Early-stage analysis of cyber-physical production systems through collaborative modelling
This paper demonstrates the flexible methodology of modelling cyber-physical systems (CPSs) using the INTO-CPS technology through co-simulation based on Functional Mock-up Units (FMUs). It explores a novel method with two main co-simulation phases: homogeneous and heterogeneous. In the first phase,...
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Veröffentlicht in: | Software and systems modeling 2020-05, Vol.19 (3), p.581-600 |
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creator | Neghina, Mihai Zamfirescu, Constantin-Bala Pierce, Ken |
description | This paper demonstrates the flexible methodology of modelling cyber-physical systems (CPSs) using the INTO-CPS technology through co-simulation based on Functional Mock-up Units (FMUs). It explores a novel method with two main co-simulation phases: homogeneous and heterogeneous. In the first phase, high-level, abstract FMUs are produced for all subsystems using a single discrete-event formalism (the VDM-RT language and Overture tool). This approach permits early co-simulation of system-level behaviours and serves as a basis for dialogue between subsystem teams and agreement on interfaces. During the second phase, model refinements of subsystems are gradually introduced, using various simulation tools capable of exporting FMUs. This heterogeneous phase permits high-fidelity models of all subsystems to be produced in appropriate formalisms. This paper describes the use of this methodology to develop a USB stick production line, representing a smart system of systems. The experiments are performed under the assumption that the orders are received in a Gaussian or Uniform distribution. The focus is on the homogeneous co-simulation phase, for which the method demonstrates two important roles: first, the homogeneous phase identifies the right interaction protocols (signals) among the various subsystems, and second, the conceptual (system-level) parameters identified before the heterogeneous co-simulation phase reduce the huge size of the design space and create stable constraints, later reflected in the physical implementation. |
doi_str_mv | 10.1007/s10270-019-00753-w |
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The focus is on the homogeneous co-simulation phase, for which the method demonstrates two important roles: first, the homogeneous phase identifies the right interaction protocols (signals) among the various subsystems, and second, the conceptual (system-level) parameters identified before the heterogeneous co-simulation phase reduce the huge size of the design space and create stable constraints, later reflected in the physical implementation.</description><subject>Compilers</subject><subject>Computer Science</subject><subject>Computer simulation</subject><subject>Cyber-physical systems</subject><subject>Data buses</subject><subject>Formalism</subject><subject>Gaussian distribution</subject><subject>Information Systems Applications (incl.Internet)</subject><subject>Interpreters</subject><subject>IT in Business</subject><subject>Modelling</subject><subject>Parameter identification</subject><subject>Programming Languages</subject><subject>Programming Techniques</subject><subject>Simulation</subject><subject>Software Engineering</subject><subject>Software Engineering/Programming and Operating Systems</subject><subject>Subsystems</subject><subject>System of systems</subject><subject>Theme Section Paper</subject><issn>1619-1366</issn><issn>1619-1374</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kEtLAzEUhYMoWGr_gKuA62gek2SylFIfUHCjC1chzSTTkXRSkxnL_HujFd25uvfAOYd7PwAuCb4mGMubTDCVGGGiUJGcocMJmBFRJGGyOv3dhTgHi5y7DcYVVaoSYgZeVyaFCeXBtA6a3oQpdxlGD-20cQntt0VbE-A-xWa0Qxd7mKc8uF2GwzbFsd1CG0Mwm5jM0H04uIuNC6Hr2wtw5k3IbvEz5-DlbvW8fEDrp_vH5e0aWSbkgBRtSFVTRZlSjZSiZkwyxSnllBHmLbe2cdRXdUMUr7xj5XruFONe-po3ns3B1bG3nPg-ujzotzim8knWlKqKCsI5Ky56dNkUc07O633qdiZNmmD9RVEfKepCUX9T1IcSYsdQLua-demv-p_UJzCqdig</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Neghina, Mihai</creator><creator>Zamfirescu, Constantin-Bala</creator><creator>Pierce, Ken</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7XB</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20200501</creationdate><title>Early-stage analysis of cyber-physical production systems through collaborative modelling</title><author>Neghina, Mihai ; 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It explores a novel method with two main co-simulation phases: homogeneous and heterogeneous. In the first phase, high-level, abstract FMUs are produced for all subsystems using a single discrete-event formalism (the VDM-RT language and Overture tool). This approach permits early co-simulation of system-level behaviours and serves as a basis for dialogue between subsystem teams and agreement on interfaces. During the second phase, model refinements of subsystems are gradually introduced, using various simulation tools capable of exporting FMUs. This heterogeneous phase permits high-fidelity models of all subsystems to be produced in appropriate formalisms. This paper describes the use of this methodology to develop a USB stick production line, representing a smart system of systems. The experiments are performed under the assumption that the orders are received in a Gaussian or Uniform distribution. The focus is on the homogeneous co-simulation phase, for which the method demonstrates two important roles: first, the homogeneous phase identifies the right interaction protocols (signals) among the various subsystems, and second, the conceptual (system-level) parameters identified before the heterogeneous co-simulation phase reduce the huge size of the design space and create stable constraints, later reflected in the physical implementation.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s10270-019-00753-w</doi><tpages>20</tpages></addata></record> |
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subjects | Compilers Computer Science Computer simulation Cyber-physical systems Data buses Formalism Gaussian distribution Information Systems Applications (incl.Internet) Interpreters IT in Business Modelling Parameter identification Programming Languages Programming Techniques Simulation Software Engineering Software Engineering/Programming and Operating Systems Subsystems System of systems Theme Section Paper |
title | Early-stage analysis of cyber-physical production systems through collaborative modelling |
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