Gregor Hoepfner, I. Nachmann, T. Zerwas, J. Berroth, J. Kohl, C. Guist, Bernhard Rumpe, G. Jacobs
{"title":"基于整体功能模型的机电信息物理系统设计方法研究","authors":"Gregor Hoepfner, I. Nachmann, T. Zerwas, J. Berroth, J. Kohl, C. Guist, Bernhard Rumpe, G. Jacobs","doi":"10.1115/1.4056807","DOIUrl":null,"url":null,"abstract":"\n Engineering Cyber-Physical Systems (CPS) is complex and time-consuming due to the heterogeneity of the involved engineering domains and the high number of physical and logical interactions of its subsystems. Model-based Systems Engineering (MSBE) approaches tackle the complexity of developing CPS by formally and explicitly modeling subsystems and their interactions. Newer approaches also integrate domain-specific models and modeling languages to cover different aspects of CPS. However, MBSE approaches are currently not fully applicable for CPS development since they do not integrate formal models for physical and mechanical behavior to an extent that allows to seamlessly link mechanical models to the digital models and reuse them. In this paper, we discuss the challenges arising from the missing integration of physics into MBSE and introduce a model-based methodology capable of integrating physical functions and effects into an MBSE approach on a level where detailed physical effects are considered. Our approach offers a fully virtual, model-based development methodology covering the whole development process for the development of CPS. Evaluating this methodology on a real automotive use case demonstrates benefits regarding virtual development and functional testing of CPS. It shows potentials regarding automated development and continuous integration of the whole CPS including all domains. As an outlook of this paper, we discuss potential further research topics extending our development workflow.","PeriodicalId":54856,"journal":{"name":"Journal of Computing and Information Science in Engineering","volume":"7 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards a Holistic and Functional Model-Based Design Method for Mechatronic Cyber-Physical Systems\",\"authors\":\"Gregor Hoepfner, I. Nachmann, T. Zerwas, J. Berroth, J. Kohl, C. Guist, Bernhard Rumpe, G. Jacobs\",\"doi\":\"10.1115/1.4056807\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Engineering Cyber-Physical Systems (CPS) is complex and time-consuming due to the heterogeneity of the involved engineering domains and the high number of physical and logical interactions of its subsystems. Model-based Systems Engineering (MSBE) approaches tackle the complexity of developing CPS by formally and explicitly modeling subsystems and their interactions. Newer approaches also integrate domain-specific models and modeling languages to cover different aspects of CPS. However, MBSE approaches are currently not fully applicable for CPS development since they do not integrate formal models for physical and mechanical behavior to an extent that allows to seamlessly link mechanical models to the digital models and reuse them. In this paper, we discuss the challenges arising from the missing integration of physics into MBSE and introduce a model-based methodology capable of integrating physical functions and effects into an MBSE approach on a level where detailed physical effects are considered. Our approach offers a fully virtual, model-based development methodology covering the whole development process for the development of CPS. Evaluating this methodology on a real automotive use case demonstrates benefits regarding virtual development and functional testing of CPS. It shows potentials regarding automated development and continuous integration of the whole CPS including all domains. 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Towards a Holistic and Functional Model-Based Design Method for Mechatronic Cyber-Physical Systems
Engineering Cyber-Physical Systems (CPS) is complex and time-consuming due to the heterogeneity of the involved engineering domains and the high number of physical and logical interactions of its subsystems. Model-based Systems Engineering (MSBE) approaches tackle the complexity of developing CPS by formally and explicitly modeling subsystems and their interactions. Newer approaches also integrate domain-specific models and modeling languages to cover different aspects of CPS. However, MBSE approaches are currently not fully applicable for CPS development since they do not integrate formal models for physical and mechanical behavior to an extent that allows to seamlessly link mechanical models to the digital models and reuse them. In this paper, we discuss the challenges arising from the missing integration of physics into MBSE and introduce a model-based methodology capable of integrating physical functions and effects into an MBSE approach on a level where detailed physical effects are considered. Our approach offers a fully virtual, model-based development methodology covering the whole development process for the development of CPS. Evaluating this methodology on a real automotive use case demonstrates benefits regarding virtual development and functional testing of CPS. It shows potentials regarding automated development and continuous integration of the whole CPS including all domains. As an outlook of this paper, we discuss potential further research topics extending our development workflow.
期刊介绍:
The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications.
Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping