IN Brief:
- ABB has launched ABB Ability Augmented Operator to integrate AI-assisted process monitoring and operational decision support into existing control room workflows.
- The suite combines Anomaly Detector, Knowledge Extractor, and Process Predictor, providing early deviation detection, historical context, and what-if simulations.
- The system is intended for continuous industrial operations including power generation, with human operators retaining responsibility for the decisions made.
ABB has launched ABB Ability Augmented Operator, an AI-enabled software suite that combines process anomaly detection, historical operating knowledge, and simulations for industrial control rooms. Introduced at ADIPEC in Abu Dhabi on 2 November, the software is designed for power generation, chemicals, oil and gas, water, and other complex process operations. It works within existing control room workflows, allowing operational staff to examine changing plant conditions before deciding how to respond.
The suite brings together current process data, comparable events from the facility’s operating history, and predictions of how process variables could respond to a change. Control rooms already present measurements, alarms, and equipment states, but interpreting several interacting conditions can require knowledge that is spread across records and experienced personnel. ABB’s application is intended to make that information available together when operators assess a developing condition.
Anomaly Detector evaluates multiple process measurements to identify departures from normal behaviour. Variables such as flow, pressure, and temperature can change in combination before any one measurement reaches an individual alarm threshold. Looking for unusual relationships within the available data provides another way to draw attention to developing operating conditions. The resulting indication is additional information for the team responsible for the plant, which must assess it against the current process state and established operating procedures.
Knowledge Extractor searches the facility’s own historical operating information for similar events, including relevant records of what happened and how personnel responded. An operator investigating an unusual process pattern can therefore compare it with previous conditions at that plant. The application also makes recorded experience accessible across shifts and to newer staff, while the applicability of an earlier response depends on whether the present equipment configuration and operating conditions are comparable.
Process Predictor provides the third function, using what-if simulation to explore the possible effects of a proposed change. A control adjustment can influence several connected process measurements, particularly in continuously operating equipment where flows, temperatures, and pressures interact. The simulation shows projected outcomes for the variables represented in the model, giving personnel information to consider before applying a change through the established control system.
The functions are connected within one operating workflow. An unusual pattern identified by Anomaly Detector can be examined against historical cases retrieved by Knowledge Extractor, then assessed through Process Predictor if an adjustment is being considered. The interface presents those three functions together during a control room investigation. The data available to each function and the suitability of historical comparisons will depend on the plant’s records, instrumentation, and configured models.
Power generation is one of the industrial applications identified for the software. Generating facilities have process and auxiliary systems whose operating conditions influence one another: turbines, cooling equipment, pumps, and other plant can impose linked limits on production. A temperature or pressure change may therefore need to be interpreted alongside flows, equipment status, and current operating demands. Bringing the information into a connected investigation can support control room personnel as they evaluate an abnormal condition.
Operational responsibility remains with the control room team. ABB has designed Augmented Operator to explain its reasoning and present possible responses, while authorised personnel retain control of decisions made at the facility. Established alarms, protective systems, and approved operating procedures remain part of the process through which any intervention is assessed and executed. Plant safety continues to depend on those procedures, protective functions, and assessment of prevailing operating conditions.
Gino Hernandez, head of global digital business at ABB’s Energy Industries division, said the software draws on a facility’s experience and allows operators to test changes before making them. He connected that approach with the company’s plans for increasing operational autonomy while keeping people involved. The initial product is presented as a decision-support suite, with the control room continuing to make and implement the operating decisions.
The availability of plant knowledge across shifts is an important part of that design. In its 2025 World Energy Employment analysis, the International Energy Agency reported that advanced economies have 2.4 energy workers nearing retirement for every worker under 25. That ratio describes the wider energy workforce, rather than the staffing profile of any particular generating station. The software’s historical search function gives ABB a way to retain and retrieve recorded operating experience as teams change.
ABB identifies reduced unplanned shutdowns, more consistent process control, and improved operating efficiency among the intended benefits of combining anomaly detection, historical context, and prediction. Those functions have different inputs and outputs, but together they provide a sequence for identifying deviations, examining comparable events, and considering a response. The software has been introduced for plants with continuous or complex processes, including electricity generation.
Deployment at an individual facility will require its process information and operating records to be available to the application, along with integration into the control room’s existing workflow. The quality and completeness of those inputs will determine what the anomaly, search, and prediction functions can show operators. ABB has introduced the suite as a control room tool; individual plant installations and measured operating results will follow their own implementation programmes.
