Skip to main content
SpringerLink
Log in
Book cover

Simulation for Industry 4.0 pp 19–37Cite as

Industry 4.0, Digitisation in Manufacturing, and Simulation: A Review of the Literature

  • Chapter
  • First Online:

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

Simulation is perhaps the most widely used approach to design and analyze manufacturing systems than to any other application area. Industry 4.0, the latest industrial revolution , also involves the use of simulation and other related technologies in manufacturing. In this study, our main ambition is to provide readers with a comprehensive review of publications which lie within the intersection of Industry 4.0, digitization in manufacturing, and simulation. To achieve this, we follow a two-stage review methodology. Firstly, we review several academic databases and discuss the impact and application domain of a number of selected papers. Secondly, we perform a direct Google Scholar search and present numerical results on global trends for the related technologies between years 2011 and 2018. Our reviews show that simulation is in the heart of most of the technologies Industry 4.0 utilises or provides. Simulation has significant role in Industry 4.0 in terms of supporting development and deployment of its technologies such as Cyber-Physical System (CPS ), Augmented Reality (AR) , Virtual Reality (VR) , Smart Factory , Digital Twin , and Internet of Things (IoT) . Additionally in terms of management of these technologies, simulation helps design, operate and optimise processes in factories.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Tamas P, Illes B (2016) Process improvement trends for manufacturing systems in Industry 4.0. Acad J Manuf Eng 14(4):119–125

    Google Scholar 

  2. Mcginnis LF, Rose O (2017) History and perspective of simulation in manufacturing. In: Winter simulation conference, pp 385–397

    Google Scholar 

  3. Fowler JW, Rose O (2004) Grand challenges in modeling and simulation of complex manufacturing systems. Simulation 80(9):469–476

    Article  Google Scholar 

  4. Brettel M, Friederichsen N, Keller M, Rosenberg M (2014) How virtualization decentralization and network building change the manufacturing landscape: an Industry 4.0 perspective. Int J Inf Commun Eng 8(1):37–44

    Google Scholar 

  5. Qin J, Liu Y, Grosvenor R (2016) A categorical framework of manufacturing for industry 4.0 and beyond. In: Procedia CIRP, vol 52. http://doi.org/10.1016/j.procir.2016.08.005

    Article  Google Scholar 

  6. Roblek V, Meško M, Krapež A (2016) A complex view of industry 4.0. SAGE Open 6(2). http://doi.org/10.1177/2158244016653987

    Article  Google Scholar 

  7. Jain S, Lechevalier D (2016) Standards based generation of a virtual factory model C3. In: Proceedings—Winter Simulation Conference, Wintersim, pp 2762–2773. http://doi.org/10.1109/WSC.2016.7822313

  8. SISO (2012) SISO-STD-008-01-2012: standard for core manufacturing simulation data—XML representation. Simulation Interoperability Standards Organization, Orlando, FL

    Google Scholar 

  9. Hofmann E, Rüsch M (2017) Industry 4.0 and the current status as well as future prospects on logistics. Comput Ind 89:23–34. https://doi.org/10.1016/j.compind.2017.04.002

    Article  Google Scholar 

  10. Zhong RY, Xu X, Klotz E, Newman ST (2017) Intelligent manufacturing in the context of Industry 4.0: a review. Engineering 3(5):616–630. https://doi.org/10.1016/J.ENG.2017.05.015

    Article  Google Scholar 

  11. Strozzi F, Colicchia C, Creazza A, Noe C (2017) Literature review on the Smart Factory concept using bibliometric tools. Int J Prod Res 55(22):6572–6591. https://doi.org/10.1080/00207543.2017.1326643

    Article  Google Scholar 

  12. Vieira AAC, Dias LMS, Santos MY, Pereira GAB, Oliveira JA (2018) Setting an Industry 4.0 research and development agenda for simulation—a literature review. Int J Simul Modell 17(3):377–390

