Demystifying Industrial AI

THE IMPORTANCE OF STATISTIC AND PHYSICS ANALYSIS WITH MACHINE LEARNING IN INDUSTRY APPLICATIONS

Industrial processes lend themselves to statistical and physics-based analysis. When these techniques are applied manually by a data scientist, they produce accurate and predictable results as a post analysis solution. This is where machine learning takes over and brings additional benefits to traditional approaches.

Some of these benefits include;

• Holistic approaches to data driven problem framing and solving
• Plant based (entire asset) vs equipment based (condition/physics based) modelling
• Improved time-intensive calculations through advanced algorithms
• Self-validation by introducing new data and reinforced learning
• Autonomy

All these terms describe tools in the toolbox of AI for industrial data.

For AI to build a statistical or mathematical model of a certain problem, it needs data and lots of it. The more data it has the better it is at dealing with dynamic behaviours of an industrial process. Machine learning algorithms can automatically calculate the current or future status of the sensor data and derive further meaning from it.

Using purely statistical or physics-based models alone can provide a post-mortem fitted result. But in real life applications the data is never static and due to wear, environmental and human interaction of these systems their behaviour will change over time. To deal with the dynamic behaviour of a process you need artificial intelligence and specifically machine learning by which multi-dimensional problems with prominent level of uncertainties can be dealt with.

Auto Machine Learning (Auto ML) is a sophisticated pre-configured and pre-tuned Machine Learning solution for both data civillians and data scientists without the necessity to complete large volumes of manual data preparation, model selection, model hyperparameters, and model compression parameters, etc. Auto ML can use both supervised and unsupervised learning, not involving the direct control of the developer. It is able to extract valuable insights and detect patterns, ideal for predictive maintenance, root cause analysis and time-to-failure insights.

At VROC we address the challenges of behavioural change, big data and iteration using Auto ML techniques, including the following;

• Data uniformity and cleansing
• High speed distributed data access
• Out of order time-series data processing
• Linear and non-linear time-series filling
• Data ingestion using real-time industrial communications protocols and batch ingestion
• Fast model training and stream training
• Rapid deployment and platform scaling
• Auto labelling and optimization
• Dynamic and real-time data aggregation for visualization
• Visualization tools including real time dashboards for central ops facilities
• Optionally web-based SCADA for control of processes
• Additional numerous proprietary techniques.

YOU LOST ME AT AI!

To summarise that technical description, its best to think of AI and machine learning as advance mathematical equations. Due to the volume of the data and computing limitations it can be hard to construct these equations manually. A typical data science approach to solving complex problems would be to apply algorithms/equations to a subset of historical data. This can require trialling multiple different algorithms over time to try and get the most accurate result.

It is this manual approach that has left many in the industry disillusioned at the inability to scale AI and experience tangible results.

A DIFFERENT APPROACH

At VROC we have a different approach. It’s automated, scalable, and best of all gives real-time insights for time-critical situations.

Our no-code AI platform, OPUS allows end-users to simply define the insight they are looking for without the need to know anything about AI or machine learning. They don’t need to categorise data or tune the algorithm. The VROC platform will automatically analyse the available data (live and historical data) and extract insights tailored to your requirements. No coding required, no data manipulation, just real time insights.

This unique holistic approach, which analyses a whole plant or facilities data, helps identify un-foreseen correlations between processes and helps identify causes of deviation with pin-point accuracy to the individual component or sensor level.

UNDERSTANDING THE INDUSTRIAL USE CASE

Automated AI is being used across many industrial settings, from oil and gas, mining and resources, renewables, utilities, and manufacturing. Just some of the use cases include;

• Live monitoring of assets and industrial processes
• Predicting equipment future failures for early intervention, for example the first failure on a produced water pump
• Optimizing fuel consumption for a power plant by identifying a fault in an air supply system
• Reducing OPEX in late life assets
• Aiding the reduction, remote working or centralisation of asset management and operations teams
• Accurately identifying the root cause of a potential contamination incident, avoiding a significant safety event and improving environmental outcomes

IS AI SAFE AND RELIABLE FOR INDUSTRIAL SETTINGS?

Many industries are accustomed to routine maintenance inspections, and contractual obligations with OEM’s for maintenance and warranties. These often restrict operators, keeping them tied to unnecessary activities and high ongoing costs.

Moving away from these traditional methods can feel risky. However, nearly all equipment and assets are fitted with sensors that can give operators greater real-time insights than routine inspections will ever provide.

For industrial processes, where 24-hour productivity is required, automatic AI data solutions can provide the analytics to help improve operational efficiency and maximise production.

Advanced analytics are provided to engineers and operators, to assist them in their critical decision making. These subject matter experts still make the final decisions, they just have data insights to help inform and reinforce their decisions.

AI FOR THE FUTURE

Industrial AI is the future of industry. Not flying cars and robotics that replace entire workforces. AI is a powerful analytical tool, that when used by businesses can assist them in generating powerful ROI.

Learn more.