Modeling and Analysis of Challenges for Industry 4.0 Implementation in Medical Device Industry to Post COVID -19 Scenario

Document Type : SI; Managing SCL in COVID-19


1 School of Management. BML Munjal University, Gurugram, Haryana, India

2 Guildhall School of Business and Law, London Metropolitan University, London, UK

3 School of Engineering and Technology. BML Munjal University, Gurugram, Haryana, India


Today, the health care and medical sector is adopting digital technologies aggressively. However, this adoption also has significant challenges, especially during COVID-19. This research aims to identify and categorize the significant challenges related with application of Industry 4.0 (I4.0) technologies in the medical device industry. An expert-based survey is carried to capture the perception of medical device industry leaders about the challenges associated with the implementation of digital technologies. Further, interpretive structural modeling (ISM) method was used for an empirical investigation of the hierarchy and interdependencies of identified challenges. The authors have proposed a mind map and conceptual model of hierarchy and interdependencies of challenges associated with the digital transformation of the medical device industry towards I4.0. Industry leaders and policymakers worldwide are defying challenges while the digital transformation of the organizations post COVID-19. The I4.0 implementation challenges identified and categorized in this research may aid as a guide for medical device manufacturing organizations while designing a strategy for I4.0 transformation and to make sure that they start on the right -footing. Most of the existing work is focused on the advantages of I4.0 for managing the organization's post-COVID-19, lacks thoroughness and testing. Owing to the identified gap, this study intends to empirically identify the critical challenges associated with applying I4.0 technologies in the medical device manufacturing sector. This study is a pioneer in identifying and categorizing the vital challenges needed to deal with this critical situation.


Ahmed, S. M., Karmaker, C. L., Doss, D. A., and Khan, A. H. (2020). Modeling the Barriers in Managing Closed Loop Supply Chains of Automotive Industries in Bangladesh. International Journal of Supply and Operations Management, Vol. 7(1), pp. 76-92.
Akdil, K. Y., Ustundag, A., and Cevikcan, E. (2018). Maturity and readiness model for industry 4.0 strategy. Industry 4.0: Managing digital transformation 61-94). Springer, Cham, DOI: 10.1007/978-3-319-57870-5_4
AlMaadeed, M. A. (2020) Emergent materials and industry 4.0 contribution toward pandemic diseases such as COVID-19. Emergent Materials, 1. DOI: 10.1007/s42247-020-00102-4 
Alizadeh, R., Lund, P. D., Beynaghi, A., Abolghasemi, M., and Maknoon, R. (2016). An integrated scenario-based robust planning approach for foresight and strategic management with application to the energy industry. Technological Forecasting and Social Change, Vol.104, pp. 162-171.
Amini, A., and Alinezhad, A. (2017). Integrating DEA and group AHP for efficiency evaluation and the identification of the most efficient DMU. International Journal of Supply and Operations Management, Vol. 4(4), pp. 318-327.
Basak, P. C., and KG, V. (2015). Costs of quality: Exploratory analysis of hidden elements and prioritization using analytic hierarchy process. International Journal of Supply and Operations Management, Vol.1(4), pp.489-506.
Brettel, M., Friederichsen, N., Keller, M., and Rosenberg, M. (2014). How virtualization, decentralization, and network building change the manufacturing landscape: An Industry 4.0 Perspective. International journal of mechanical, industrial science and engineering, Vol.8(1), pp.37-44.
Birkel, H. S., Veile, J. W., Müller, J. M., Hartmann, E., and Voigt, K. I. (2019). Development of a risk framework for Industry 4.0 in the context of sustainability for established manufacturers. Sustainability, 11(2), 384. DOI: 10.3390/su11020384 Büchi, G., Cugno, M., & Castagnoli, R. (2020). Smart factory performance and Industry 4.0. Technological Forecasting and Social Change, Vol.150, pp. 119790.
Cho, Y. S., Maysami, R., Jung, J., and Lee, C. C. (2016). An Empirical Investigation of the Universal Effectiveness of Quality Management Practices: A Structural Equation Modeling Approach. International Journal of Supply and Operations Management, Vol.3(1), pp.1102-1111.
De Vries, H., and Van Wassenhove, L. N. (2020). Do Optimization Models for Humanitarian Operations Need a Paradigm Shift? Production and Operations Management, Vol.29(1), pp.55-61.
Dun and Bradstreet, 2020. accessed on May 10, 2020
Dube, N., Van der Vaart, T., Teunter, R. H., and Van Wassenhove, L. N. (2016). Host government impact on the logistics performance of international humanitarian organisations. Journal of Operations Management, Vol.47, pp.44-57.
Drake, D. F., Kleindorfer, P. R., and Van Wassenhove, L. N. (2016). Technology choice and capacity portfolios under emissions regulation. Production and Operations Management, Vol.25(6), 1006-1025.
