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The fit of Industry 4.0 applications in manufacturing logistics: a multiple case study

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Abstract

The fourth industrial revolution, Industry 4.0, is expected to cause disruptive changes in industrial production. It is driven by rapid technological developments and the need for manufacturing companies to make themselves independent of high labor costs. Industry 4.0 concerns several aspects of industrial production, including manufacturing logistics, business models and products and services. The applications of Industry 4.0 have been vastly outlined. However, the fit of Industry 4.0 applications in different production environments is not clear. The purpose of this paper is to identify and investigate the Industry 4.0 technologies that are applicable to manufacturing logistics, and how the production environment influences the applicability of these technologies. This is done through a multiple case study of four Norwegian manufacturing companies. The findings from the study indicate that the applicability of Industry 4.0 in manufacturing logistics is dependent on the production environment. Companies with a low degree of production repetitiveness see less potential in applying Industry 4.0 technologies in manufacturing logistics, while companies with a highly repetitive production see a higher potential.

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References

  1. Kagermann H, Helbig J, Hellinger A et al (2013) Securing the future of German manufacturing industry recommendations for implementing the strategic initiative Industry 4.0. Final report of the Industrie 4.0 working group. Forschungsunion, pp 1–84

  2. Jonsson P, Mattsson SA (2003) The implications of fit between planning environments and manufacturing planning and control methods. Int J Oper Prod Manag 23(8):872–900

    Article  Google Scholar 

  3. MacCarthy BL, Fernandes FCF (2000) A multi-dimensional classification of production systems for the design and selection of production planning and control systems. Prod Plan Control 11(5):481–496

    Article  Google Scholar 

  4. Lasi H, Fettke P, Kemper HG et al (2014) Industry 4.0. business & information. Syst Eng 6(4):239–242

    Google Scholar 

  5. Hermann M, Pentek T, Otto B (2016) Design principles for Industrie 4.0 scenarios. In: The 49th Hawaii international conference on system sciences (HICSS) IEEE, pp 3928–3937

  6. Wang S, Wan J, Li D et al (2016) Implementing smart factory of Industrie 4.0: an outlook. Int J Distrib Sensor Netw 12:3159805

    Article  Google Scholar 

  7. Brettel M, Friederichsen N, Keller M et al (2014) How virtualization, decentralization and network building change the manufacturing landscape: an Industry 4.0 perspective. Int J Mech Ind Sci Eng 8(1):37–44

    Google Scholar 

  8. European Commission (2004) Manufuture: a vision for 2020, assuring the future of manufacturing in Europe

  9. Stock T, Seliger G (2016) Opportunities of sustainable manufacturing in Industry 4.0. Proc CIRP 40:536–541

    Article  Google Scholar 

  10. Lin HW, Nagalingam SV, Kuik SS et al (2012) Design of a global decision support system for a manufacturing SME: towards participating in collaborative manufacturing. Int J Prod Econ 136(1):1–12

    Article  Google Scholar 

  11. Lee EA (2008) Cyber physical systems: design challenges. In: 11th IEEE international symposium on object oriented real-time distributed computing (ISORC), IEEE, pp 363–369

  12. Lee J, Bagheri B, Kao HA (2015) A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett 3:18–23

    Article  Google Scholar 

  13. Slack N, Chambers S, Johnston R (2010) Operations management. Pearson Education, London

    Google Scholar 

  14. Anderl R (2014) Industrie 4.0-advanced engineering of smart products and smart production. In: 19th international seminar on high technology, technological innovations in the product development, Piracicaba, Brazil

  15. Lucke D, Constantinescu C, Westkämper E (2008) Smart factory-a step towards the next generation of manufacturing. In: Mitsuishi M, Ueda K, Kimura F (eds) Manufacturing systems and technologies for the new frontier, Springer: London, pp 115–118

  16. Radziwon A, Bilberg A, Bogers M et al (2014) The smart factory: exploring adaptive and flexible manufacturing solutions. Proc Eng 69:1184–1190

    Article  Google Scholar 

  17. Yoon JS, Shin SJ, Suh SH (2012) A conceptual framework for the ubiquitous factory. Int J Prod Res 50(8):2174–2189

    Article  Google Scholar 

  18. Dopico M, Gomez A, De la Fuente D et al (2016) A vision of Industry 4.0 from an artificial intelligence point of view. In: International conference on artificial intelligence (ICAI). The steering committee of the world congress in computer science, computer engineering and applied computing (WorldComp), pp 407–413

  19. Li BH, Hou BC, Yu WT et al (2017) Applications of artificial intelligence in intelligent manufacturing: a review. Front Inf Technol Electr Eng 18(1):86–96

    Article  Google Scholar 

  20. McAfee A, Brynjolfsson E, Davenport TH et al (2012) Big data. The management revolution. Harvard Bus Rev 90(10):61–67

    Google Scholar 

  21. Sagiroglu S, Sinanc D (2013) Big data: a review. In: International conference on collaboration technologies and systems (CTS). IEEE, pp 42–47

  22. Rüßmann M, Lorenz M, Gerbert P et al (2015) Industry 4.0: the future of productivity and growth in manufacturing industries. Boston Consulting Group, Boston, p 14

