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“Operations optimization is estimated to provide the most economic value out of all IoT use cases by 2030”
Resolving complex operational challenges may be the key to untapping significant savings and value for many industrial businesses. Today we can learn from the vast amounts of big data being produced and the application of machine learning and artificial intelligence technology to rapidly transform businesses to be leaner and more productive.
Whatever the objective, be it increased yield, reduced consumption or improvements to product quality or equipment utilization, if high quality data is available, AI can be used to uncover unexpected correlations and contributing factors to help businesses optimize today, for a better tomorrow.
OPUS is a proven technology, producing optimization insights for our customersRead more
The VROC platform has generated over US200 Million in savings to date for our customersRead more
Sensor and equipment agnostic for ease of adoption across business units and sitesRead more
No programming or coding experience necessaryRead more
Without any programming or coding experience, subject matter experts can model their operational processes and systems and uncover insights for optimization, including
Our real-time insights allow teams to make faster more accurate business decisions, rather than make theoretical recommendations based on out-dated historical data analysis.Download ‘Transitioning to Automated Data Science’
“We have prolonged the gas compressor reliability to four months, from a maximum of 2 weeks running. The GCM uptime has improved to a value of 21.7m USD.”
“Let everyone use, don’t restrict to any process engineer or operation engineer, give everybody access including business planners, let everyone use it. Because the beauty of this is that it will open the eyes of the importance of Artificial Intelligence in Oil and Gas.”
“It took our Focus group 2 weeks to come up with the problem with the gas compressor and form an action plan. When we met with VROC, the VROC model gave all the problems that we needed to focus on in less than 10minutes. This helped the engineers pinpoint the problem.”
“Trying to scale machine learning models across thousands and thousands of failure modes on a plant, is probably not practical in the traditional approach to data science, where you can spend three to six months building a model, training it testing and operationalising it, maybe longer.”
Discover why we need to change our thinking and approach to Data ScienceDownload Now
AI Analytics reduces improves energy production and leads to reduced fuel costs for power plantRead Case Study
The next frontier for scalable AI is the democratization of data through the use of analytics process automation (APA)Read Full Article
The value of the insights that can be obtained from Industrial analytics is so great that businesses need to find ways to ovRead Full Article
Chemicals are an operating cost for a water treatment plant. Operators can reduce costs by dosing just enough chemical to acRead Case Study
Understanding inherent biases this is critical for recognising how they become present in AI-driven technology, thanks to pRead Full Article
Discover what are the challenges experienced in scaling data science and the emerging opportunities for growth within industWatch Now
Explore the difference in data science offerings, understand the differences and advantages.Read Full Article
Ready to embark on a pilot project or roll-out the innovation enterprise wide? Perhaps you need assistance integrating your systems or accessing your data? We have a solution to help you as you progress through your digital transformation.
Interested in a demo of one of our data solution products?
DataHUB4.0 is our enterprise data historian solution, OPUS is our Auto AI platform and OASIS is our remote control solution for Smart Cities and Facilities.
Book your demo with our team today!
Ready to embark on a pilot project or roll-out AI innovation enterprise wide? Perhaps you need assistance integrating your systems or storing your big data? Whatever the situation, we are ready to help you on your digital transformation.
The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
Learn more about DataHUB4.0, VROC's distributed enterprise data historian. Complete the form form to download the product sheet.
Discover how you can connect disparate systems and smart innovations in one platform, and remotely control your smart facility. Complete the form to download the product sheet.
'OPUS, an artistic work, especially on a large scale'
Please complete the form to download the OPUS Product Sheet, and discover how you can scale Auto AI today.
Interested in reading the technical case studies? Complete the form and our team will be in touch with you.
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