Approach for an Integrated Model-based Design of Intelligent Dynamic Systems Using Solution and System Knowledge. (2016)

• Record Type: Journal Article
• Authors: Oestersötebier, Felix; Abrishamchian, Farisoroosh; Lankeit, Christopher; Just, Viktor; Trächtler, Ansgar
• Is Part Of: Procedia technology. Volume 26(2016)
• Page Start: 436
• Page End: 446
• Publication Date: 2016
• Subjects: model-based design -- discipline-spanning coordination -- technical requirements -- Multifunctional Model Client; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.08.056
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: In the design process of intelligent technical systems, simultaneous and concurrent engineering is generally encouraged on the one hand, while on the other hand cooperation and coordination of the involved disciplines is required. In multidisciplinary system development, 1) a common understanding of the objective is of vital importance for the system's success and 2) the combined artifacts of the different disciplines need to be analyzed before the system is built. In this paper, we address these issues and present an approach for an integrated model-based design process, which facilitates the use of solution and system knowledge and reduces the huge effort for building and maintaining the required simulation models. To illustrate this, we use the application example of two cooperating delta robots. The system knowledge constitutes the basis for concurrent design in the involved disciplines, all of which provide and expand certain aspects. To analyze the domain-specific dynamic behavior of the subsystems and their components, multiple dynamic behavior models are developed in different levels of detail and domains. However, in order to analyze the complex interactions and dependencies between them, integrated models of the whole system are needed, which fit the varying modeling objectives and analysis goals. Certainly, the manual process of building up such models and maintaining consistency between all the artifacts entails great effort. To improve this, we present the concept of a Multifunctional Model Client (MMC).