Skip to main content

2019 | OriginalPaper | Buchkapitel

Symbiotic Simulation System (S3) for Industry 4.0

verfasst von : Bhakti Stephan Onggo

Erschienen in: Simulation for Industry 4.0

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter discusses symbiotic simulation system, a simulation system that is designed to support online short-term operations management decision. The prevalence of real-time data and the advances in Industry 4.0 technologies have made the real-world implementation of the vision of using simulation to support real-time decision making a reality. The main contributions of this chapter are to provide a review of similar concepts in simulation, to provide the architecture of symbiotic simulation system at the conceptual level, to classify the types of symbiotic simulation applications, and to highlights research challenges in symbiotic simulation.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Rogers P, Gordon RJ (1993) Simulation for real-time decision making in manufacturing systems. In: Proceedings of the winter simulation conference, pp 866–874 Rogers P, Gordon RJ (1993) Simulation for real-time decision making in manufacturing systems. In: Proceedings of the winter simulation conference, pp 866–874
2.
Zurück zum Zitat Davis W (1998) On-line simulation: Need and evolving research requirements. In: Banks J (ed) Handbook of simulation. Wiley, New York, pp 465–516CrossRef Davis W (1998) On-line simulation: Need and evolving research requirements. In: Banks J (ed) Handbook of simulation. Wiley, New York, pp 465–516CrossRef
3.
Zurück zum Zitat Rowson JA (1994) Hardware/software co-simulation. In: Proceedings of the design automation conference, pp 439–440 Rowson JA (1994) Hardware/software co-simulation. In: Proceedings of the design automation conference, pp 439–440
4.
Zurück zum Zitat Bohlmann S, Szczerbicka H, Klinger V (2010) Co-simulation in large scale environments using the HPNS framework. In: Proceedings of the 2010 conference on grand challenges in modeling & simulation, pp 211–218 Bohlmann S, Szczerbicka H, Klinger V (2010) Co-simulation in large scale environments using the HPNS framework. In: Proceedings of the 2010 conference on grand challenges in modeling & simulation, pp 211–218
5.
Zurück zum Zitat Darema F (2004) Dynamic data driven applications systems: a new paradigm for application simulations and measurements. In: Bubak M, van Albada GD, Sloot PMA, Dongarra J (eds) Computational science—ICCS 2004. ICCS 2004. Lecture notes in computer science, vol 3038. Springer, Berlin, HeidelbergCrossRef Darema F (2004) Dynamic data driven applications systems: a new paradigm for application simulations and measurements. In: Bubak M, van Albada GD, Sloot PMA, Dongarra J (eds) Computational science—ICCS 2004. ICCS 2004. Lecture notes in computer science, vol 3038. Springer, Berlin, HeidelbergCrossRef
6.
Zurück zum Zitat Fujimoto R, Lunceford D, Page E, Uhrmacher AM (2002) Grand challenges for modeling and simulation: Dagstuhl report. Technical report 350, Schloss Dagstuhl. Seminar No 02351 Fujimoto R, Lunceford D, Page E, Uhrmacher AM (2002) Grand challenges for modeling and simulation: Dagstuhl report. Technical report 350, Schloss Dagstuhl. Seminar No 02351
7.
Zurück zum Zitat Aydt H, Turner SJ, Cai W, Low MYH (2008) Symbiotic simulation systems: an extended definition motivated by symbiosis in biology. In: Proceedings of the 22nd workshop on principles of advanced and distributed simulation, pp 109–116 Aydt H, Turner SJ, Cai W, Low MYH (2008) Symbiotic simulation systems: an extended definition motivated by symbiosis in biology. In: Proceedings of the 22nd workshop on principles of advanced and distributed simulation, pp 109–116
8.
Zurück zum Zitat Szozda N (2017) Industry 4.0 and its impact on the functioning of supply chains. LogForum 13(4):401–414 Szozda N (2017) Industry 4.0 and its impact on the functioning of supply chains. LogForum 13(4):401–414
9.
Zurück zum Zitat Xu LD, Xu EL, Li L (2018) Industry 4.0: state of the art and future trends. Int J Prod Res 56(8):2941–2962 Xu LD, Xu EL, Li L (2018) Industry 4.0: state of the art and future trends. Int J Prod Res 56(8):2941–2962
10.
Zurück zum Zitat Yin Y, Stecke KE, Li D-n (2018) The evolution of production systems from Industry 2.0 through Industry 4.0. Int J Prod Res 56(1–2):848–861CrossRef Yin Y, Stecke KE, Li D-n (2018) The evolution of production systems from Industry 2.0 through Industry 4.0. Int J Prod Res 56(1–2):848–861CrossRef
11.
Zurück zum Zitat Monostori L (2014) Cyber-physical production systems: roots, expectations and R&D challenges. Proc CIRP 17:9–13CrossRef Monostori L (2014) Cyber-physical production systems: roots, expectations and R&D challenges. Proc CIRP 17:9–13CrossRef
16.
Zurück zum Zitat Onggo BS, Mustafee N, Juan AA, Molloy O, Smart A (2018) Symbiotic simulation system: hybrid systems model meets big data analytics. In: Proceedings of the 2018 winter simulation conference, pp 1358–1369 Onggo BS, Mustafee N, Juan AA, Molloy O, Smart A (2018) Symbiotic simulation system: hybrid systems model meets big data analytics. In: Proceedings of the 2018 winter simulation conference, pp 1358–1369
17.
Zurück zum Zitat Fu MC (2015) Handbook of simulation optimization, 1st edn. Springer, New York, NYMATH Fu MC (2015) Handbook of simulation optimization, 1st edn. Springer, New York, NYMATH
18.
Zurück zum Zitat Juan AA, Faulin J, Grasman SE, Rabe M, Figueira G (2015) A review of simheuristics: extending metaheuristics to deal with stochastic combinatorial optimization problems. Oper Res Perspect 2:62–72MathSciNetCrossRef Juan AA, Faulin J, Grasman SE, Rabe M, Figueira G (2015) A review of simheuristics: extending metaheuristics to deal with stochastic combinatorial optimization problems. Oper Res Perspect 2:62–72MathSciNetCrossRef
19.
Zurück zum Zitat Rhodes-Leader L, Onggo BS, Worthington DJ, Nelson BL (2018b) Multi-fidelity simulation optimisation for airline disruption management. In: Proceedings of the 2018 simulation workshop, pp 2179–2190 Rhodes-Leader L, Onggo BS, Worthington DJ, Nelson BL (2018b) Multi-fidelity simulation optimisation for airline disruption management. In: Proceedings of the 2018 simulation workshop, pp 2179–2190
20.
Zurück zum Zitat Panadero J, Juan AA, Mozos JM, Corlu CG, Onggo BS (2018) Agent-based simheuristics: extending simulation-optimization algorithms via distributed and parallel computing. In: Proceedings of the 2018 winter simulation conference, pp 869–880 Panadero J, Juan AA, Mozos JM, Corlu CG, Onggo BS (2018) Agent-based simheuristics: extending simulation-optimization algorithms via distributed and parallel computing. In: Proceedings of the 2018 winter simulation conference, pp 869–880
21.
Zurück zum Zitat Onggo BS, Karatas M (2016) Test-Driven simulation modelling: a case study using agent-based maritime search-operation simulation. Eur J Oper Res 254(2):517–531CrossRef Onggo BS, Karatas M (2016) Test-Driven simulation modelling: a case study using agent-based maritime search-operation simulation. Eur J Oper Res 254(2):517–531CrossRef
22.
Zurück zum Zitat Moeuf A, Pellerin R, Lamouri S, Tamayo-Giraldo S, Barbaray R (2017) The industrial management of SMEs in the era of industry 4.0. Int J Prod Res 56(3):1118–1136CrossRef Moeuf A, Pellerin R, Lamouri S, Tamayo-Giraldo S, Barbaray R (2017) The industrial management of SMEs in the era of industry 4.0. Int J Prod Res 56(3):1118–1136CrossRef
23.
Zurück zum Zitat Katz D, Manivannan S (1993) Exception management on a shop floor using online simulation. In: Proceedings of the winter simulation conference, pp 888–896 Katz D, Manivannan S (1993) Exception management on a shop floor using online simulation. In: Proceedings of the winter simulation conference, pp 888–896
24.
Zurück zum Zitat Oakley D, Onggo BSS, and Worthington DJ (2019) Symbiotic Simulation for the Operational Management of Inpatient Beds: Model Development and Validation using Δ-Method. Health Care Management Science. In press. Oakley D, Onggo BSS, and Worthington DJ (2019) Symbiotic Simulation for the Operational Management of Inpatient Beds: Model Development and Validation using Δ-Method. Health Care Management Science. In press.
25.
Zurück zum Zitat Patrikalakis NM, McCarthy JJ, Robinson AR, Schmidt H, Evange-linos C, Haley PJ, Lalis S, Lermusiaux PFJ, Tian R, Leslie WG, Cho W (2004) Towards a dynamic data driven system for rapid adaptive interdisciplinary ocean forecasting. Massachusetts Institute of Technology, Cambridge, MA, USA. Retrieved from http://czms.mit.edu/poseidon/new1/publications/kluwer.pdf. Accessed on 03 Oct 2018 Patrikalakis NM, McCarthy JJ, Robinson AR, Schmidt H, Evange-linos C, Haley PJ, Lalis S, Lermusiaux PFJ, Tian R, Leslie WG, Cho W (2004) Towards a dynamic data driven system for rapid adaptive interdisciplinary ocean forecasting. Massachusetts Institute of Technology, Cambridge, MA, USA. Retrieved from http://​czms.​mit.​edu/​poseidon/​new1/​publications/​kluwer.​pdf. Accessed on 03 Oct 2018
26.
Zurück zum Zitat Rhodes-Leader L, Onggo BS, Worthington DJ, Nelson BL (2018a). Airline disruption recovery using symbiotic simulation and multi-fidelity modelling. In: Proceedings of the 2018 simulation workshop, pp 146–155 Rhodes-Leader L, Onggo BS, Worthington DJ, Nelson BL (2018a). Airline disruption recovery using symbiotic simulation and multi-fidelity modelling. In: Proceedings of the 2018 simulation workshop, pp 146–155
27.
Zurück zum Zitat Parashar M, Klie H, Ctalynrek U, Kurc T, Bangerth W, Matossian V, Saltz J, Wheeler MF (2004) Application of grid–enabled technologies for solving optimization problems in data-driven reservoir studies. Future Gener Comput Syst 21:19–26CrossRef Parashar M, Klie H, Ctalynrek U, Kurc T, Bangerth W, Matossian V, Saltz J, Wheeler MF (2004) Application of grid–enabled technologies for solving optimization problems in data-driven reservoir studies. Future Gener Comput Syst 21:19–26CrossRef
28.
Zurück zum Zitat Kotiadis K (2016) Towards self-adaptive discrete event simulation (SADES). In: Proceedings of the operational research society simulation workshop, pp 181–191 Kotiadis K (2016) Towards self-adaptive discrete event simulation (SADES). In: Proceedings of the operational research society simulation workshop, pp 181–191
Metadaten
Titel
Symbiotic Simulation System (S3) for Industry 4.0
verfasst von
Bhakti Stephan Onggo
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-04137-3_10

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.