Our ORTO Software

ORTO (Oram Real-time Optimisation) is proprietary software which utilises our novel optimisation algorithm, implanted within 'ORTO agents'. 

One or more agents make up an optimisation scheme, having a defined optimisation objective. Each agent is autonomous and self-learning. At the heart of each agent is a deterministic algorithm. They are not AI/ML based. 

Each agent has the optimisation variable (OV) as its main input and continuously adjusts a single unique manipulated variable (MV) e.g. a setpoint of a PID controller, in a primary to secondary cascade fashion. For an agent to work, there must be a cause-and-effect relationship between the MV and OV. An ORTO agent’s speed is governed by its configuration parameters, set by the engineer. 

Unlike existing real-time optimisation software techniques, ORTO agents help make the optimisation of a process or system simple and intuitive. The technology encapsulates a novel, easily implemented model-free approach i.e., there is no need to build a dynamic or steady state first principles or empirical model of the process.

While ORTO agents are functionally independent, their actions collectively contribute to achieving the defined optimisation objective. This mechanism is referred to as 'the ORTO Agent Principle’. The ORTO agent principle enables identifying the true optimum and, its tracking over time, if and when it moves.

Yes. We have gone back to square one and developed a completely new approach to RTO. Our ORTO technology is both novel and revolutionary. We sincerely believe it will help make real-time optimisation as ubiquitous as PID control across all processes and systems. 

We believe our technology is truly transformative. Reasons are numerous:

• Being model free, ORTO optimisation schemes can be built easily and quickly. ROI is thus accelerated and increased.
• Being model free, there's no process model mismatch to grow over time. As a result, ORTO schemes require far less maintenance than a traditional model based approach. Maintenance costs are significantly reduced and ROI is maintained.
• Each independent ORTO agent is easy to configure and intuitive to the engineer. Engineers involved do not have to be trained in complex software packages or versed in optimisation theory and practice i.e., external, highly specialised resources are not needed to build and maintain ORTO schemes. 
• ORTO schemes are highly flexible and scalable. ORTO agents can be readily added (to improve overall optimisation performance) or removed from an optimisation scheme (if it is deemed the agent is adding little to achieving the overall optimisation objective).
• ORTO finds the true optimum and, if it moves, tracks it over time. ORTO schemes can therefore yield bigger benefits compared to existing traditional RTO techniques.