    Google Scholar 

  23. Reif R, Walch D (2008) Augmented & virtual reality applications in the field of logistics. Vis Comput 24(11):987–994

    Article  Google Scholar 

  24. Wang X, Ong S, Nee C (2016) A comprehensive survey of augmented reality assembly research. Adv Manuf 4(1):1–22

    Article  Google Scholar 

  25. McFarlane D, Sarma S, Chirn JL et al (2003) Auto ID systems and intelligent manufacturing control. Eng Appl Artif Intell 16(4):365–376

    Article  Google Scholar 

  26. Ilie-Zudor E, Kemény Z, Van Blommestein F et al (2011) A survey of applications and requirements of unique identification systems and RFID techniques. Comput Ind 62(3):227–252

    Article  Google Scholar 

  27. Xiao Y, Yu S, Wu K et al (2007) Radio frequency identification: technologies, applications, and research issues. Wirel Commun Mobile Comput 7(4):457–472

    Article  Google Scholar 

  28. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

    Article  MATH  Google Scholar 

  29. Shrouf F, Ordieres J, Miragliotta G (2014) Smart factories in Industry 4.0: a review of the concept and of energy management approached in production based on the Internet of things paradigm. In: International conference on industrial engineering and engineering management (IEEM) IEEE, pp 697–701

  30. Arica E, Powell DJ (2014) A framework for ICT-enabled real-time production planning and control. Adv Manuf 2(2):158–164

    Article  Google Scholar 

  31. Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput Integr Manuf 28(1):75–86

    Article  Google Scholar 

  32. Zhang L, Luo Y, Tao F et al (2014) Cloud manufacturing: a new manufacturing paradigm. Enterp Inf Syst 8(2):167–187

    Article  Google Scholar 

  33. Li BH, Zhang L, Wang SL et al (2010) Cloud manufacturing: a new service-oriented networked manufacturing model. Comput Integr Manuf Syst 16(1):1–7

    Google Scholar 

  34. OECD (2017) The next production revolution: implications for governments and business. OECD Publishing, Paris

  35. Rüßmann M, Lorenz M, Gerbert P et al (2015) Industry 4.0: the future of productivity and growth in manufacturing industries. Boston Consulting Group, Boston, p 9

    Google Scholar 

  36. Holmström J, Partanen J, Tuomi J et al (2010) Rapid manufacturing in the spare parts supply chain: alternative approaches to capacity deployment. J Manuf Technol Manag 21(6):687–697

    Article  Google Scholar 

  37. Khajavi SH, Partanen J, Holmström J (2014) Additive manufacturing in the spare parts supply chain. Comput Ind 65(1):50–63

    Article  Google Scholar 

  38. Lödding H (2012) Handbook of manufacturing control: fundamentals, description, configuration. Springer Science & Business Media, Berlin

    Google Scholar 

  39. Olhager J, Rudberg M (2002) Linking manufacturing strategy decisions on process choice with manufacturing planning and control systems. Int J Prod Res 40(10):2335–2351

    Article  MATH  Google Scholar 

  40. Schönsleben P (2007) Integral logistics management: operations and supply chain management in comprehensive value-added networks. CRC Press, Boca Raton

    Book  Google Scholar 

  41. Newman WR, Sridharan V (1995) Linking manufacturing planning and control to the manufacturing environment. Integr Manuf Syst 6(4):36–42

    Article  Google Scholar 

  42. Ptak CA, Schragenheim E (2003) ERP: tools, techniques, and applications for integrating the supply chain. CRC Press, Boca Raton

    Book  Google Scholar 

  43. APICS online dictionary

  44. Stevenson M, Hendry LC, Kingsman BG (2005) A review of production planning and control: the applicability of key concepts to the make-to-order industry. Int J Prod Res 43(5):869–898

    Article  Google Scholar 

  45. Fernandes FCF, Godinho Filho M (2011) Production control systems: literature review, classification, and insights regarding practical application. Afr J Bus Manag 5(14):5573–5582

    Google Scholar 

  46. Yin RK (2013) Case study research: design and methods. Sage publications, Thousand Oaks

    Google Scholar 

  47. Forza C (2002) Survey research in operations management: a process-based perspective. Int J Oper Prod Manag 22(2):152–194

    Article  Google Scholar 

  48. Kitzinger J (1995) Qualitative research. Introducing focus groups. BMJ 311(7000):299–302

    Article  Google Scholar 

  49. Wortmann JC (1992) Production management systems for one-of-a-kind products. Comput Ind 19(1):79–88

    Article  Google Scholar 

  50. Gosling J, Naim MM (2009) Engineer-to-order supply chain management: a literature review and research agenda. Int J Prod Econ 122(2):741–754

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the support from the ongoing research project Manufacturing Network 4.0, funded by the Research Council of Norway. The project partners’ support of the research presented in this paper has been crucial. Moreover, the authors are grateful for the case company representatives’ contribution to the data acquisition process and their support of the research.

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Correspondence to Jo Wessel Strandhagen.

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Strandhagen, J.W., Alfnes, E., Strandhagen, J.O. et al. The fit of Industry 4.0 applications in manufacturing logistics: a multiple case study. Adv. Manuf. 5, 344–358 (2017). https://doi.org/10.1007/s40436-017-0200-y

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  • DOI: https://doi.org/10.1007/s40436-017-0200-y

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