Login Register Cart 0
Generic placeholder image

Recent Advances in Computer Science and Communications

Editor-in-Chief

ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

Back
Journal Home About Journal Editorial Board Current Issue Volumes/Issues
Subscribe
Research Article

Assessment of Risks for Successful Implementation of Industry 4.0

Author(s): Rimalini Gadekar*, Bijan Sarkar and Ashish Gadekar

Volume 15, Issue 1, 2022

Published on: 28 September, 2020

Page: [111 - 130] Pages: 20

DOI: 10.2174/2666255813999200928215915

Price: $65

Abstract

Purpose: The transformation happening globally, though referred to by different names and nomenclatures, the overall objective to inspire digitalization and smart practices by reducing human intervention and enhancing machine intelligence to take on the global manufacturing and production to another level of excellence is a proven fact now. However, earlier research has been found lacking in the strategic approach to evaluate and analyze the I4.0 adoption-related risks for its implementation. This ultimately deprived organizations of a multitude of the benefits of I4.0 adoption. This research proposes a systematic methodology for understanding and evaluating the most evident risks in the context of I4.0 implementation.

Design/Methodology/Approach: The research is mainly based on the inputs from experts/consultants along with robust literature review and researcher’s experience in the area of risk handling. The MCDM methods used for investigation and assessment are Fuzzy AHP and Fuzzy TOPSIS. The outcomes of the study are further validated through sensitivity analysis and real-world scenario.

Results: Technical and Information Technology (IT) risks are found to be on the top of the priority list, which needs urgent attention while embarking on I4.0 adoption in the industry, and the most important criteria, which needed urgent attention was Information Security. The paper has also developed the ‘Industry 4.0 Risks Iceberg model’ and systematically categorized the challenges into 5 dimensions for easy assessment and analysis.

Practical Implications: This systematic and holistic study of the I4.0 associated risks can be used to find the most critical and crucial risks based on which the strategies and policies may be modified to harness the best of I4.0. This will not only ensure the returns on investment but also will build trust in the system. The research would be very beneficial to managers, academicians, researchers, and technocrats who would be involved in I4.0 implementation.

Keywords: Industry 4.0, risks management, sustainability, sensitivity analysis, fuzzy AHP, fuzzy TOPSIS, multi-criteria decision- making method (MCDM).

