to evaluate the performance of BrainiAll's advanced artificial intelligence system in optimizing grinding operations. The test, which spanned 25 days from January 10 to February 5, 2024, alternated every 48 hours between AI-driven and manual operation modes. This on-off testing approach accounted for variances such as rock type, feed blend, and operational rate, ensuring accurate comparisons.
“ Results revealed that the BrainiAll AI system consistently outperformed manual operations, achieving productivity gains of 3% to 10%."
Notably, the BrainiAll AI system demonstrated its effectiveness in handling both hard and soft materials, with significant benefits in scenarios requiring continuous optimization. The findings highlight BrainiAll AI will enhance operational efficiency, improve productivity, and unlock financial gains in mining operations.
For a detailed breakdown of the study and its results,
Mining Productivity Study
Actual Test & Results
1. Introduction
The application of BrainiAll artificial intelligence (“AI”) in the mining industry has become increasingly relevant, enabling significant improvements in operational efficiency, cost reduction, and enhanced performance outcomes. This technology has been applied across various stages of mining operations, including planning, prospecting, processing, and monitoring.
As part of an initiative to explore this innovative intelligent control system, a leading Canadian mid-tier gold producer conducted a test to develop BrainiAll's AI application in milling, aiming to increase productivity rates.
2. Objective
The primary objective of this study was to evaluate the performance of BrainiAll AI in grinding operations. A comparative analysis was conducted between the existing manual operation and the AI system, focusing on particle size distribution and energy consumption.
3. Methodology
Over a two-year collaboration between BrainiAll and the gold producer’s process engineering team, an intelligent system for grinding control was developed. Following its implementation, comparative tests were conducted between the BrainiAll AI-driven system and manual operations.
The official testing period spanned January 10, 2024, to February 5, 2024, with operational modes alternated every 48 hours to account for variances such as rock type, feed blend, % solids, and operational rates. A total of 25 days of data was collected.
As illustrated in Figure 1, the days in blue represent the manual operation, the days in orange indicate the AI's performance, and the days in red correspond to grinding stops due to maintenance, which were excluded from the analysis.
Figure 1: Industrial Test Calendar
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Blue days: Manual operation. (12 days)
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Orange days: BrainiAll AI operation. (13 days)
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Red days: Maintenance periods (excluded from the analysis). (3 days)
To ensure consistency, only periods with at least 85% active operational hours were analyzed, resulting in a comparable dataset for both BrainiAll AI and manual systems.is an easy-to-read font, with tall and narrow letters, that works well on almost every site.
4. Results and Discussion
The overall comparison between the artificial intelligence (AI) system and manual operation demonstrates a clear advantage for the BrainiAll AI system in terms of productivity and efficiency. Over the course of 265 operational hours for each method, the Brainiall AI system processed 115,347 tons of material compared to 109,079 tons for the manual operation, achieving a 6% higher productivity rate (435 t/h vs. 412 t/h). This improvement was achieved with only a marginal increase in energy consumption, showcasing the BrainiAll AI system's ability to optimize operations. Additionally, particle size distribution (p80) values remained consistent between the two methods, indicating that the BrainiAll AI system maintained the quality of output while enhancing overall performance. These results highlight how BrainiAll AI will significantly improve operational efficiency in milling processes.
Table 1 Summarizes the results for all operational conditions:
The BrainiAll AI system demonstrated a 6% increase in productivity compared to manual operations, despite elevated feed rates influenced by transitional ore blends.
Fresh Rock Analysis
To isolate the impact on harder material, tests were conducted using feed with a Bond Work Index (Wi) ≥ 14kWh/t. Results are summarized in Table 2:
The AI system delivered a 3% productivity increase for harder materials, achieving rates above the plant design specifications despite higher hardness levels.
Softer Materials
For softer materials, the AI system achieved an 8% increase in productivity, demonstrating its effectiveness in optimizing SAG mill operations under varying feed conditions. .Excluding samples with Wi ≥ 14kWh/t, the results for softer materials are shown in Table 3:
For softer materials, the AI system achieved an 8% increase in productivity, demonstrating its effectiveness in optimizing SAG mill operations under varying feed conditions.
Economic Feasibility
Assuming exclusive future processing of fresh rock, the estimated annual production increase is 2,694 ounces, with potential financial impacts summarized in Table 4:
5. Conclusion
The comparative tests conducted in early 2024 confirmed the superior performance of BrainiAll's AI system over manual operations.
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Productivity gains ranged from 3% to 8%, depending on material hardness.
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Annual production could increase by 2,694 ounces, with a potential profit of $781,314, subject to software costs.
The results highlight BrainiAll's AI-driven optimization in mining operations, offering measurable economic and operational benefits.
BrainiAll Study Results Speak for Themselves
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Higher Production
Output:
Optimized grinding processes translated to increased yields.
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Enhanced Resource Efficiency:
Smarter utilization of energy and materials reduced waste and operational costs.
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Consistent
Performance:
BrainiAll AI’s ability to adapt to fluctuating conditions ensured stability and reliability across the production line.
Key Benefits of BrainiAll AI Test Results
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Real-Time Optimization: The AI constantly monitors sensor data, dynamically adapting parameters to maintain peak efficiency.
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Improved Yields: By fine-tuning processes, BrainiAll ensures maximum output from raw materials.
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Reduced Downtime: Autonomous adjustments prevent disruptions, keeping operations smooth and predictable.
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Cost Efficiency: Enhanced resource utilization and energy optimization lower operational costs, directly impacting profitability.