Why use Deep Blue AI's Engineering solutions?
Domain expertise from engineers
Customised cutting-edge model architectures
Built-in feedback for continuous improvement
The engineering industry has long been an early adopter of new technologies, from robotic factory workers to autonomous mining trucks.
Deep Blue AI’s founders have 25 years of experience in engineering research and application. We use this experience to identify the data and models most suited to your application and deliver state-of-the-art machine learning solutions to solve your problem.
Our modular platform and interactive dashboards make it easy to integrate our solution into your processes.
Our engineering frameworks
Detect failures and anomalies early, saving time and money due to unplanned maintenance.
Engineering - detailed solutions
Regression analysis is a tried-and-tested method for modelling engineering systems of all types. With the growth in complexity and scope, traditional regression techniques struggle to accurately model the responses of modern multivariate systems.
Deep Blue AI’s Regression engine combines technical engineering expertise with cutting-edge research in machine learning to deliver algorithms capable of modelling immensely complex systems. Accuracy is a quantum leap ahead of traditional systems and, with our cloud-based approach, so is speed.
Engineering failures are rare but, when they occur, are often expensive in terms of downtime, lives lost and property damage. Anomaly detection has traditionally been based on thresholds for different parameters but these need to be individually tuned for each machine.
Apollo, Deep Blue AI’s Anomaly Detection engine, has been designed with this limitation in mind. Apollo intelligently analyses the running of any machine to determine what expected behaviour looks like and can alert the operator when any unusual behaviour is noticed. When combined with our dashboards, failure can be detected early and predictive maintenance can be scheduled.
With the evidence of climate change growing and the greater push for companies to reduce their carbon emissions, the reduction of Energy Use is imperative. With the many energy consumers in modern industries, analysis of energy use has been difficult and limited.
Deep Blue AI’s Energy Use algorithm can predict daily energy usage based on historical data and estimate the importance of parameters affecting energy usage. This capability allows you to determine the optimum strategy to leverage energy storage ability, exploit energy market arbitrage, and design plants and buildings to minimise their energy usage.
In many applications it is beneficial to be able to group items as similar. This enables the treatment of a whole group instead of individual objects, reducing time and money spent on tasks. Classification has historically been difficult and has required decades of experience in the industry.
Deep Blue AI’s Classification engine takes the guesswork out of grouping items. Whether you are grouping risks to form risk clusters, machinery parts to form similar batches, or machinery measurements to determine machine state, our solution helps you optimise your process to save time and money.