Our Offerings
Our technology is unique as it is executed with Physics-model-based, with Degradation
Entropy Generation, Shannon Information Theory, Nonlinear Robust Observers, Confidence a posteriori estimates, etc.
We provide closed-loop system monitoring (and control-aide) and diagnostics of operational health and integrity of oil field operations. Our solution increases energy availability and reduces operation & maintenance costs.
Ability to do Just-In-Time maintenance, reduce inventory, and have more accurate lead
times. Enables risk analysis with higher confidence metrics.
Consulting
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Dry gas Seal Failures
- Motor Pump
- System Modeling [Digital Copy]
- Realibity Assessment
- Artificial intelligence with Physic base models
SAHAS
System Asset Health Assurance System
- Programmatically diagnose your assets health and predict their degradation
- Degradation Entropy Analysis
- Shannon Entropy Generation
- Automatic Reports
- Connect your existing PI System and
Smart Connect
Why are we here
Need from the Industry
There are clear limitations of current signal-based diagnostics, thus we created our technology to address these limitations. Thera is significant potential benefits of such technology in the areas of safety, production, and environment.
90+ years Experience in Diagnostics of Industrial Equipment
Our team has 90 years of accumulated experience in the Energy Industry. Machine Essence’s experience is a concentration of subject matter experts with real-life experience both on and out of the field with the tools to resolve some of the most challenging aspects in diagnostics.
Commercializing Our Technology
This technology was developed out of careful research and development at The University of Texas at Austin. It has gone through various vetting processes. The theorems applied have been recognized in the most esteemed scientific journals. Our technology has already been deployed in the industry with successful results proven by our models.
Business Opportunity
The industry has been ridden with diagnostic solutions that fail to meet expectations. We concentrate on Physics-Based-Models, meaning we hold our models to the rules of the real world (physics) and we concentrate on the concept of Observability in order to ascertain how a particular fault would be observable. Thus, we are able to ascertain real-life results since we are physics-based with great accuracy.
The Industries
Oil & Gas
Chemical and Petrochemical
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Power Generation
The intrinsic nature of these industries, is that it is riddled with many assets, and managing these assets is a feat in itself. Some of the assets are safety and production critical where maintenance and reliability are of utmost importance.
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One of these assets’ failures and downtimes could represent hazard conditions and cost millions of dollars. Our solution is made to diagnose, and predict with a high level of certainty, failure development in the time and determine failure modes and components on their way to failure.
Value Proposition
Gains
Energy availability increases and reduces operation & maintenance costs. Ability to do Just-In-Time maintenance, reduce inventory, and have more accurate lead times. Enables risk analysis with higher confidence metrics.
Novel
Physics-model-based, with Degradation Entropy Generation, Shannon Information Theory, Nonlinear Robust Observers, Confidence a posteriori estimates, etc.
Valuable
We provide closed-loop system monitoring (and control-aide) and diagnostics of operational health and integrity of oil field operations.
Savings
Reduce Cost & Inventory by 50% and save on average $9.7M.
Reliability
Reduce Unscheduled Downtime by 80%, False Alarms by at least 50% and unscheduled maintenance by 25%.
Founders
Mike Bryant, Phd, PE
CEO
After obtaining a BS in Bioengineering from the University of Illinois at Chicago in 1972, Mike achieved a Masters in Mechanical Engineering at Northwestern University in 1980 and a PhD in Engineering Science and Applied Mathematics from the same university in 1981.
Benito Fernández, Phd
CTO
Benito began his career in Venezuela, where he studied Chemical Engineering in 1979 and Materials Engineering in 1981. In 1981, he moved to the US to carry out graduate research at MIT, where he received his MS in 1985 and PhD in 1988, both in Mechanical Engineering.
Antonio Machado is a seasoned mechanical engineer with over 40 years of industrial experience specializing in Rotating Equipment and Reliability. He holds a Dipl.-Ing./M.S. (1990) in Mechanical Engineering with a focus on Turbomachinery and Internal Combustion Engines from the University of Karlsruhe, Germany, and a B.S. (1983) in Mechanical Engineering from the University of Zulia, Venezuela.
Our Publication
UNCATEGORIZED
UNCATEGORIZED
