After the first article in this series dealt with the general basic building blocks of control systems, the second article is dedicated to modeling the behavior of systems. The focus here is on differentiating between different types of modeling. The main part of the article introduces a special data-driven approach that has recently attracted growing scientific interest.
The automatic control of complex systems poses a growing theoretical and technical challenge. Regardless of whether these systems are biological or chemical reactors, wind turbines, power grids, airplanes or even manufacturing systems, the questions to be answered are always comparable. This upcoming series of articles will give an introduction to this interesting field and, in the first part, will cover the general basic components of control systems using a production example.
The bUnit library can be used to create unit tests for Blazor web front-ends. This allows you to create many tests that can be run quickly. Examples are used to present the first steps and the most important features of bUnit.
Blazor is a Microsoft framework for creating interactive web frontends with C#. Three deployment models are available for Blazor apps. The different architectures have a strong effect on the applications. This is explored by examples in industry.
In the so-called “Industry 4.0”, the productive times of machines and entire production lines are largely optimized in many industries. Therefore, the optimization of unproductive times, as machine downtime and reject production, are now being considered. Digital twins of production lines can be created using comprehensive data capture. Our author Marco Grafe discusses what is behind digital twins, what they are used for and whether we need them at all.
Production sites in high-wage countries demand highly automated and flexible production systems to remain competitive. In most cases, developing software for production systems requires using physical components under real conditions.
This blog post is the first in the new “Smart Manufacturing” series. This focuses on the Fischer Technology Learning Factory at the Görlitzer site of ZEISS Digital Innovation, which simulates a networked production environment and is controlled by a self-developed cloud application.
As the Industry 4.0 concepts mature, we will look at the Azure edition of Digital Twins. The definition of Digital Twins assumes the digital representation of real-world things’ (or people’s) properties, either in real time (for control and predictive maintenance) or in simulations to acquire and test behaviors before actual deployment. As such, Azure Digital Twins are closely related to Azure IoT services; however, they could do a bit more, as we will see in this blog article.