TNO-ESI, Managing complexity in cyber physical systems. The Netherlands are well known for their high tech industry, which is of major importance for its competitive position. In order to maintain this excellent position, we need continuous innovation. ESI, a TNO research center, specializes in the innovation of system engineering methodologies, methods, techniques and tools for modelling, design and engineering.

TNO-ESI. Trusted partner for the high-tech industry

Are you dealing with complex control software that is difficult to manage and develop correctly? Then Synthesis-Based Engineering (SBE) may help as it supports efficient and high-quality engineering of trustworthy control software at reduced costs and effort. As industrial systems are growing in complexity, traditional engineering of their control software is becoming increasingly challenging. Synthesis-based engineering helps to manage the complexity by automatically synthesising correct-by-construction control software based on specifications of 'what' the system should do rather than 'how' it should do it. This reduces development time and improves controller quality.

is a leader when it comes to high-tech manufacturing. This concerns complex systems such as industrial printers, machines that make sophisticated computer chips, medical systems for hospitals. To preserve that lead, and to ensure that Dutch competitiveness is given a boost, ESI as an open innovation knowledge center performs research and development into methods to improve and further develop such complex highly digitalised systems. ESI. Managing complexity.

Have you ever struggled to understand the behaviour of a piece of software? Have you ever seen a change in software cause a regression in a seemingly unrelated part of the system?
These are the kinds of challenges we address. Complex high-tech systems typically consist of many concurrently communicating software components. Understanding the current software behavior is a major challenge.

We consider three important aspects to validate:

1. functional requirements

2. architectural decomposition

3. performance indicators

To validate systems before realizing them, you need lightweight simulation that abstracts from as many details as possible.

The principles of how to reason from customer value to technical choices and vice versa.
This is generally very challenging as there are many steps between technical realization and emerging system properties, which are what customers actually experience.

How can DSL help you and your company to manage system complexity?

of the Digital Twin of Philips IGT systems

Prisma, an ESI project. A domain model-centric approach for the development of large-scale office lighting systems.

MBSA - an ESI (TNO) project. Model Based System Architecting. Systematic quantitative early architecting.

From virtual prototype to digital twin. In traditional model-driven development, models are used to guide system development. Models are used to analyze aspects of the system under development and identify the appropriate trade-off between different system qualities. To analyze a system’s behavior, simulation models are used; these virtual prototypes allow analysis and optimization of system behavior under realistic usage scenarios. The simulation models do not lose their value when the system has become operational. Then they can be used as digital twins to analyze the system’s performance. The simulation models can be used as a reference to identify anomalous or suboptimal system behavior.

AI-based System Health Assessment Scaled for Industrial Use Integrating human knowledge and AI techniques for better diagnosis and effective predictive maintenance of high tech systems.