Metals, Materials and Mining

Metallurgists and process engineers use MATLAB and Simulink to optimize throughput, minimize downtime, and increase safety. They analyze real-time sensor data, model and simulate mining operations, implement control strategies, and leverage artificial intelligence systems.

MATLAB and Simulink help mining engineers:

Develop predictive maintenance systems by applying numerical techniques to high-speed sensor data
Use machine learning with historical data to troubleshoot process problems
Use plant and equipment modeling and simulation to improve process performance
Co-operate with data scientists and IT personnel to adopt digitization
Use a digital twin to continue plant operations when sensors are down

Optimize Assets with Predictive Maintenance and Signal Processing

MATLAB can help you develop predictive maintenance algorithms customized to the specific operational and architectural profile of your equipment. Use Predictive Maintenance Toolbox™ to design condition indicators and estimate the remaining useful life of your rotary equipment.

You can use Signal Processing Toolbox™ to automate the monitoring of performance of your control loops, remotely determine the extent of corrosion or pitting in your pipelines, and detect the location and quantity of pipeline leaks.

Machine Learning, Deep Learning, and Big Data

Interactive apps in Statistics and Machine Learning Toolbox™ let you apply machine learning techniques without having to be an expert in data science. MATLAB also provides a single, high-performance environment for working with big data and developing deep learning models. This enables you to perform fault detection and diagnosis faster and better monitor your processes.

Simulating Failure Data

Traditionally, engineers optimize mining plants and processes based on data collected from sensors. However, sensor data is not always available for the multiple possible failure modes in a machine. Instead, you can use simulation data to represent failures by creating a model of your machine and simulating faulty operating conditions.

Simulink and Simscape enable you to build a model of your machine that can describe its behavior in terms of its physical components and dynamics. You can represent different failure modes of the machine by modifying parameter values, injecting faults, and changing model dynamics.

Develop and Deploy Process Control Strategies

You can use MATLAB control products to design control schemes and perform dynamic simulations to analyze plant behavior better. Validate your design with online hardware testing and rapid prototyping approaches.

Simplify Planning and Scheduling Activities

Improve efficiencies in production and scheduling through discrete event simulation. With SimEvents™, you can study the effects of task timing and resource usage in a batch production process. Using MATLAB and Simulink products, you can also conduct operational research for decisions related to forecasting, capacity planning, and supply-chain management.

Digitization

MathWorks can help you adopt and implement big data strategies specific to the needs of your organization. You can use prebuilt MATLAB toolboxes and reference architectures to simplify a wide range of applications: from integrating with enterprise IT systems, the cloud, and production data infrastructure to scaling your computation to clusters or deploying your models as applications to share with users outside of MATLAB. See how you can achieve this on the cloud.

Metals, Materials and Mining

Optimize Assets with Predictive Maintenance and Signal Processing

Machine Learning, Deep Learning, and Big Data

Simulating Failure Data

Develop and Deploy Process Control Strategies

Simplify Planning and Scheduling Activities

Digitization

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