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Tech Corner

13 Mar 2020

Part 2: Using Condition Indicators for Predictive Maintenance

Learn how to Extract Condition Indicators for your machine learning algorithm so you can predict and prevent the next equipment failure. 

18 Feb 2020

Part 1: What is Predictive Maintenance?

In this first eBook of its series we take a look at “What is Predictive Maintenance?.” In future posts we will cover how we can use MATLAB to Extract Condition Indicators, Estimate Remaining Useful Life, and so much more. 

14 Feb 2020

Enabling Data-Driven Decision Making

In this post, we will show you how we typically make use of Opti-Num’s Data Management Framework and PowerBI to process, model and visualise your big data into dynamic and insightful views tailored to your business needs.  

29 Jan 2020

Feature Selection made easy with ‘screenpredictors’

Pre-processing of features or predictor variables for the development of machine learning models is usually a tedious process. The MathWorks has come to the rescue with a function called screenpredictors that was released with the R2019a MATLAB version. Several customers have commented on its usefulness, which is why I’ve been inspired to write this post.

26 Nov 2019

Conifers for Crypto – Bitcoin Volatility Forecasting Using Machine Learning

Verushen Coopoo, Application Engineer Opti-Num Solutions (2019) In this script, we demonstrate MATLAB’s machine learning abilities to build a regression tree that will be used to forecast the 10-day volatility of Bitcoin. We show that in one environment, you can download up-to-date Bitcoin data, rapidly prototype a machine learning model, and then test and evaluate […]

26 Nov 2019

SuperBru Predictions with AI

Congrats to the Boks! For the recent Rugby World Cup a few members of the Opti-Num team participated in a sports prediction game using the SuperBru platform. Points were awarded in the Rugby World Cup for: Predicting the correct winning team Predicting the correct margin of winning Many of us used our rugby knowledge, patriotism […]

26 Nov 2019

AI in Industry 4.0: I have all this sensor data… Now what?

Predictive maintenance uses data to monitor the condition of equipment. Using fourth industrial revolution techniques means reduced failures, less machine downtime, reduced maintenance costs, and so much more. Most industrial plants collect large amounts of sensor data from their equipment. The sheer volume of data may leave most people thinking “What now?”. Using this data to inform smart business decisions requires a rare combination of both domain and statistical expertise.

26 Nov 2019

Accessing Equity Data using a MATLAB Web App

Timely and convenient access to data is crucial in the world of finance to enable rapid and informed decision-making.  To address this need, we have developed a web app in MATLAB that demonstrates how data access and custom analytics can be made accessible across an organisation. The app shows a very simplistic workflow that allows […]

26 Nov 2019

From Simulation to Implementation: Model Predictive Control on a Package Boiler

More and more manufacturers are adopting a new approach to process optimisation by integrating practical advances in technology into their day-to-day operations. The concept is built around developing a plant-wide collaborative process that results in efficiency gains that would otherwise have been missed. Many global tech and industry experts believe that this approach is the […]