Graphical Abstract

[1]
M. Ben-Daya, E. Hassini, and Z. Bahroun, "Internet of things and supply chain management: A literature review", Int. J. Prod. Res., vol. 57, no. 15-16, pp. 4719-4742, 2019.
[http://dx.doi.org/10.1080/00207543.2017.1402140]
[2]
H.S. Birkel, J.W. Veile, J.M. Müller, E. Hartmann, and K.I. Voigt, "Development of a risk framework for industry 4.0 in the context of sustainability for established manufacturers", Sustainability, vol. 11, no. 2, p. 384, 2019.
[http://dx.doi.org/10.3390/su11020384]
[3]
H. Kagermann, J. Helbig, A. Hellinger, and W. Wahlster, " Recommendations for implementing the strategic initiative INDUSTRIE 4.0 April 2013 Securing the future of German manufacturing industry Final report of the Industrie 4.0 Working Group, 2013", https://www.din.de/blob/76902/e8cac883f42bf28536e7e8165993f1fd/recommendations-for-implementing-industry-4-0-data.pdf
[4]
H. Lasi, P. Fettke, H.G. Kemper, T. Feld, and M. Hoffmann, "Industry 4.0", Bus. Inf. Syst. Eng., vol. 6, no. 4, pp. 239-242, 2014.
[http://dx.doi.org/10.1007/s12599-014-0334-4]
[5]
A. Khan, and K. Turowski, "A Survey of Current Challenges in Manufacturing Industry and Preparation for Industry 4.0", In: Advances in Intelligent Systems and Computing., Springer Verlag, 2016, pp. 15-26.
[6]
M. Colak, I. Kaya, and M. Erdogan, "A Fuzzy Based Risk Evaluation Model for Industry 4.0 Transition Process", In: Industrial Engineering in the Big Data Era., Springer: Cham, 2019, pp. 201-215.
[http://dx.doi.org/10.1007/978-3-030-03317-0_17]
[7]
T. Stock, M. Obenaus, S. Kunz, and H. Kohl, "Industry 4.0 as enabler for a sustainable development: A qualitative assessment of its ecological and social potential", Process Saf. Environ. Prot., vol. 118, pp. 254-267, 2018.
[http://dx.doi.org/10.1016/j.psep.2018.06.026]
[8]
D. Kiel, J.M. Müller, C. Arnold, and K. Voigt, "Sustainable industrial value creation: Benefits and challenges of industry 4.0", Int. J. Innov. Manage., 2017.
[http://dx.doi.org/10.1142/S1363919617400151]
[9]
L. Georghiou, "What lies beneath: Avoiding the risk of under-evaluation", Sci. Public Policy, vol. 34, no. 10, pp. 743-752, 2007.
[http://dx.doi.org/10.3152/030234207X259003]
[10]
S. Nath, and B. Sarkar, "“An integrated cloud manufacturing model for warehouse selection in a smart supply chain network: A comparative study”, J. Inst. Eng. (India)", Ser. C, vol. 101, no. 1, pp. 25-41, 2020.
[http://dx.doi.org/10.1007/s40032-019-00544-8]
[11]
Y. Kazancoglu, and Y.D. Ozkan-Ozen, "Analyzing workforce 4.0 in the fourth industrial revolution and proposing a road map from operations management perspective with fuzzy DEMATEL", J. Enterp. Inf. Manag., vol. 31, no. 6, pp. 891-907, 2018.
[http://dx.doi.org/10.1108/JEIM-01-2017-0015]
[12]
A. Ahmi, H. Elbardan, and R.H. Ali, "Bibliometric analysis of published literature on industry 4.0", In 2019 International Conference on Electronics, Information and Communication (ICEIC), 2019pp. 1-6
[13]
B. Chen, J. Wan, L. Shu, P. Li, M. Mukherjee, and B. Yin, "Smart factory of industry 4.0: Key technologies, application case, and challenges", IEEE Access, vol. 6, pp. 6505-6519, 2017.
[http://dx.doi.org/10.1109/ACCESS.2017.2783682]
[14]
M. Khan, X. Wu, X. Xu, and W. Dou, "Big data challenges and opportunities in the hype of Industry 4.0", In 2017 IEEE International Conference on Communications (ICC), 2017pp. 1-6
[15]
X. Chao, G. Kou, Y. Peng, and F.E. Alsaadi, "Behavior monitoring methods for trade-based money laundering integrating macro and micro prudential regulation: A case from China", Technol. Econ. Dev. Econ., vol. 25, no. 6, pp. 1081-1096, 2019.
[http://dx.doi.org/10.3846/tede.2019.9383]
[16]
S.S. Kamble, A. Gunasekaran, and S.A. Gawankar, "Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives", Process Saf. Environ. Prot., vol. 117, pp. 408-425, 2018.
[http://dx.doi.org/10.1016/j.psep.2018.05.009]
[17]
S.S. Kamble, A. Gunasekaran, and R. Sharma, "Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry", Comput. Ind., vol. 101, pp. 107-119, 2018.
[http://dx.doi.org/10.1016/j.compind.2018.06.004]
[18]
D.K. Maurya, A. Kumar, S. Kaunoujiya, D. Prasad, and V. Nath, Study and design of smart industry: A review.Nanoelectronics, Circuits and Communication Systems., Springer: Singapore, 2019, pp. 591-598.
[19]
B. Sivathanu, "Adoption of industrial IoT in auto-component manufacturing SMEs in India", Inf. Resour. Manage. J., vol. 32, no. 2, pp. 52-75, 2019.
[http://dx.doi.org/10.4018/IRMJ.2019040103]
[20]
S. Vaidya, P. Ambad, and S. Bhosle, Industry 4.0 - A glimpse., Procedia Manuf, 2018, pp. 233-238.
[21]
P.D. Jadhav, "A study on impact of industry 4.0 in India", Sagar. Int. Adv. Res. J. Sci. Eng. Technol, vol. 2, no. 1, pp. 1-5, 2015.
[22]
P. Priyadarshinee, R.D. Raut, M.K. Jha, and S.S. Kamble, "A cloud computing adoption in Indian SMEs: Scale development and validation approach", J. High Technol. Manage. Res., vol. 28, no. 2, pp. 221-245, 2017.
[http://dx.doi.org/10.1016/j.hitech.2017.10.010]
[23]
S.A. Gawankar, A. Gunasekaran, and S. Kamble, "A study on investments in the big data-driven supply chain, performance measures and organisational performance in Indian retail 4.0 context", Int. J. Prod. Res., vol. 58, no. 5, pp. 1574-1593, 2020.
[http://dx.doi.org/10.1080/00207543.2019.1668070]
[24]
F.D. Keskin, İ. Kabasakal, Y. Kaymaz, and H. Soyuer, "An assessment model for organizational adoption of industry 4.0 based on multi-criteria decision techniques", In Proceedings of the International Symposium for Production Research, 2018pp. 85-100
[25]
G. Kou, X. Chao, Y. Peng, F.E. Alsaadi, and E. Herrera-Viedma, "Machine learning methods for systemic risk analysis in financial sectors", Technol. Econ. Dev. Econ., vol. 25, no. 5, pp. 716-742, 2019.
[26]
N. Medić, J. Prester, and I. Palcic, "Evaluation of advanced digital technologies in manufacturing companies: Hybrid fuzzy MCDM approach building competitiveness of croatian manufacturing view project", In 25th International European Manufacturing Conference, 2018, pp. 1-10.https://www.researchgate.net/publication/326040450
[27]
M. Peruzzini, M. Pellicciari, and C. Bil, "Transdisciplinary engineering methods for social innovation of industry 4.0", In Proceedings of the 25th ISPE Inc. International Conference on Transdisciplinary Engineering, vol. 7, p. 72, 2018.
[28]
J. Tupa, J. Simota, and F. Steiner, "Aspects of risk management implementation for industry 4.0", Procedia Manuf., vol. 11, pp. 1223-1230, 2017.
[http://dx.doi.org/10.1016/j.promfg.2017.07.248]
[29]
G. Kou, Y. Peng, and G. Wang, "Evaluation of clustering algorithms for financial risk analysis using MCDM methods", Inf. Sci., vol. 275, pp. 1-2, 2014.
[http://dx.doi.org/10.1016/j.ins.2014.02.137]
[30]
M.T. Bhagawati, E. Manavalan, K. Jayakrishna, and P. Venkumar, "Identifying key success factors of sustainability in supply chain management for industry 4.0 using DEMATEL method", In Proceedings of International Conference on Intelligent Manufacturing and Automation, 2019pp. 583-591
[http://dx.doi.org/10.1007/978-981-13-2490-1_54]
[31]
J.M. Müller, O. Buliga, and K.I. Voigt, "Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0", Technol. Forecast. Soc. Change, vol. 132, pp. 2-17, 2018.
[http://dx.doi.org/10.1016/j.techfore.2017.12.019]
[32]
D. O. Sanchez, "Sustainable development challenges and risks of industry 4.0: A literature review", In: 2019 IEEE Global IoT Summit (GIoTS), 2019, pp. 1-6.
[33]
T. Bányai, P. Tamás, B. Illés, Ž. Stankevičiūtė, and Á. Bányai, "Optimization of municipal waste collection routing: Impact of industry 4.0 technologies on environmental awareness and sustainability", Int. J. Environ. Res. Public Health, vol. 16, no. 4, p. 634, 2019.
[http://dx.doi.org/10.3390/ijerph16040634] [PMID: 30795548]
[34]
A. Benešová, and J. Tupa, "Requirements for education and qualification of people in industry 4.0", Procedia Manuf., vol. 11, pp. 2195-2202, 2017.
[http://dx.doi.org/10.1016/j.promfg.2017.07.366]
[35]
M. Gill, and S. VanBoskirk, The digital maturity model 4.0. benchmarks: Digital transformation playbook, 2016, p. 17.
[36]
S. Mittal, D. Romero, and T. Wuest, "Towards a smart manufacturing maturity model for SMEs", In IFIP International Conference on Advances in Production Management Systems, 2018pp. 155-163
[37]
U. Niesen, and M.A. Maddah-Ali, "Coded caching with nonuniform demands", IEEE Trans. Inf. Theory, vol. 63, no. 2, pp. 1146-1158, 2017.
[http://dx.doi.org/10.1109/TIT.2016.2639522]
[38]
I. Castelo-Branco, F. Cruz-Jesus, and T. Oliveira, "Assessing industry 4.0 readiness in manufacturing: Evidence for the European union", Comput. Ind., vol. 107, pp. 22-32, 2019.https://www2.deloitte.com/content/dam/Deloitte/cy/Documents/innovation-and-entrepreneurship%20centre/Industry%204.0%20readiness%20report%202019.pdf
[39]
K. Lichtblau, V. Stich, R. Bertenrath, M. Blum, M. Bleider, A. Millack, K. Schmitt, E. Schmitz, and M. Schröter, IMPULS-Industrie 4.0-Readiness., Impuls-Stiftung des VDMA: Aachen, Köln, 2015.
[40]
S. Wibowo, and S. Grandhi, "Fuzzy multicriteria analysis for performance evaluation of internet-of-things-based supply chains", Symmetry, vol. 10, no. 11, p. 603, 2018.
[http://dx.doi.org/10.3390/sym10110603]
[41]
P. Potyrańska, Opportunities and Threats for the Introduction of Nuclear Power in Poland., Energy Policy Studies, 2019.
[42]
D. Jobber, and F. Ellis-Chadwick, Principles and practice of marketing (No. 7th)., McGraw-Hill Higher Education, 2012.
[43]
T.L. Satty, The Analytic Hierarchy Process., McGraw-Hill: New York, 1980.
[44]
E.K. Zavadskas, and V. Podvezko, "Integrated determination of objective criteria weights in MCDM", Int. J. Inf. Technol. Decis. Mak, vol. 15, no. 2, pp. 267-283, 2016.
[http://dx.doi.org/10.1142/S0219622016500036]
[45]
E.K. Zavadskas, Z. Turskis, and V. Bagočius, "Multi-criteria selection of a deep-water port in the Eastern Baltic Sea", Appl. Soft Comput. J., vol. 26, pp. 180-192, 2015.
[http://dx.doi.org/10.1016/j.asoc.2014.09.019]
[46]
J.J. Buckley, "Ranking alternatives using fuzzy numbers", Fuzzy Sets Syst., vol. 15, no. 1, pp. 21-31, 1985.
[http://dx.doi.org/10.1016/0165-0114(85)90013-2]
[47]
S. NǎdǍban, "S. Dzitac and I. Dzitac, “Fuzzy TOPSIS: A general view", Procedia Comput. Sci., vol. 91, pp. 823-831, 2016.
[48]
P. Priyadarshinee, R.D. Raut, M.K. Jha, and S.S. Kamble, "A cloud computing adoption in Indian SMEs: Scale development and validation approach", J. High Technol. Manage. Res., vol. 28, no. 2, pp. 221-245, 2017.
[http://dx.doi.org/10.1016/j.hitech.2017.10.010]
[49]
B.M. Elomda, H.A. Hefny, and H.A. Hassan, "An extension of fuzzy decision maps for multi-criteria decision-making", Egypt. Inform. J., vol. 14, no. 2, pp. 147-155, 2013.
[http://dx.doi.org/10.1016/j.eij.2013.05.001]
[50]
H.Y. Wu, G.H. Tzeng, and Y.H. Chen, "A fuzzy MCDM approach for evaluating banking performance based on balanced scorecard", Expert Syst. Appl., vol. 36, no. 6, pp. 10135-10147, 2009.
[http://dx.doi.org/10.1016/j.eswa.2009.01.005]
[51]
A.N. Haq, and G. Kannan, "Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model", Int. J. Adv. Manuf. Technol., vol. 29, no. 7-8, pp. 826-835, 2006.
[http://dx.doi.org/10.1007/s00170-005-2562-8]
[52]
V.K. Mittal, and K.S. Sangwan, "Fuzzy TOPSIS method for ranking barriers to environmentally conscious manufacturing implementation: Government, industry and expert perspectives", Int. J. Environ. Technol. Manag., vol. 17, no. 1, pp. 57-82, 2014.
[http://dx.doi.org/10.1504/IJETM.2014.059466]
[53]
C.L. Hwang, and K. Yoon, Multiple Attribute Decision Making: Methods and Applications A State-Of-The-Art Survey., Springer Science & Business Media,Springer, 2012.
[54]
C.T. Chen, "Extensions of the TOPSIS for group decision-making under fuzzy environment", Fuzzy Sets Syst., vol. 114, no. 1, pp. 1-9, 2000.
[http://dx.doi.org/10.1016/S0165-0114(97)00377-1]
[55]
K. Govindan, A. Diabat, and K.M. Shankar, "Analyzing the drivers of green manufacturing with fuzzy approach", J. Clean. Prod., vol. 96, pp. 182-193, 2015.
[http://dx.doi.org/10.1016/j.jclepro.2014.02.054]
[56]
H.C. Lee, and C.T. Chang, "Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan", Renewable and Sustainable Energy Reviews, vol. 92, pp. 883-896, 2018.
[http://dx.doi.org/10.1016/j.rser.2018.05.007]
[57]
F. Ma, Y. Zhao, Y. Pu, and J. Li, "A comprehensive multi-criteria decision making model for sustainable material selection considering life cycle assessment method", IEEE Access, vol. 6, pp. 58338-58354, 2018.
[http://dx.doi.org/10.1109/ACCESS.2018.2875038]
[58]
D. Pamučar, and G. Ćirović, "The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC)", Expert Syst. Appl., vol. 42, no. 6, pp. 3016-3028, 2015.
[http://dx.doi.org/10.1016/j.eswa.2014.11.057]

Rights & Permissions Print Cite
Article Metrics
18
1
© 2024 Bentham Science Publishers | Privacy Policy