Ωpera
Ωpera

Ωpera

Ωpera (pronounced opera) is Koidra’s operators-driven automation platform. It democratizes industrial automation by enabling production operators and managers to be in control of their automation strategies.

Ωpera provides a flexible and user-friendly web interface for the controllers to define their control strategies in a simple yet powerful way, like writing Excel formulas. Controllers can easily update and improve their control strategies over time and are no longer constrained by the cluttered graphical user interface (often with many windows, menus, and submenus) in legacy SCADA systems.

Why It Matters

1️⃣ Operators-driven. Farms, power plants, factories, and buildings (so-called plants for short) operate much the same way as they have for decades — following static hard-coded instructions. The automation logic is mostly implemented by automation engineers, and typically at the time of project development. Once operational, the automation logic frequently stays fixed and operators are hired to run the plants. Operators are followers, not leaders of automation.

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However, automation is an operation problem and operators are the domain experts at the process flow and how to optimize it. They understand better than most what need to be automated and how to improve the control strategies.

The operators-followed automation model has been around since the dawn of automation and is still prevalent today. It was the right model in the past because programming on traditional PLCs is a highly technical skill. However, modern software/hardware technologies, including but not limited to low-code development, now enable less technical users to easily program and evolve their automatable tasks.

A typical control room setup. Controllers frequently have to follow the screens and manually change setpoints.
A typical control room setup. Controllers frequently have to follow the screens and manually change setpoints.

2️⃣ Continuous improvement. As traditional automation model doesn’t enable operators to improve and evolve the control strategies, the continuous improvement culture (aka. kaizen) is hard to practiced and realized. This eventually leads to loss of yield, efficiency, and competitiveness.

3️⃣ Transparency. Most manufacturing plants either don’t have automation or have automation logic hard-coded inside black boxes called PLCs (programmable logic controllers). This gives rise to the lack of transparency. Transparency is important because it leads to changes in behavior, enables teamwork, continuous improvement, and hence operational excellence.

Other limitations of traditional automation

4️⃣ Control sophistication. Traditional automation is frequently programmed using low-level ladder logic or equivalent. Such low-level programming logic hinders the programmers’ ability to program sophisticated logic, that may be required in complex control applications (such as greenhouse control, power plant control, chemical plants, thermodynamics, etc.).

For perspective: software engineering and computing in general have evolved rapidly in the last 50 years. Today, no one would program in assembly when developing applications. In contrast, ladder logic and PLC programming have stayed the same.

5️⃣ Time and costs. Due to antiquated programming model of traditional PLCs, the development time and costs to develop the automation solution for a new industrial project are typically very high.

6️⃣ Scalability. Ladder logic and traditional PLCs do not support version control (such as git). As such, automation solutions need to be reprogrammed for each new project. This makes it hard for manufacturing companies to centralize their operational automation and scale their businesses.

Increase scalability with Formula Based Control

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The user interface allows linking a controllable variable (setpoint) to an Excel-like formula. In the formula, acquired sensor data can act as inputs and combine with built-in Excel functions / customized functions to give the desired control output in different operational scenarios. This low-code language is very expressive and enables the development of strategies ranging from simple to sophisticated.

The web interface allows the user to access the formula settings anytime with access to the internet. The formulas/control strategies can act as one as the plant system.

Track changes with Version History

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Version control allows the user to keep track of their work and helps them to easily explore the changes made to the control platform. The goal of this tool is to have a simple versioning system that can be used to track the different releases of the control platform.

This allows the user to directly compare different versions of the control platform and share it among collaborators. The changes to the control platform are stored online to benefit the user and their collaborators.

Identify logical defects with Test

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The Test option allows users to confirm the correctness of the control strategy and discover logical defects. This help user to produce more reliable control rules and increase the overall quality of Opera-based control system.

Case Study

Application in Greenhouse Industry

A demo application in the greenhouse
A demo application in the greenhouse

Application in Industrial Automation

One application of Ωpera to the industry is at a large biomass production facility in Vietnam. The system was originally designed and built with traditional PLC/HMI/SCADA technology, and provided baseline functionality. However, the facility owners were looking for a way to improve operations without getting into complex and expensive engineering cycles.

Screenshot of the deployment of dryer control for a biomass production facility. This screenshot of a low-code configuration setup for a dryer is a basic example of how Opera adds an additional layer of automation on top of the existing PLC by automating the dryer’s output temperature setpoint. The operators no longer need to manually tune this parameter, because they have applied their skills to the automation.
Screenshot of the deployment of dryer control for a biomass production facility. This screenshot of a low-code configuration setup for a dryer is a basic example of how Opera adds an additional layer of automation on top of the existing PLC by automating the dryer’s output temperature setpoint. The operators no longer need to manually tune this parameter, because they have applied their skills to the automation.

In the screenshot above, Opera’s excel-like language was used to achieve the necessary outcome humidity for the drying process. Using excel functions, we can form a proportional control for the humidity by adjusting the temperature setpoint and the calculated temperature setpoint can also be bounded for safety reasons. Changes to any version of this equation are visible to the collaborators.

Compared to the traditional process, Ωpera relieves the users from dealing with complex low-level PLC systems and enables focusing more on the control strategies.