Fazli-Khalaf, M., Khalilpourazari, S., and Mohammadi, M. (2019). Mixed robust possibilistic flexible chance constraint optimization model for emergency blood supply chain network design. Annals of Operations Research, Vol.283(1), pp.1079-1109.
Fadel, M., Salomon, J., and Descatha, A. (2020). Coronavirus outbreak: the role of companies in preparedness and responses. The Lancet Public Health, Vol.5(4), e193. //
Frederico, G. F., Garza-Reyes, J. A., Kumar, A., and Kumar, V. (2020). Performance measurement for supply chains in the Industry 4.0 era: a balanced scorecard approach. International Journal of Productivity and Performance Management. DOI: 10.1108/IJPPM-08-2019-0400 Fortune, 2020. impact/, accessed on May 10, 2020
Frederico, G. F., Garza-Reyes, J. A., Kumar, A., & Kumar, V. (2020). Performance measurement for supply chains in the Industry 4.0 era: a balanced scorecard approach. International Journal of Productivity and Performance Management, Vol. 70 (4), pp. 789-807.
Ghobakhloo, M. (2018), The future of manufacturing industry: a strategic roadmap toward Industry 4.0, Journal of Manufacturing Technology Management, Vol. 29(6), pp. 910-936. DOI 10.1108/JMTM-02-2018-0057
Ghadge, A., Kara, M. E., Moradlou, H., and Goswami, M. (2020). The impact of Industry 4.0 implementation on supply chains. Journal of Manufacturing Technology Management. DOI: 10.1108/JMTM-10-2019-0368
Gopal, P.R.C., and J. Thakkar. (2016). Analysing Critical Success Factors to Implement Sustainable Supply Chain Practices in Indian Automobile Industry: A Case Study. Production Planning & Control, Vol.27 (12), pp. 1005–1018
Hariharasudan, A., and Kot, S. (2018). A scoping review on digital English and Education 4.0 for Industry 4.0. Social Sciences, Vol.7(11), pp.227. DOI: 10.3390/socsci7110227
Hoseini, S. M., Mollaverdi, N., Hejazi, S. R., and Rezvan, M. T. (2019). A Multi-attribute Approach for Simultaneous Determination of Preventive Replacement Times and Order Quantity of Spare Parts. International Journal of Supply and Operations Management, Vol.6(2), pp. 110-125.
Khan, A. S., and Ghauri, S. K. (2020). Corona Pandemic: Lack of Resources but not of Determination–A South Asian Perspective. South Asian Journal of Emergency Medicine, Vol.3(1), pp. 1-2.
Khalilpourazari, S., Pasandideh, S. H. R., and Ghodratnama, A. (2019). Robust possibilistic programming for multi-item EOQ model with defective supply batches: Whale optimization and water cycle algorithms. Neural Computing and Applications, Vol.31(10), pp. 6587-6614.
Haleem, A., Javaid, M., Vaishya, R., and Deshmukh, S. G. (2020). Areas of academic research with the impact of COVID-19. The American Journal of Emergency Medicine. //
Ito, K., Ikeuchi, K., Criscuolo, C., Timmis, J., Bergeaud, A., Inoue, H., and Erbahar (2020), A. COVID-19 could spur automation and reverse globalization–to some extent. Accessed on May 10, 2020.
Ivanov, D., Dolgui, A., and Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, Vol.57(3), pp. 829-846.
Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case. Transportation Research Part E: Logistics and Transportation Review, Vol.136, pp. 1019220 DOI: 10.1016/j.tre.2020.101922
Ivanov, D., and Dolgui, A. (2020). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, pp. 1-14.
Javaid, M., Haleem, A., Vaishya, R., Bahl, S., Suman, R., and Vaish, A. (2020). Industry 4.0 technologies and their applications in fighting the COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. DOI: 10.1016/j.dsx.2020.04.032
Javaid, M., and Haleem, A. (2019). Industry 4.0 applications in the medical field: a brief review. Current Medicine Research and Practice.
Kiel, D., Müller, J. M., Arnold, C., and Voigt, K. I. (2017). Sustainable industrial value creation: Benefits and challenges of industry 4.0. International Journal of Innovation Management, Vol. 21(08), pp. 1-34.
Kıran, M. S., Özceylan, E., Gündüz, M., and Paksoy, T. (2012). A novel hybrid approach based on particle swarm optimization and ant colony algorithm to forecast energy demand of Turkey. Energy conversion and management, Vol.53(1), pp. 75-83.
Koonin, L. M. (2020). Novel coronavirus disease (COVID-19) outbreak: Now is the time to refresh pandemic plans. Journal of business continuity & emergency planning, Vol.13(4), pp.1-15
Khan, A. S., and Ghauri, S. K. (2020). Corona Pandemic: Lack of Resources but not of Determination–A South Asian Perspective. South Asian Journal of Emergency Medicine, Vol.3(1), pp.1-2.
Kumari, A., Tanwar, S., Tyagi, S., and Kumar, N. (2018). Fog computing for Healthcare 4.0 environment: Opportunities and challenges. Computers & Electrical Engineering, Vol. 72, pp. 1-13. / 0045-7906
Kumar, A., Zavadskas, E. K., Mangla, S. K., Agrawal, V., Sharma, K., & Gupta, D. (2019). When risks need attention: adoption of green supply chain initiatives in the pharmaceutical industry. International Journal of Production Research, Vol.57(11), pp. 3554-3576.
Kaviani, M. A., Tavana, M., Kumar, A., Michnik, J., Niknam, R., and de Campos, E. A. R. (2020). An integrated framework for evaluating the barriers to successful implementation of reverse logistics in the automotive industry. Journal of Cleaner Production, Vol.272, pp. 122714.
Kumar, A., Choudhary, S., Garza-Reyes, J. A., Kumar, V., Khan, S. R. A., and Mishra, N. (2020). Analysis of critical success factors for implementing industry 4.0 integrated circular supply chain–Moving towards sustainable operations. Production Planning and Control. (in press)
Kruger, H. M., Meaton, J., and Williams, A. (2020). Pandemic Continuity Planning: will coronavirus test local authority business continuity plans? A case study of a local authority in the north of England. Emergency Management Review, Vol.4(1), pp. 4-27.
Livingston, E., Desai, A., and Berkwits, M. (2020). Sourcing personal protective equipment during the COVID-19 pandemic. JAMA, Vol.323(19), pp.1912-1914. DOI:10.1001/jama.2020.5317
Lee, J., Davari, H., Singh, J., and Pandhare, V. (2018). Industrial Artificial Intelligence for industry 4.0- based manufacturing systems. Manufacturing Letters, Vol.18, pp. 20-23.
Luthra, S., and Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, Vol.117, pp. 168-179.
Luthra, S., Mangla, S. K., Garg, D., and Kumar, A. (2018). Internet of things (IoT) in agriculture supply chain management: a developing country perspective. In Emerging Markets from a Multidisciplinary Perspective (pp. 209-220). Springer, Cham.
Martin, F. M. (2020). Economic realities and consequences of the COVID-19 pandemic—Part II: The economy and fiscal policy. Economic Synopses, 11. 2020
Mhlanga, D. (2020). Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion. International Journal of Financial Studies, Vol.8(3), pp.45.
Mitra, A., Ray Chadhuri, T., Mitra, A., Pramanick, P., and Zaman, S. (2020). Impact of COVID-19 related shutdown on the atmospheric carbon dioxide level in the city of Kolkata. Parana Journal of Science and Education, Vol. 6(3), pp. 84-92.
Nicola, M., Alsafi, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, C., and Agha, R. (2020). The socio-economic implications of the coronavirus and COVID-19 pandemic: A review. International Journal of Surgery. DOI: 10.1016/j.ijsu.2020.04.018
Neirotti, P., and Raguseo, E. (2017). On the contingent value of IT-based capabilities for the competitive advantage of SMEs. Mechanisms and empirical evidence. Information & Management, Vol.54(2), pp. 139-153, DOI: 10.1016/
Nishat Faisal, M., Banwet, D.K. and Shankar, R. (2006), "Supply chain risk mitigation: modeling the enablers", Business Process Management Journal, Vol. 12(4), pp. 535-552.
Oesterreich, T. D., and Teuteberg, F. (2016). Understanding the implications of digitization and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry. Computers in industry, Vol.83, 121-139. 0166-3615.
Panahifar, F., P.J. Byrne, and C. Heavey. (2014). ISM Analysis of CPFR Implementation                Barriers. International Journal of Production Research, Vol.52(18), pp. 5255–5272.
Porter, J. A., Haberling, K., and Hohman, C. (2016). Employer desired competencies for undergraduate health administration graduates entering the job market. Journal of Health Administration Education, Vol.33(3), pp. 355-375.
Prisecaru, P. (2017). The challenges of the industry 4.0. Global Economic Observer, 5(1), 66. Ranney, M. L., Griffeth, V., & Jha, A. K. (2020). Critical supply shortages—the need for ventilators and personal protective equipment during the Covid-19 pandemic. New England Journal of Medicine, Vol.382(18), e41. DOI: 10.1056/NEJMp2006141.
Sannino, G., De Falco, I., and De Pietro, G. (2018). A Continuous Noninvasive Arterial Pressure (CNAP) Approach for Health 4.0 Systems. IEEE Transactions on Industrial Informatics, Vol.15(1), pp. 498-506. DOI: 10.1109/TII.2018.2832081
Seknickova, J. and Jablonsky, J., (2020). Alternative energy sources and their analysis as investment opportunities: A case of the Czech Republic. International Journal of Supply and Operations Management, Vol.7(2), pp.189-201.
