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Grinding and Flotation Optimization Using Operational Intelligence

In recent years, metal-producing companies have increased their investment in automation and technological innovation, embracing new opportunities to enable transformational change. Transformation to a digital plant can fundamentally revolutionize how industrial complexes operate...

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Collaboration at the Enterprise using Real Time Data Analysis:
Real-TimeFrom Data to Action

Intelligent System (IS) technologies are receiving much attention in a wide range of process engineering applications from plant operations to enterprise-wide competence centers. The application of rapidly changing technologies has become a serious challenge to both management and technical teams. Data, captured from diverse real-time devices, manufacturing assets, and transactional systems, can be aggregated into information and structured by context for its use....

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Metallurgy Analytics: Transforming Plant Data Into Actionable
Insights

The advent of the digital revolution has now enabled us with numerous tools that could be leveraged to transform our operational data into actionable insights. Key opportunities with digitization include better visualization, transparency, integrated planning and execution for value-chain optimization, which results in smarter production, intelligent response to changes in ore, process and equipment conditions, reducing energy and waste, along with prevention of asset breakdown, safety and environmental issues...

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Dynamic Model-Based Flotation Performance Monitoring

Froth flotation is widely used for the separation of particulate materials in the world. It is a complex process whose operational behavior in process plants is difficult to predict. This model uniquely linked the particle/bubble interactions and water transport phenomena to the flotation cell hydrodynamics...

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Grade Recovery Optimization Using Data Unification and Real-Time Gross Error Detection

The efficient operation of any modern metallurgical facility depends on the accurate measurement and estimation of flow rates, inventories, and the composition of their intermediate and final products. All of this information is subject to both statistical errors and gross errors, which can lead to poor estimation of efficiency, yields and specific energy consumption...

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Bascur, O. A., 2024, Maximizing copper production by proper water management using a Digital Twin,
International Mineral Processing Congress, IMPC 2024, Washington, USA

Mineral processing plants processing low-grade ores require large amounts of energy and water to operate in a sustainable and profitable state. These ores present large variations in their mineralogy, metal content and hardness. These low-grade ore plants process mostly rock in the first part of the process, followed by traditional mineral processing and water recovery systems. Currently, mineral processing plants operate in silos and lack the necessary integration of data from mining, grinding, classification, flotation, thickening, and tailings processing...

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Measuring, Managing, and Maximizing Refinery Performance

Implementing continuous quality improvement is a confluence of total quality management, people empowerment, performance indicators, and information engineering. Supporting information technologies allow a refiner to narrow the gap betweenmanagement objectives and the process control level. The dynamic performance monitoring benefits come from production cost savings, communication improvement, and enhanced decision-making. A refinery workgroup information flow model helps automate continuous improvement of processes, performance, and the organization.

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Real-Time Information Management Infrastructure
– Collaboration at Mine-Mill for Asset Optimization

Recent advances in industrial automation require a new approach to get plants to reduce their start-up times and adapt to the varying ore types. Integration of many subsystems is a requirement for improved operational management in metallurgical complexes' operations. For example, drastic changes in ore type at the mine require a proactive evaluation for the optimal crushing requirements for improved leaching of the ore. The access to the internet and faster networks are assisting in providing high visibility of the operations...

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Measuring, Managing and Maximizing Performance in Petroleum Refineries

The implementation of continuous quality improvement is the confluence of management quality, people empowerment, the use of performance indicators, and information engineering. The supporting information technologies allow a refiner to narrow the gap between management business objectives and the process control level. Dynamic performance monitoring benefits come from production cost savings, improved communications and enhanced decision making. A refinery workgroup information flow model is presented to help automate continuous improvement of processes, performance, and the organization.

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Operational Decision Support for Low-Grade Mineral Processing Plants

Ores are becoming extremely variable with mineralogy and hardness disturbing the integrated crushing, grinding, flotation, and thickening processes. The current grinding and flotation sensors provide large amounts of data for process optimization. To augment the operational knowledge for proactive actions for improving the performance of the grinding and flotation circuits, we need to add the right process knowledge context and operational modes...

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