Roland Rosen

Digital Twin—The Simulation Aspect

The vision of the Digital Twin itself refers to a comprehensive physical and functional description of a component, product or system, which includes more or less all information which could be useful in all—the current and subsequent—lifecycle phases. In this chapter we focus on the simulation aspects of the Digital Twin. Today, modelling and simulation is a standard process in system development, e.g. to support design tasks or to validate system properties. During operation and for service first simulation-based solutions are realized for optimized operations and failure prediction. In this sense, simulation merges the physical and virtual world in all life cycle phases. Current practice already enables the users (designer, SW/HW developers, test engineers, operators, maintenance personnel, etc) to master the complexity of mechatronic systems.

Modeling and Numerical Simulation of Pipe Flow Problems in Water Supply Systems

In this chapter the simulation of a water supply system on a mesoscale abstraction level is considered. The water network consists of storage tanks, pipes, pumps and valves. It is operated by the characteristics of the water supplier, the consumer and the pumps. For all network elements the modeling equations are given. They include mass and momentum conservation for pressurized pipe flow. For their numerical solution the method of lines is proposed. The discretization in space is based on a finite volume approach together with a local Lax-Friedrich splitting and central WENO reconstruction. Boundary and coupling conditions are implemented as algebraic equations. This leads to a system of differential-algebraic equations in time which is solved by a special Rosenbrock method. The paper ends with some typical simulation results of the network.

Referenzentwicklungsprozess für cybertronische Produkte und Produktionssysteme

Durch die stetige Digitalisierung in der Industrie entwickeln sich mechatronische Systeme weiter zu cybertronischen Systemen (CTS). Durch diese Evolution mussen die konventionellen Entwicklungs- bzw. Planungsprozesse fur Produkte und Produktionssysteme auf den Prufstand gestellt werden. Die hohe Komplexitat von CTS fuhrt zu einem Wandel von einer dokumentenbasierten Vorgehensweise, hin zu einem modellbasierten Ansatz fur die Entwicklung von cybertronischen Produkten (CTP) bzw. fur die Planung von cybertronischen Produktionssystemen (CTPS). Weiterhin fuhren die spezifischen Charakteristika von CTP und CTPS zu neuen Herausforderungen im Entwicklungsprozess. Aus diesem Grund wurde im Rahmen des Forschungsprojektes mecPro2 ein Referenzentwicklungsprozess fur die Entwicklung von CTP und CTPS erarbeitet. Nachdem in Kapitel 6 die Vorgehensweise zur Erarbeitung des Entwicklungsprozesses und dessen grundsatzlicher Aufbau vorgestellt wurden, wird in diesem Kapitel der mecPro2-spezifische Referenzentwicklungsprozess fur cybertronische Produkte und Produktionssysteme naher beschrieben und anhand von Beispielen illustriert.

Co-simulation techniques in assistance systems for process control

The penetration of production systems and common infrastructure with information and communication technologies (ICT) creates new systems, called Smart Grids in energy or Industry 4.0 in production. This offers unprecedented opportunities for flexible and customized production and distribution. However, these complex and interconnected systems need new approaches for operation. Assistance system similar to those known from the automotive sector will support operators in their task to provide a safe, efficient and undisturbed operation of production systems. The paper supports, that more complex functionalities of assistance systems are based on simulation. This paper discusses the question how well co-simulation approaches are suited for this task. Co-simulation is the joint simulation of independent simulators each representing a component or subsystem of the overall system. The modularity of co-simulation reflects the modularity of production systems. It is possible to compose a simulation by using existing models. It is easy to adapt co-simulation to different configurations of production systems or changes in topology. The inherent flexibility of co-simulation makes it possible to cover broad range of requirements regarding, among others, simulation speed and precision. Co-simulation further allows to include models as “black boxes” which can be used to protect intellectual property on the modeled components. However, co-simulation always comes with additional costs for communication. Data exchange between models sets upper bounds for simulation speed. This limits the application of co-simulation: If requirements on calculation speed are very high other approaches like hybrid simulations are more suitable. For very precise simulations parallel simulation may be appropriate.

Modellbildung und Simulation

Simulation ist eine in Wissenschaft und Industrie haufig genutzte und bewahrte Methode, die bei der Entwicklung von Systemen, wie z. B. cybertronischen Produkten und Produktionssystemen, eingesetzt wird. In diesem Kapitel wird aufgezeigt, welche veranderte Rolle die Simulation im Entwicklungsprozess in Zukunft einnehmen wird. Dies adressiert bereits in fruhen Entwicklungsphasen eine engere Verknupfung zwischen Systemmodellen und der Simulation sowie die Verbindung zwischen der Produktentwicklung und der Produktionssystementwicklung.

A Lightweight Approach to Manage Engineering Parameters in Mechatronic Design Processes

In mechatronic design processes the exchange of information between stakeholders from different disciplines is essential to enable simultaneous engineering and a successful integration of domain specific subsystems. Although there is a comprehensive range of methodologies and tools to support collaboration, intentions to implement a central data management platform covering all stakeholders often do not succeed. Reasons are the heterogeneous model landscape, the variety of stand-alone authoring tools, departments’, disciplines’ or companies’ boundaries and a lack of flexibility of established solutions regarding the support of unpredictable and quickly changing design processes. This paper focuses on the management of individual parameters and parameter instances (values) within a multi-disciplinary development team. The presented lightweight approach can extend existing methods and data management infrastructure by adding functionalities to provide access to individual parameters using a dedicated database. The procedure is shown by the example of a technical mechanism.

Optimal Control of Sewer Networks Problem Description

This chapter gives an overview of optimal control of sewer networks with dynamic process models. After introducing the method of model predictive control (MPC) and its requirements for optimization and process modeling a focus is set on practical applications and the industrial viewpoint. An up-to-date sewer management system is introduced and used to illustrate industrial requirements and the mathematical challenges involved in it.