Spina, S., Marrazzo, F., Migliari, M., Stucchi, R., Sforza, A., and Fumagalli, R. (2020). The response of Milan's Emergency Medical System to the COVID-19 outbreak in Italy. The Lancet, Vol. 395(10227), pp. e49-e50.
Shamim, S., Cang, S., Yu, H., and Li, Y. (2017). Examining the feasibilities of Industry 4.0 for the hospitality sector with the lens of management practice. Energies, Vol.10(4), pp. 499. DOI:10.3390/en10040499
Salimova, T., Guskova, N., Krakovskaya, I., and Sirota, E. (2019, March). From industry 4.0 to Society 5.0: challenges for the sustainable competitiveness of the Russian industry. In IOP Conference Series: Materials Science and Engineering (Vol. 497, No. 1, p. 012090). IOP Publishing. DOI:10.1088/1757-899X/497/1/012090
Sivaprakasam, R., V. Selladurai, and P. Sasikumar. (2015). Implementation of Interpretive Structural Modelling Methodology as a Strategic Decision Making Tool in a Green Supply Chain Context. Annals of Operations Research, Vol.233(1), pp. 423–448
Snieška, V., Navickas, V., Havierniková, K., Okręglicka, M., and Gajda, W. (2020). Technical, information, and innovation risks of industry 4.0 in small and medium-sized enterprises–case of Slovakia and Poland. Journal of Business Economics and Management, Vol.21(5), pp. 1269-1284.
Sulkowski, A. J. (2020). COVID-19: What's Next? Future of Work, Business, and Law: Automation, Transparency, Blockchain, Education, and Inspiration. Business, and Law: Automation, Transparency, Blockchain, Education, and Inspiration (April 19, 2020).
Sunil Luthra, Anil Kumar, Edmundas Kazimieras Zavadskas, Sachin Kumar Mangla and Jose Arturo Garza-Reyes (2020) Industry 4.0 as an enabler of sustainability diffusion in the supply chain: an analysis of influential strength of drivers in an emerging economy, International Journal of Production Research, Vol.58(5), pp. 1505-1521, DOI: 10.1080/00207543.2019.1660828
Thuemmler, C., and Bai, C. (2017). Health 4.0: Application of industry 4.0 design principles in future asthma management. In Health 4.0: How virtualization and big data are revolutionizing healthcare (pp. 23-37). Springer, Cham.
Tupa, J., Simota, J., and Steiner, F. (2017). Aspects of risk management implementation for Industry 4.0. Procedia Manufacturing, Vol.11, pp. 1223-1230. DOI: 10.1016/j.promfg.2017.07.248
Vaishya, R., Haleem, A., Vaish, A., and Javaid, M. (2020). Emerging technologies to combat COVID-19 pandemic. Journal of Clinical and Experimental Hepatology DOI: 10.1016/j.jceh.2020.04.019
Vasanthakumar, C., S. Vinodh, and K. Ramesh. (2016). Application of Interpretive Structural Modeling for Analysis of Factors Influencing Lean Remanufacturing Practices. International Journal of Production Research, Vol.54 (24), pp. 7439–7452.
Verawardina, U., Asnur, L., Lubis, A. L., Hendriyani, Y., Ramadhani, D., Dewi, I. P., and Sriwahyuni, T. (2020). Reviewing Online Learning Facing the COVID-19 Outbreak. Journal of Talent Development and Excellence, Vol.12(3s), pp. 385-392.
Wang, N., Nguyen, T., and Nguyen, H. (2015). Strategic Alliance Decision-Making for the Auto Industry Base on an Integrate DEA and GM (1, 1) Approach. International Journal of Supply and Operations Management, Vol.2(3), pp. 856-870.
Wuest, T., Kusiak, A., Dai, T., and Tayur, S. R. (2020). Impact of COVID-19 on Manufacturing and Supply Networks—The Case for AI-Inspired Digital Transformation. Available at SSRN 3593540.
Warfield, J.W. (1974), Developing interconnected matrices in structural modeling, IEEE Transactions on Systems, Man and Cybernetics, Vol. 4(1), pp. 51-81.
Xu, L. D., Xu, E. L., and Li, L. (2018). Industry 4.0: state of the art and future trends. International Journal of Production Research, Vol. 56(8), pp. 2941-2962.
Yadav, G., Kumar, A., Luthra, S., Garza-Reyes, J. A., Kumar, V., and Batista, L. (2020). A framework to achieve sustainability in manufacturing organizations of developing economies using industry 4.0 technologies' enablers. Computers in Industry, Vol. 122, pp. 103280.