    Article  Google Scholar 

  13. Liao Y, Deschamps F, de Freitas Rocha Loures E, Ramos LFP (2017) Past, present and future of Industry 4.0—a systematic literature review and research agenda proposal. Int J Prod Res 55(12), 3609–3629. http://doi.org/10.1080/00207543.2017.1308576

    Article  Google Scholar 

  14. Jain S, Shao G, Shin SJ (2017) Manufacturing data analytics using a virtual factory representation. Int J Prod Res 55(18):5450–5464. https://doi.org/10.1080/00207543.2017.1321799

    Article  Google Scholar 

  15. Oztemel E, Gursev S (2018) Literature review of Industry 4.0 and related technologies. J Intell Manuf. http://doi.org/10.1007/s10845-018-1433-8

  16. Jahangirian M, Eldabi T, Naseer A, Stergioulas LK, Young T (2010) Simulation in manufacturing and business: a review. Eur J Oper Res 203(1):1–13

    Article  Google Scholar 

  17. Lee J, Bagheri B, Kao H-A (2015) A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufact. Lett. 3:18–23. https://doi.org/10.1016/j.mfglet.2014.12.001

    Article  Google Scholar 

  18. Zhou K, Liu T, Zhou L (2015) Industry 4.0: towards future industrial opportunities and challenges. In: 2015 12th International conference on fuzzy systems and knowledge discovery (FSKD), pp 2147–2152. http://doi.org/10.1109/FSKD.2015.7382284

  19. Saldivar AAF, Li Y, Chen WN, Zhan ZH, Zhang J, Chen LY (2015) Industry 4.0 with cyber-physical integration: a design and manufacture perspective. In: 2015 21st International conference on automation and computing (ICAC), pp 1–6. http://doi.org/10.1109/IConAC.2015.7313954

  20. Scheifele S, Reidel O, Pritschow G (2017) Engineering of machine tools and manufacturing systems using cyberphysical systems. In: Winter simulation conference, pp 1503–1514

    Google Scholar 

  21. Mueller E, Chen X-L, Riedel R (2017) Challenges and requirements for the application of industry 4.0: a special insight with the usage of cyber-physical system. Chin J Mech Eng 30(5):1050–1057. https://doi.org/10.1007/s10033-017-0164-7

    Article  Google Scholar 

  22. Longo F, Nicoletti L, Padovano A (2017) Smart operators in industry 4.0: a human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Comput Ind Eng 113:144–159. https://doi.org/10.1016/J.CIE.2017.09.016

    Article  Google Scholar 

  23. Syberfeldt A, Holm M, Danielsson O, Wang L, Brewster RL (2016) Support systems on the industrial shop-floors of the future—operators’ perspective on augmented reality. Procedia CIRP 44:108–113. https://doi.org/10.1016/j.procir.2016.02.017

    Article  Google Scholar 

  24. Gorecky D, Schmitt M, Loskyll M, Zühlke D (2014) Human-machine-interaction in the industry 4.0 era. In: 2014 12th IEEE international conference on industrial informatics (INDIN), pp 289–294. http://doi.org/10.1109/INDIN.2014.6945523

  25. Herter J, Ovtcharova J (2016) A model based visualization framework for cross discipline collaboration in industry 4.0 scenarios. Procedia CIRP 57:398–403. https://doi.org/10.1016/j.procir.2016.11.069

    Article  Google Scholar 

  26. Karlsson I, Bernedixen J, Ng AHC, Leif P (2017) Combining augmented reality and simulation-based optimization for decision support in manufacturing. In: Wintersim, pp 3988–3999

    Google Scholar 

  27. Nunes ML, Pereira AC, Alves AC (2017) Smart products development approaches for Industry 4.0. Procedia Manuf 13:1215–1222. https://doi.org/10.1016/j.promfg.2017.09.035

