The essence of Calejo Optimize™

Calejo Optimize™ is an optimization engine for industrial processes. It’s a new way of modeling and helping the industry to manage, structure, analyze, simulate, optimize and control the overall data and knowledge flows from its processes.


    Non-linear models

    DAE compatible and more scalable than other solutions

    Variable time-step solving

    Faster optimization than reinforcement learning

    Easily deployable in edge devices, cloud and personal computers

    Mixed neural network and physical equations in any combination

Implementation in four stages

During a joint workshop on-site with the customer, the functions and data flows of the current process are mapped to obtain consensus around boundaries and what effect goals the use of Calejo Optimize will achieve.

Based on set goals, Calejo’s representatives then announce the conditions required in terms of the amount of existing data, the handling of real-time data and the configuration of the control system.

The industry is in the driver's seat The customer determines the degree of commitment. It is the customers who is the experts in their own process. We discuss together the best solution and what is feasible based on the conditions that exist.

What Calejo needs is input from the customer about how the process works and also help with collecting data. If the customer does not have their own knowledge or can provide their own resources, Calejo can help with guiding, or contribute with resources from one of Calejo’s many partner companies.

We adapt to the customers technical conditions We can install our solution with aggregated data from the process locally inside the facility or in private or public clouds. We can also – if necessary – with help from our partners create appropriate systems and cloud solutions to collect and store all information.

When it comes to control systems, we are not dependent on any special ones. Calejo delivers an overall control system and we already cooperates or can cooperate with most control systems on the market.

We are happy to AI train operators and management The customer does not need any AI skills. However, together with our partners, we are happy to assist and train operators and management to ensure that employees have a better understanding of the possibilities of technology and increase their own and the company’s overall AI maturity.

Implementation takes place in the following stages:

Stage 1. The creation of a digital twin.

    Process mapping.

    Data verification based on measuring points, quality and quantity.

    Modeling a digital twin over the process.

    Training the digital twin.

    Verification of the digital twin against the actual process.

Stage 2. Optimization of the process based on given power goals.

Priorities and rules for optimization are developed. Calejo Optimize can optimize processes based on more than one effect target. A mutual priority between the goals must thus be created. Other process critical boundaries and rules must also be defined. The system is optimized on the basis of given conditions.

Stage 3. Interface for operators.

Together with selected operators, the interface between Calejo Optimize and the operators is adapted so that the instructions’ designations and nomenclature correspond with the other operator environment.

Stage 4. Verification and final delivery of the implementation.

    Operator support is being rigorously tested by Calejo’s staff to verify the implementation.

    Training of operators and others concerned with the use of Calejo Optimize.

    Commissioning of Calejo Optimize.

Frequently asked questions
Together with the customer, we collect, wash and analyze important input data from the process, after which we create a so-called digital twin. Our digital twin is a hybrid solution, which can be based on both traditional physical calculation and what we usually call AI, that is, the connection between data.
With the help of the digital twin, real-time data from the process control system and production planning, the operator can get suggestions on how process parameters should be adjusted to achieve an optimal and sustainable total production.
The solution can most easily be compared to the type of navigation system used in cars. The navigation system relates to existing conditions and existing traffic or process environment. But it can also take into account external and more varied factors and temporary deviations, such as maintenance work, queues and disturbances in connection with the car or as in this case the process navigator’s route suggestions. It can also suggest an update of the route during the journey.
In the next step, the digital twin can also be used to train, simulate, optimize and ultimately also control an autonomous industry.
Calejo Optimize 1.0 is based on Open Modelica. The different parts of the model are linked to the database. In the library there are unique AI blocks to be used. The result is presented in existing program dashboards, SCADA systems etc. or in a separate instrument panel, which is part of Calejo Optimize. The system can collect data from all modern platforms and systems. Ie IoTplatforms, Azure, Siemens, ABB, SAP, SQL, Oracle, Maximo, etc.
Calejo Optimize is an optimization engine for industrial processes. It represents a whole new way of modelling and helping the industry to manage, structure, analyze, simulate, optimize and control the overall data and knowledge flows from its processes. Calejo Optimize has been developed based on the latest scientific findings and represents the unique result of 15+ years of experience from various international AI projects.