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Industry 4.0

25 Sep 2019

Smart Manufacturing: From Simulation to Implementation

This paper, which was written by Opti-Num consultants (Richard Fisher and Jason Miskin) in collaboration with John Thompson (a division of ACTOM), was presented at the IFAC MMM (Mining, Minerals and Metal Processing) 2019 conference. It discusses a practical end-to-end implementation of a Smart Manufacturing technique, namely Model-Predictive Control (MPC) in search for efficiency gains.

23 Aug 2019

AI in Industry 4.0: Neural Networks for Time Series Modelling in MATLAB

An essential aspect of the mining process is the froth flotation process. This removes impurities from minerals, such as silica from iron ore, which ultimately determines the quality of the product. In this article we focus on how neural networks can be applied to the mineral extraction process, ensuring products of a higher quality. The […]

31 Jul 2019

AI in Industry 4.0: Reinforcement Learning for control design

Watch our two-part video series created by our Vacation Work Students Daniel and Vicky to find out more about how reinforcement learning works and how to implement a practical controller with a reinforcement learning algorithm in MATLAB.

28 Jun 2019

AI in Industry 4.0: Getting started with Machine Learning

Machine learning has made its mark! From medical diagnostic tools, speech recognition (think Siri and Alexa) to movie recommendations and predictive maintenance; machine learning techniques are being used to make critical business and life decisions.

04 Jun 2019

AI in Industry 4.0: Got Big Data?

Accessing and processing of data can be done entirely within MATLAB, no matter where it might be stored, including SQL/NoSQL databases, Spark™, and/or Hadoop®. Find out how you can tackle Big Data with MATLAB

07 May 2019

AI in Industry 4.0: How do I access my data?

What do smart homes, self-driving cars, intelligent factory condition monitoring and fault diagnosis have in common? They all need data This data often exists in several different formats The data changes with time The first step in any Machine Learning workflow involves accessing the data you want to work with. If you have worked with […]

04 Sep 2018

Industry 4.0 – Internet of Things and ThingSpeak

Industry 4.0 – Internet of Things and ThingSpeak   Internet of Things or “IoT” is becoming a popular buzz word these days. It is an emerging trend that describes a situation with embedded devices and sensors all connected to edge nodes, to upload sensed data to cloud storage resources. Data can be used in some […]

22 May 2018

Digital Transformation in MATLAB and Simulink with Predictive Maintenance and Digital Twin

In this webinar, we explore what is meant by predictive maintenance and the different workflows which can used based on the data available from a system. Learn about the value in implementing predictive maintenance, leverage machine learning techniques to get insights from sensor data and find out when you might create a digital twin of […]

24 Apr 2018

Industry 4.0 Applications – How do they get Operationally Deployed?

Industry 4.0 Applications – How do they get Operationally Deployed? The advent of Big Data and Industry 4.0 has lead companies to drive enterprise-wide digitalisation strategies. Engineers are now being tasked with implementing machine learning and deep learning into their projects to make their systems or applications ‘smart’. These challenges are mostly embraced and the […]

18 Apr 2018

Geotechnical Sensor Analysis – Kriging or Gaussian Process Regression for Fracture Risk in Mining.

Geotechnical Sensor Analysis – Kriging or Gaussian Process Regression for Fracture Risk in Mining. The ability to make informed and quick decisions is invaluable in any operation. Mining operations are particularly safety aware. For geotechnical experts to assess risks and decide on the appropriate procedures quickly, can save lives and save money. In mining operations […]