Industry 4.0 and the new simulation modelling paradigm

Abstract

Background and Purpose: The aim of this paper is to present the influence of Industry 4.0 on the development of the new simulation modelling paradigm, embodied by the Digital Twin concept, and examine the adoption of the new paradigm via a multiple case study involving real-life R&D cases involving academia and industry. Design: We introduce the Industry 4.0 paradigm, presents its background, current state of development and its influence on the development of the simulation modelling paradigm. Further, we present the multiple case study methodology and examine several research and development projects involving automated industrial process modelling, presented in recent scientific publications and conclude with lessons learned. Results: We present the research problems and main results from five individual cases of adoption of the new simulation modelling paradigm. Main lesson learned is that while the new simulation modelling paradigm is being adopted by big companies and SMEs, there are significant differences depending on company size in problems that they face, and the methodologies and technologies they use to overcome the issues. Conclusion: While the examined cases indicate the acceptance of the new simulation modelling paradigm in the industrial and scientific communities, its adoption in academic environment requires close cooperation with industry partners and diversification of knowledge of researchers in order to build integrated, multi-level models of cyber-physical systems. As shown by the presented cases, lack of tools is not a problem, as the current generation of general purpose simulation modelling tools offers adequate integration options.

Keywords

simulation;modelling;automated modelling;Industry 4.0;Digital Twin;SME;multiple-case study;

Data

Language:	English
Year of publishing:	2017
Typology:	1.01 - Original Scientific Article
Organization:	UM FOV - Faculty of Organizational Sciences
UDC:	004.9
COBISS:	2048464659
ISSN:	1318-5454
Parent publication:	Organizacija
Views:	861
Downloads:	373
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary title:	Industrija 4.0 in nova paradigma simulacije in modeliranja
Secondary abstract:	Ozadje in namen: Namen tega prispevka je predstaviti vpliv Industrije 4.0 na razvoj nove paradigme modeliranja in simulacije, ki jo pooseblja koncept »Digital Twin«, in preučiti razširjanje nove paradigme v okviru študije več primerov raziskav in razvoja, ki vključujejo akademsko in industrijsko panogo. Zasnova: V prvem delu predstavimo paradigmo Industrija 4.0 in njeno ozadje, trenutno stanje razvoja in njen vpliv na razvoj nove paradigme modeliranja in simulacije. Nadalje predstavimo metodologijo študije primerov in več primerov raziskav in razvoja, ki vključujejo avtomatizirano modeliranje industrijskih procesov, predstavljenih v novejših znanstvenih publikacijah in zaključimo s predstavitvijo ugotovitev naše študije. Rezultati: Predstavimo raziskovalne probleme in glavne rezultate petih posameznih primerov implementacije nove paradigme modeliranja in simulacije. Naša glavna ugotovitev je, da medtem ko tako velika kot mala podjetja sledijo novi paradigmi modeliranja in simulacije, obstajajo velike razlike med njimi, in sicer pri težavah, s katerimi se soočajo, ter metodologiji in tehnologiji, ki ju uporabljajo za premagovanje teh težav. Zaključek: Čeprav obravnavani primeri kažejo, da industrija in znanstvena skupnost sprejemata novo paradigmo modeliranja in simulacije, njeno uveljavljanje v akademskem okolju zahteva tesno sodelovanje z industrijskimi partnerji in diverzifikacijo znanja raziskovalcev, da bi lahko razvijali integrirane, večplastne modele kiber-fizičnih sistemov. Kot je razvidno iz predstavljenih primerov, pomanjkanje orodij ni problem, saj že sedanja generacija splošnih simulacijskih orodij ponuja ustrezne možnosti integracije.
Secondary keywords:	simulacija;modeliranje;Industrija 4.0;digitalni dvojček;MSP;študija večih primerov;
URN:	URN:NBN:SI
Type (COBISS):	Scientific work
Pages:	str. 193-207
Volume:	ǂVol. ǂ50
Issue:	ǂno. ǂ3
Chronology:	aug. 2017
DOI:	10.1515/orga-2017-0017
ID:	10883861