OUR SOLUTIONS
EmpiricAI’s solutions are data-based tools and algorithmic models that Industrial plant professionals can use to address specific challenges and provide recommendations to make specific processes more efficient and provide an immediate ROI.
Operational Advisors
Cooling Tower System Advisor is an advisory tool that utilizes a physics based thermodynamic model, at its core, to identify operational recommendations that maximize plant output and efficiency. An AI/ML based engine compares the recommended settings to historical settings to assist in quantification of the improvement magnitude.
Running the cooling tower on recommended set points helps user achieve:
➜ Reduced supply water temperature
➜ Improved condenser performance
➜ Better energy efficiencies
➜ Improvement in plant’s output.
Running the cooling tower on recommended set points helps user achieve:
➜ Reduced supply water temperature
➜ Improved condenser performance
➜ Better energy efficiencies
➜ Improvement in plant’s output.
A ML/AI anomaly detection tool that detects, alerts, and advises operators about auxiliary power consumptions at the plant, system, and asset level. Operators have an intuitive view of each consumer whereby bad actors are easily detected and alerted. The ALM advisor contributes to:
➜ Maximum availability for dispatch
➜ Reduced cost of generation
➜ Reduced time for trouble shooting problematic equipment.
➜ Maximum availability for dispatch
➜ Reduced cost of generation
➜ Reduced time for trouble shooting problematic equipment.
The Reverse Osmosis (RO) chemical dosing advisor uses an ML/AI engine to provide plant operators and engineers with analysis and real time advice on how to achieve a lower overall cost of production via optimization of chemical dosing rates without any loss in production rate, water quality, or plant reliability and availability. Users can view a summary or detailed view of each dosing chemical, it’s variation from optimal and the associated cost impact. The cost optimization financials take into consideration chemical usage, inlet treatment filtration, as well as membrane cleanings and replacement.
➜ Chemical Dosing Costs
➜ Inlet Filtration Maintenance Costs
➜ Membrane Maintenance Costs
➜ Chemical Dosing Costs
➜ Inlet Filtration Maintenance Costs
➜ Membrane Maintenance Costs
Process Setpoint Advisor uses a combination of physics-based models and ML/AI based models to recommend process settings to optimize critical plant KPI’s such as production output and energy efficiency. Real-time operating data from the DCS are channeled to the models where models compare current settings to optimal set points and then offer a recommendation to the plant operator and engineers.
The Concentrated Solar Plant (CSP) Energy Storage Advisor sits on top of a combined physics and ML/AI model engine to recommend the optimal generation versus energy storage mix for each day or partial day. The advisor engine takes into condition the forecasted sun energy, process physics, and the economics of energy sales process and how they can vary throughout the day.
➜ Daytime generation vs storage for nighttime
➜ Energy sales rates
➜ Turbine and storage capacities
➜ Daytime generation vs storage for nighttime
➜ Energy sales rates
➜ Turbine and storage capacities
Maintenance Advisors
The GT Offline Wash Advisor uses a combination of turbine thermodynamics and plant economic operating factors to compare the currently planned next wash date to the most economically optimal date. The compressor efficiency trends are calculated from the real time DCS data, averaged over a specified time period and then trended. An ML/AL based prediction engine is then used to forecast the trend over the coming weeks to find the optimal trade-off point between the losses from reduced capacity and efficiency versus the cost of a 1-2 day elective shutdown.
The Gas Air Heater Wash Advisor applies to steam turbine thermal power plants and uses a combination of turbine thermodynamics and plant economic operating factors to compare the currently planned next wash date to the most economically optimal date. The heater effectiveness and DP trends are calculated from the real time DCS data, averaged over a specified time period and then trended. An ML/AL based prediction engine is then used to forecast the trend over the coming weeks to find the optimal trade-off point between the losses from reduced capacity and efficiency versus the cost of a 1-2 day elective shutdown.
The Heat Exchanger Cleaning Advisor applies to any plant whose heat exchangers have scaling of fouling cycles that significantly influence plant operating financial metrics. The advisor combined heat exchanger first principles with plant impact derivatives, as well and cost factors of those impacts. The result is a recommended date to take the exchanger out of service for a cleaning that to heat transfer physics. The effectiveness trends are calculated from the real time DCS data, averaged over a specified time period and then trended. An ML/AL based prediction engine is then used to forecast the trend over the coming weeks to find the optimal trade-off point between the losses from reduced capacity and efficiency versus the cost of a 1-2 day elective shutdown.
Process Analyzers
The Process KPI Analyzer provides measured, expected, and deviation of plant parameters using user-editable CSVs , Ebsilon Models and Data Science Models. The plant data is imported, validated, and then ingested into the KPI. These KPIs are useful in determining the performance of the plant, and are an integral foundation for use in the associated trending, root cause, and anomaly detection tools.
The Degradation Analyzers take the overall loss in key plant performance indicators (such as output capacity and energy index) and break them down into the contributing components, such that corrective actions (Capex or Opex) can be taken quantitatively. The key indicators for each type plant will be customized based on customer criticalities. The underlying physics models provide the calculation foundation, and can be tuned by the user to keep pace with regularly scheduled maintenance events.
The What-If Analyzer give the customer direct easy-to-use access to the foundational physics model such that various studies can be made. From a simple browser interface with no training on how to use models, the customer can run the models. With What-If Analyzer, maintenance decisions, operational setpoints decisions, and plant upgrades decision can be backed up with actual physics simulations, taking the guesswork out of the equation.
Plant Field Solutions
Digital Log is an application developed by Engro Digital to allow the plant personnel to collect field data using hand held devices. This ensures increased productivity of the lead engineers & site technicians, improved visibility of equipment health to the site management and drastically reduces site’s paper consumption
Professional services
AI/ML Modeling
We leverage on our core expertise in EDA, IDA, predictive and prescriptive data analysis, ETL techniques, big data handling, statistics modeling, deep learning and neural networks to develop sophisticated data science models for our customers to solve complex problems.
Engineering Solutions
Our in-house subject matter experts in industries like petroleum, petrochemicals, power generation and chemical processes develop engineering models using software technologies such as Ebsilon, Gate cycle and Aspen to solve problems for our customers.
IIoT Solution Development
We provide custom solution development services including IIoT solution development. Web and mobile Application Development, UI/UX development, 3rd party integrations, cloud and on premise deployment, monitoring and administration services, data mapping and transfer services, recovery and backup services, data integrity and validation services, analytics and dashboards, cyber security services and database management.