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ABB Demonstrator



You can find details about the ABB demonstrator in the following documents:

The rest of this page provides a small overview of the ABB demonstrator.


The ABB demonstrator represents a system from the area of process control systems. Such systems (Fig. 1) control and supervise industrial processes (e.g., power generation, oil refineries, chemical plants, etc.). They visualize complex time-dependent processes involving different materials and allow human intervention. Sensor data from the physical process (e.g., temperature, flow, pressure, etc.) can be collected and analyzed. Actuators in the process (e.g., pumps, valves, heaters, etc.) can be handled automatically or controlled by human operators from remote operator workplaces. Furthermore, these systems usually contain alarm management, user management, site visualization, andengineering functionality.

Fig. 1: Industrial Process Control System

Demonstrator Setup

The installation of the demonstrator resides in the so-called “Process Automation Lab” (PAL) of ABB’s German Corporate Research Center (Fig. 2). Besides the computing nodes, the lab contains several physical devices, such as tanks, sensors, valves, pumps, etc., which are arranged as a small, exemplary industrial process. The process can be supervised from an operator workplace  that visualizes the running process schematically and allows for human intervention. The following movie clip shows the demonstrator running.

Fig. 2: ABB Process Automation Lab used as Q-ImPrESS Demonstrator

Q-ImPrESS application

ABB used the Q-ImPrESS method and tools on the demonstrator for reverse engineering, performance and reliability prediction, and trade-off analyses.

Reverse Engineering

The tools SiSSy and SoMoX were applied on the C++ code of the process control system. They extracted the G-AST structure (SiSSy) and identify software components and interfaces on this structure using different metrics (SoMoX), such as coupling and cohesion. The usefulness of the extracted components and connectors model was evaluated by comparing it against existing architecture documentation. Details can be found in the Demonstrator Evaluation Report.

Fig. 3: Reverse Engineering Results based on open OPC code

Manual Modeling

Besides the efforts for reverse engineering, ABB manually built a Q-ImPrESS model of the demonstrator in parallel. The manually built model corresponds to the architecture documented in D7.1. It abstracts the system in a goal-oriented way to incorporate both the performance and reliability measurements and to evaluate the proposed evolution scenarios.

Fig. 4: Manually built Q-ImPrESS model of the ABB demonstrator

Performance Prediction

The manually built model together with manual additions were annotated with performance properties. To obtain these annotation (e.g., service execution times for certain steps in the scenarios described above), the implementation of the process control system was instrumented and executed according to the described scenarios. Details are provided in the Demonstrator Evaluation Report.

Fig. 5: Performance predictions for the ABB demonstrator

Reliability Prediction

After manually enhancing the manually built model, component failure rates and transition probabilities were added to enable a reliability prediction. The sensitivity analyses in Fig. 6 shows the subsystems most critical for the overall reliability of the system.

Fig. 6: Reliability prediction results for the ABB demonstrator


Domain Example: Waste Management Plant in Malmø running process control system

Domain Example

Demonstrator Setup: Experimental lab in Ladenburg, Germany

Demonstrator Setup

Applying Q-ImPrESS 1: reverse engineering tools

Applying Q-ImPrESS 1

Applying Q-ImPrESS 2: performance prediction tools