    Article  Google Scholar 

  28. Akpan IJ, Shanker M (2017) The confirmed realities and myths about the benefits and costs of 3D visualization and virtual reality in discrete event modeling and simulation: A descriptive meta-analysis of evidence from research and practice. Comput Ind Eng 112:197–211

    Article  Google Scholar 

  29. Jain S, Lechevalier D, Woo J, Shin S (2015) Toward a virtual factory prototype. In: Proceedings of the 2015 winter simulation conference, pp 2207–2218

    Google Scholar 

  30. Shao G, Jain S, Shin S-J (2014) Data analytics using simulation for smart manufacturing. In: Tolk A, Diallo SD, Ryzhov IO, Yilmaz L, Buckley S, Miller JA, Proceedings of the 2014 winter simulation conference. Institute of Electrical and Electronics Engineers, Inc, Piscataway, New Jersey, pp 2192–2203

    Google Scholar 

  31. Jain S, Sigurðardóttir S, Lindskog E, Andersson J, Johansson B (2013) Multi-resolution modeling for supply chain sustainability analysis. In: Pasupathy R, Kim S-H, Tolk A, Hill R, Kuhl ME (eds) Proceedings of the 2013 winter simulation conference. Institute of Electrical and Electronics Engineers, Inc, Piscataway, NJ, pp 1996–2007

    Google Scholar 

  32. Weyer S, Schmitt M, Ohmer M, Gorecky D (2015) Towards Industry 4.0—standardization as the crucial challenge for highly modular, multi-vendor production systems. IFAC-PapersOnLine 48(3):579–584. https://doi.org/10.1016/j.ifacol.2015.06.143

    Article  Google Scholar 

  33. Theorin A, Bengtsson K, Provost J, Lieder M, Johnsson C, Lundholm T, Lennartson B (2017) An event-driven manufacturing information system architecture for Industry 4.0. Int J Prod Res 55(5):1297–1311. https://doi.org/10.1080/00207543.2016.1201604

    Article  Google Scholar 

  34. Srewil Y, Scherer RJ (2017) Construction objects recognition in framework of CPS. In: Proceedings of the 2017 winter simulation conference, pp 2472–2483

    Google Scholar 

  35. Rodič B (2017) Industry 4.0 and the new simulation modelling paradigm. Organizacija 50(3), 193–207. http://doi.org/10.1515/orga-2017-0017

    Article  Google Scholar 

  36. Timm IJ, Lorig F (2015) Logistics 4.0—a challenge for simulation. In: Proceedings of the 2015 winter simulation conference, pp 3118–3119

    Google Scholar 

  37. Dallasega P, Rauch E, Linder C (2018) Industry 4.0 as an enabler of proximity for construction supply chains: a systematic literature review. Comput Ind 99:205–225. https://doi.org/10.1016/J.COMPIND.2018.03.039

    Article  Google Scholar 

  38. Tjahjono B, Esplugues C, Ares E, Pelaez G (2017) What does Industry 4.0 mean to supply chain? Procedia Manuf 13:1175–1182. https://doi.org/10.1016/j.promfg.2017.09.191

    Article  Google Scholar 

  39. Sanders A, Elangeswaran C, Wulfsberg J (2016) Industry 4.0 implies lean manufacturing: research activities in industry 4.0 function as enablers for lean manufacturing. J Ind Eng Manage 9(3):811. https://doi.org/10.3926/jiem.1940

    Article  Google Scholar 

  40. Wagner T, Herrmann C, Thiede S (2017) Industry 4.0 impacts on lean production systems. Procedia CIRP 63:125–131. https://doi.org/10.1016/j.procir.2017.02.041

    Article  Google Scholar 

  41. Zúñiga ER, Moris MU, Syberfeldt A (2017) Integrating simulation-based optimization, lean, and the concepts of Industry 4.0. In: Winter simulation conference, pp 3828–3839

