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

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.

Keywords

Industry 4.0 / Manufacturing logistics / Production planning and control / Production environment

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. The implications of fit between planning environments and manufacturing planning and control methods. Int J Oper Prod Manag, 2003, 23(8): 872-900.

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

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

[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. Implementing smart factory of Industrie 4.0: an outlook. Int J Distrib Sensor Netw, 2016, 12: 3159805.

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

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

[9] Stock T, Seliger G. Opportunities of sustainable manufacturing in Industry 4.0. Proc CIRP, 2016, 40: 536-541.

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

[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. A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett, 2015, 3: 18-23.

[13] Slack N, Chambers S, Johnston R. Operations management, 2010, London: Pearson Education

[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. The smart factory: exploring adaptive and flexible manufacturing solutions. Proc Eng, 2014, 69: 1184-1190.

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

[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. Applications of artificial intelligence in intelligent manufacturing: a review. Front Inf Technol Electr Eng, 2017, 18(1): 86-96.

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

[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. Industry 4.0: the future of productivity and growth in manufacturing industries, 2015, Boston: Boston Consulting Group 14

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

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

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

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

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

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

[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. A framework for ICT-enabled real-time production planning and control. Adv Manuf, 2014, 2(2): 158-164.

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

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

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

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

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

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

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

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

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

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

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

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

[43] APICS online dictionary

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

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

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

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

[48] Kitzinger J. Qualitative research. Introducing focus groups. BMJ, 1995, 311(7000): 299-302.

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

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