Abstract
In this paper, we try to find the best strategy for Industry 4.0 implementation. For this aim, we determine the aggregated strategies for applying this concept and criteria that are used to select the best strategy. With the criteria set out in this context, basic strategies should be applied as a priority, considering for example human resources, work organization and design, information systems, and effective use of resources, and the development of new business models and standardization are specified. Since this selection is a process in which many different measures need to be considered, multi-criteria decision-making (MCDM) methods based on AHP-VIKOR methodologies have been applied to find the best strategy. Fuzzy set theory was beneficial for coping with uncertainties in the selection process.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barbosa J, Leitão P, Trentesaux D, Colombo AW, Karnouskosk S (2017) Cross benefits from cyber-physical systems and intelligent products for future smart industries. In: IEEE international conference on industrial informatics (INDIN) 7819214, pp 504–509
Beloglazov A, Abawajy J, Buyya R (2012) Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener Comput Syst 28(5):755–768
Buckley JJ (1985) Fuzzy hierarchical analysis. Fuzzy Sets Syst 17(3):233–247
Chang WY, Wu SJ (2016) Investigated information data of CNC machine tool for established productivity of industry 4.0. In: 2016 5th IIAI international congress on advanced applied informatics (IIAI-AAI). IEEE, pp 1088–1092
Chen JK, Chen IS (2010) Using a novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education. Expert Syst Appl 37(3):1981–1990
Fleischmann H, Kohl J, Franke J (2017) Improving maintenance processes with distributed monitoring systems. In: IEEE international conference on industrial informatics (INDIN) 7819189, pp 377–382
Forstner L, Dümmler M (2014) Integrierte Wertschöpfungsnetzwerke-Chancen und Potenziale durch Industrie 4.0. e and i. Elektrotechnik und Informationstechnik 131(7):199–201
Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabási AL (2007) The human disease network. Proc Natl Acad Sci 104(21):8685–8690
Gorecky D, Khamis M, Mura K (2017) Introduction and establishment of virtual training in the factory of the future. Int J Comput Integr Manuf 30(1):182–190
Grundstein S, Freitag M, Scholz-Reiter B (2017) A new method for autonomous control of complex job shops—integrating order release, sequencing and capacity control to meet due dates. J Manuf Syst 42:11–28
Gul M, Celik E, Aydin N, Gumus AT, Guneri AF (2016) A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89
Gupta P, Mehlawat MK, Grover N (2016) Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Inf Sci 370:184–203
Hsieh TY, Lu ST, Tzeng GH (2004) Fuzzy MCDM approach for planning and design tenders selection in public office buildings. Int J Project Manag 22(7):573–584
Kahraman C, Süder A, Kaya İ (2014) Fuzzy multicriteria evaluation of health research investments. Technol Econ Dev Econ 20(2):210–226
Kaya T, Kahraman C (2010) Multicriteria renewable energy planning using an integrated fuzzy VIKOR and AHP methodology: the case of Istanbul. Energy 35(6):2517–2527
Kaya T, Kahraman C (2011) Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology. Expert Syst Appl 38(6):6577–6585
Kaya I, Kahraman C (2014) A comparison of fuzzy multicriteria decision making methods for intelligent building assessment. J Civ Eng Manag 20(1):59–69
Klein S, Pluim JP, Staring M, Viergever MA (2009) Adaptive stochastic gradient descent optimisation for image registration. Int J Comput Vis 81(3):227
Kolberg D, Knobloch J, Zühlke D (2016) Towards a lean automation interface for workstations. Int J Prod Res. https://doi.org/10.1080/00207543.2016.1223384
Oesterreich T-D, 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. Comput Ind 83:121–139
Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455
Rennung F, Luminosu CT, Draghici A (2016) Service provision in the framework of Industry 4.0. Procedia Soc Behav Sci 221:372–377
Rezaie K, Ramiyani SS, Shirkouhi SN, Badizadeh A (2014) Evaluating performance of Iranian cement firms using an integrated fuzzy AHP-VIKOR method. Appl Math Model 38:5033–5046
Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York
Sepulcre M, Gozalvez J, Coll-Perales B (2016) Multipath QoS-driven routing protocol for industrial wireless networks. J Netw Comput Appl 74:121–132
Tuzkaya G, Gülsün B, Kahraman C, Özgen D (2010) An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application. Expert Syst Appl 37(4):2853–2863
Tzeng GH, Huang JJ (2011) Multiple attribute decision making: methods and applications. CRC press
Veza I. Mladineo M, Gjeldum N (2015) Managing innovative production network of smart factories. IFAC-Papers OnLine 48(3):555–560
Vinodh S, Prasanna M, Prakash NH (2014) Integrated fuzzy AHP–TOPSIS for selecting the best plastic recycling method: a case study. Appl Math Model 38(19):4662–4672
Wu Y, Chen K, Zeng B, Xu H, Yang Y (2016) Supplier selection in nuclear power industry with extended VIKOR method under linguistic information. Appl Soft Comput 48:444–457
Zadeh L (1965) Fuzzy sets. Inf Control 8(1965):338–353
Zare M, Pahl C, Rahnama H, Nilashi M, Mardani A, Ibrahim O, Ahmadi H (2016) Multi-criteria decision making approach in E-learning: a systematic review and classification. Appl Soft Comput 45:108–128
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Erdogan, M., Ozkan, B., Karasan, A., Kaya, I. (2018). Selecting the Best Strategy for Industry 4.0 Applications with a Case Study. In: Calisir, F., Camgoz Akdag, H. (eds) Industrial Engineering in the Industry 4.0 Era. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-71225-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-71225-3_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-71224-6
Online ISBN: 978-3-319-71225-3
eBook Packages: EngineeringEngineering (R0)