    Google Scholar 

  42. Kolberg D, Zühlke D (2015) Lean automation enabled by industry 4.0 technologies. In: IFAC-PapersOnLine, vol 28. http://doi.org/10.1016/j.ifacol.2015.06.359

    Article  Google Scholar 

  43. De Man JC, Strandhagen JO (2017) An Industry 4.0 research agenda for sustainable business models. Procedia CIRP 63:721–726. https://doi.org/10.1016/j.procir.2017.03.315

    Article  Google Scholar 

  44. Erol S, Jäger A, Hold P, Ott K, Sihn W (2016) Tangible Industry 4.0: a scenario-based approach to learning for the future of production. Procedia CIRP 54:13–18. https://doi.org/10.1016/j.procir.2016.03.162

    Article  Google Scholar 

  45. Faller C, Feldmüller D (2015) Industry 4.0 learning factory for regional SMEs. Procedia CIRP 32:88–91. https://doi.org/10.1016/j.procir.2015.02.117

    Article  Google Scholar 

  46. Prinz C, Morlock F, Freith S, Kreggenfeld N, Kreimeier D, Kuhlenkötter B (2016) Learning factory modules for smart factories in Industrie 4.0. Procedia CIRP 54:113–118. https://doi.org/10.1016/j.procir.2016.05.105

    Article  Google Scholar 

  47. Wang S, Wan J, Zhang D, Li D, Zhang C (2016) Towards smart factory for Industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput Netw 101:158–168. https://doi.org/10.1016/j.comnet.2015.12.017

    Article  Google Scholar 

  48. Zaayman G, Innamorato A (2017) The application of SIMIO scheduling in Industry 4.0. In: Winter simulation conference, pp 4425–4434

    Google Scholar 

  49. Ivanov D, Dolgui A, Sokolov B, Werner F, Ivanova M (2016) A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry. Int J Prod Res 54(2):386–402. https://doi.org/10.1080/00207543.2014.999958

    Article  Google Scholar 

  50. Oesterreich TD, Teuteberg F (2016) Understanding the implications of digitisation and automation in the context of Industry 4.0: a triangulation approach and elements of a research agenda for the construction industry. In: Computers in industry. http://doi.org/10.1016/j.compind.2016.09.006

    Article  Google Scholar 

  51. Lee J, Kao H-A, Yang S (2014) Service innovation and smart analytics for industry 4.0 and big data environment. Procedia CIRP 16:3–8. https://doi.org/10.1016/j.procir.2014.02.001

    Article  Google Scholar 

  52. Liu Y, Xu X (2016) Industry 4.0 and cloud manufacturing: a comparative analysis. J Manuf Sci Eng 139(3):34701–34708. https://doi.org/10.1115/1.4034667

    Article  Google Scholar 

  53. Pereira AC, Romero F (2017) A review of the meanings and the implications of the industry 4.0 concept. Procedia Manuf 13:1206–1214. https://doi.org/10.1016/j.promfg.2017.09.032

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Barbaros Naval Science and Engineering Institute, National Defense University, Turkish Naval Academy, Tuzla, Istanbul, Turkey

    Murat M. Gunal

  2. Industrial Engineering Department, National Defense University, Tuzla, Istanbul, Turkey

    Mumtaz Karatas

  3. Industrial Engineering Department, Bahcesehir University, Istanbul, Turkey

    Mumtaz Karatas

Authors
  1. Murat M. Gunal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mumtaz Karatas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Murat M. Gunal .

Editor information

Editors and Affiliations

  1. Barbaros Naval Science and Engineering Institute, National Defense University Tuzla, Istanbul, Turkey

    Murat M. Gunal

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gunal, M.M., Karatas, M. (2019). Industry 4.0, Digitisation in Manufacturing, and Simulation: A Review of the Literature. In: Gunal, M. (eds) Simulation for Industry 4.0. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-030-04137-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-04137-3_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04136-6

  • Online ISBN: 978-3-030-04137-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation