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Industry 4.0 - Potentials for Creating Smart Products: Empirical Research Results

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Business Information Systems (BIS 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 208))

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Abstract

Industry 4.0 combines the strengths of traditional industries with cutting edge internet technologies. It embraces a set of technologies enabling smart products integrated into intertwined digital and physical processes. Therefore, many companies face the challenge to assess the diversity of developments and concepts summarized under the term industry 4.0. The paper presents the result of a study on the potential of industry 4.0. The use of current technologies like Big Data or cloud-computing are drivers for the individual potential of use of Industry 4.0. Furthermore mass customization as well as the use of idle data and production time improvement are strong influence factors to the potential of Industry 4.0. On the other hand business process complexity has a negative influence.

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References

  1. Blanchet, M., Rinn, T., Thaden, G., Thieulloy, G.: Industry 4.0. The new industrial revolution. How Europe will succeed. Hg V Roland Berg. Strategy Consult. GmbH Münch. Abgerufen Am 1105 2014 Unter (2014). http://www.Rolandberger.Com/med.0403/Pdf

  2. Evans, P.C., Annunziata, M.: Industrial internet: pushing the boundaries of minds and machines. Gen. Electr. 21 (2012)

    Google Scholar 

  3. Brynjolfsson, E., McAfee, A.: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company, New York (2014)

    Google Scholar 

  4. Brynjolfsson, E., Hofmann, P., Jordan, J.: Cloud computing and electricity: beyond the utility model. Commun. ACM 53, 32–34 (2010)

    Article  Google Scholar 

  5. Dorst, W., EV, B.: Fabrik-und Produktionsprozesse der Industrie 4.0 im Jahr 2020. IM Fachz. Für Inf. Manag. Consult. Nr. 27, 34–37 (2012)

    Google Scholar 

  6. Beckert, S.: Empire of Cotton: A Global History. Knopf, New York (2014)

    Google Scholar 

  7. Carr, N.G.: The Big Switch: Rewiring the World, from Edison to Google. WW Norton & Company, New York (2008)

    Google Scholar 

  8. Kiebitz, F.: Nikola Tesla zum fünfundsiebzigsten Geburtstage. Naturwissenschaften 19, 665–666 (1931)

    Article  Google Scholar 

  9. Siemens, W.: Ueber telegraphische Leitungen und Apparate. Wissenschaftliche und Technische Arbeiten, pp. 15–29. Springer, Heidelberg (1889)

    Google Scholar 

  10. Bauernhansl, T.: Industry 4.0: Challenges and limitations in the production. Keynote. ATKearney Fact (2013)

    Google Scholar 

  11. Messe, H.: “Industrie 4.0” muss sich erst beweisen - Industrie - Unternehmen – Handelsblatt. http://www.handelsblatt.com/unternehmen/industrie/hannover-messe-industrie-4-0-muss-sich-erst-beweisen/8044930.html

  12. Rajkumar, R., Lee, I.: NSF workshop on cyber-physical systems (2006)

    Google Scholar 

  13. Lee, E.A.: Cyber physical systems: design challenges. In: 2008 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC), pp. 363–369. IEEE (2008)

    Google Scholar 

  14. Ashton, K.: That “internet of things” thing. RFiD J. 22, 97–114 (2009)

    Google Scholar 

  15. Cardoso, J., Voigt, K., Winkler, M.: Service engineering for the internet of services. Enterp. Inf. Syst. 13(1), 15–27 (2009)

    Google Scholar 

  16. Lee, J., Kao, H.-A., Yang, S.: Service innovation and smart analytics for industry 4.0 and big data environment. Procedia CIRP 16, 3–8 (2014)

    Article  Google Scholar 

  17. Walsh, G., Möhring, M., Koot, C., Schaarschmidt, M.: Preventive product returns management systems-a review and model. In: Proceedings of the 21th European Conference on Information Systems (ECIS), Tel Aviv, Israel (2014)

    Google Scholar 

  18. Miche, M., Schreiber, D., Hartmann, M.: Core services for smart products. 3rd European Workshop on Smart Products, pp. 1–4 (2009)

    Google Scholar 

  19. Mühlhäuser, M.: Smart products: an introduction. In: Mühlhäuser, M., Ferscha, A., Aitenbichler, E. (eds.) Constructing Ambient Intelligence, pp. 158–164. Springer, Berlin Heidelberg (2008)

    Chapter  Google Scholar 

  20. Nurcan, S., Schmidt, R.: Introduction to the first international workshop on business process management and social software (BPMS2 2008). In: Ardagna, D., Mecella, M., Yang, J., Aalst, W., Mylopoulos, J., Rosemann, M., Shaw, M.J., Szyperski, C. (eds.) Business Process Management Workshops, pp. 647–648. Springer, Berlin Heidelberg (2009)

    Chapter  Google Scholar 

  21. LaValle, S., Lesser, E., Shockley, R., Hopkins, M.S., Kruschwitz, N.: Big data, analytics and the path from insights to value. MIT Sloan Manag. Rev. 52, 21–32 (2011)

    Google Scholar 

  22. White, T.: Hadoop: The Definitive Guide. O’Reilly & Associates, Sebastopol (2015)

    Google Scholar 

  23. Forman, G.H., Zahorjan, J.: The challenges of mobile computing. Computer 27, 38–47 (1994)

    Article  Google Scholar 

  24. Mell, P., Grance, T.: The NIST Definition of Cloud Computing. http://csrc.nist.gov/groups/SNS/cloud-computing/

  25. Schmidt, R., Möhring, M.: Strategic alignment of cloud-based architectures for big data. In: Proceedings of the 17th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW), pp. 136–143. Vancouver, Canada (2013)

    Google Scholar 

  26. Schmidt, R.: Industrie 4.0 - revolution oder evolution. Wirtsch. Ostwürtt 2013, 4–7 (2013)

    Google Scholar 

  27. Ang, C.L.: Technical planning of factory data communications systems. Comput. Ind. 9, 93–105 (1987)

    Article  Google Scholar 

  28. How big data can improve manufacturing. McKinsey & Company. http://www.mckinsey.com/insights/operations/how_big_data_can_improve_manufacturing

  29. Abbott, D.: Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst. Wiley, New York (2014)

    Google Scholar 

  30. De Treville, S., Shapiro, R.D., Hameri, A.-P.: From supply chain to demand chain: the role of lead time reduction in improving demand chain performance. J. Oper. Manag. 21, 613–627 (2004)

    Article  Google Scholar 

  31. Bauer, W., Schlund, S., Marrenbach, D., Ganschar, O.: Industrie 4.0 - Volkswirtschaftliches Potenzial für Deutschland. BITKOM / Fraunhofer (2014)

    Google Scholar 

  32. Cardoso, J., Mendling, J., Neumann, G., Reijers, H.A.: A discourse on complexity of process models. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 117–128. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  33. Groover Jr., M.P.: Automation, Production Systems and Computer-Aided Manufacturing. Prentice Hall PTR, New Jersey (1980)

    Google Scholar 

  34. Groover, M.P.: Automation, Production Systems, and Computer-Integrated Manufacturing. Prentice Hall Press, New Jersey (2007)

    Google Scholar 

  35. Gilmore, J.H., Pine 2nd, B.J.: The four faces of mass customization. Harv. Bus. Rev. 75, 91–101 (1996)

    Google Scholar 

  36. Schmidt, R., Möhring, M., Maier, S., Pietsch, J., Härting, R.-C.: Big data as strategic enabler - insights from central european enterprises. In: Abramowicz, W., Kokkinaki, A. (eds.) BIS 2014. LNBIP, vol. 176, pp. 50–60. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  37. Scheer, A.-W.: Industrie 4.0. Satzweiss.com (2013)

    Google Scholar 

  38. Babbie, E.: The practice of social research. Cengage Learning, Boston (2012)

    Google Scholar 

  39. Team, T.L.: project: LimeSurvey - the free and open source survey software tool! http://www.limesurvey.org/de/start

  40. Wong, K.K.-K.: Partial least squares structural equation modeling (PLS-SEM) techniques using smartPLS. Mark. Bull. 24, 1–32 (2013)

    Google Scholar 

  41. Ringle, C.M., Wende, S., Will, A.: SmartPLS 2.0 (beta). Hamburg, Germany (2012)

    Google Scholar 

  42. Hooper, D., Coughlan, J., Mullen, M.: Structural equation modelling: guidelines for determining model fit. Articles. 2 (2008)

    Google Scholar 

  43. Chin, W.W.: The partial least squares approach to structural equation modeling. Mod. Methods Bus. Res. 295, 295–336 (1998)

    Google Scholar 

  44. Williamson, O.E.: The economics of organization: the transaction cost approach. Am. J. Sociol. 87(3), 548–577 (1981)

    Article  Google Scholar 

  45. Wigand, R.T., Picot, A., Reichwald, R.: Information, Organization and Management: Expanding Markets and Corporate Boundaries. Wiley, Chichester (1997)

    Google Scholar 

  46. Shulman, J.D., Coughlan, A.T., Savaskan, R.C.: Optimal reverse channel structure for consumer product returns. Mark. Sci. 29, 1071–1085 (2010)

    Article  Google Scholar 

  47. Christensen, C.: The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Harvard Business Review Press, Boston (2013)

    Google Scholar 

  48. Santos, J.R.A.: Cronbach’s alpha: a tool for assessing the reliability of scales. J. Ext. 37, 1–5 (1999)

    Google Scholar 

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Authors and Affiliations

  1. Business Information Systems, Aalen University, Beethovenstr. 1, Aalen, 73430, Germany

    Michael Möhring, Ralf-Christian Härting, Christopher Reichstein, Pascal Neumaier & Philip Jozinović

  2. Business Information Systems, Munich University of Applied Sciences, Lothstr. 64, Munich, 80335, Germany

    Rainer Schmidt

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  1. Rainer Schmidt
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  2. Michael Möhring
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  3. Ralf-Christian Härting
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  4. Christopher Reichstein
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  5. Pascal Neumaier
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  6. Philip Jozinović
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Correspondence to Rainer Schmidt .

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  1. Department of Information Systems, Poznań University of Economics, Poznań, Poland

    Witold Abramowicz

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Schmidt, R., Möhring, M., Härting, RC., Reichstein, C., Neumaier, P., Jozinović, P. (2015). Industry 4.0 - Potentials for Creating Smart Products: Empirical Research Results. In: Abramowicz, W. (eds) Business Information Systems. BIS 2015. Lecture Notes in Business Information Processing, vol 208. Springer, Cham. https://doi.org/10.1007/978-3-319-19027-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-19027-3_2

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