Grinding Media Optimization System Reduces Mill Operating Costs

A collaborative partnership between VALE S.A., Instituto Tecnologico Vale, and the Federal University of Ouro Preto has developed a method and system for optimizing grinding media replacement in wet ball mills. The technology uses a fuzzy controller to determine optimal replacement parameters and automates the replacement process, reducing energy consumption and operating costs in mineral beneficiation operations.

The Problem

Comminution operations, which break mineral material into progressively smaller particles, play a crucial role in mineral beneficiation and represent one of the most energy-intensive stages of mining and mineral processing. The energy expended to fragment material and the mechanical effort involved in grinding processes have a significant impact on both operating and capital costs. Traditional approaches to grinding media replacement rely on fixed schedules or reactive replacement when equipment fails, leading to either premature replacement and unnecessary costs or continued operation with degraded media that reduces milling efficiency.

The challenge requires optimizing when and how grinding media should be replaced across multiple mills operating simultaneously, considering each mill’s unique operating conditions, power consumption patterns, and material characteristics.

What This Invention Does

The system determines required power values for each mill through a fuzzy controller that processes multiple operational parameters. It then estimates the actual power of each mill based on its operational data. Using this information, a grinding media replacement determinant calculates specific replacement parameters for each mill, considering factors such as media wear, power consumption trends, and milling efficiency. Finally, an automation module replaces grinding media based on the calculated parameters, optimizing the timing and extent of replacement for each mill individually.

The fuzzy controller approach allows the system to handle imprecise operational data and complex relationships between variables more effectively than rigid algorithmic approaches. The system can account for variations in material type, mill configuration, and operational conditions that affect media wear rates, enabling more precise replacement decisions that reduce both under-utilization of media and costly premature replacement.

Key Features

• Fuzzy Controller Logic. The system uses fuzzy logic to process complex operational data and determine required power values without requiring perfectly precise measurements.
• Mill-Specific Power Estimation. Individual power calculation for each mill based on its unique operational characteristics and sensor data.
• Replacement Parameter Determination. The system calculates media replacement parameters tailored to each mill’s specific conditions and requirements.
• Automated Replacement Execution. The automation module executes media replacement based on calculated parameters, reducing manual intervention and human error.
• Energy Efficiency Optimization. By timing replacements to maintain optimal mill performance, the system reduces energy consumption and improves beneficiation efficiency.

Who Is Behind It?

This innovation resulted from collaboration between VALE S.A. (Brazil’s largest mining company), Instituto Tecnologico Vale, and Universidade Federal de Ouro Preto. Inventors include Daniel Luiz de Souza, Mário Sérgio dos Santos, Cássio Pascoal Costa, Luciano Perdigão Cota, and Marcone Jamilson Freitas Souza. The patent was filed on 22 August 2025, claiming priority to Brazilian Patent Application 102024018024-0 filed on 2 September 2024. Spruson & Ferguson represents the application in Australia.

Why It Matters

This patent addresses a fundamental inefficiency in global mineral processing operations. Mining and mineral beneficiation consume enormous amounts of energy, and optimizing grinding operations can significantly reduce operating costs and environmental impact. The fuzzy logic approach represents advancement in how complex industrial systems can be optimized through intelligent control systems that adapt to variable conditions rather than operating on fixed schedules.

For mining companies operating multiple mills with varying conditions, the ability to optimize media replacement individually for each mill could translate into substantial annual cost savings and improved overall mill fleet efficiency. This technology demonstrates how artificial intelligence and advanced control systems can drive improvements in resource extraction and processing sustainability.

Related Concepts

Ball mills are cylindrical grinding devices filled with steel or ceramic grinding media that crush and grind ore through impact and attrition. They are central to mineral processing operations worldwide. The condition and quantity of grinding media directly affects mill power draw and grinding efficiency; worn or depleted media forces the mill to consume more energy to achieve the same particle size reduction.

Fuzzy logic is a form of mathematical logic that handles imprecise, partial-truth data by reasoning in degrees rather than strict binary states. In industrial control systems, fuzzy controllers are well suited to processes with complex, non-linear relationships between multiple variables – such as mill power consumption, ore feed rate, and media wear – where classical control algorithms struggle to perform reliably across varying conditions.

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AU 2025220833 was published in the Australian Official Journal of Patents on 19 March 2026 and is open for public inspection. Patent applications represent inventions that are sought to be protected and do not necessarily reflect commercially available products.