Disruption in Manufacturing Industry - The Future of Global Workforce
DOI:
https://doi.org/10.14738/assrj.611.7414Abstract
The aim of this research was to evaluate the future of the global workforce aligned with the disruptive technologies in the manufacturing industry. The impacts of 5G, robotics, artificial intelligence, and machine learning were focused on current research. The purpose was to identify the possible safety net, which could be used by the governments and regulatory authorities to deal with the negative effects of technologies on the workers’ displacement in the next 5 to 10 years. Through the implementation of the inductive research methodology based on structured survey questionnaire administered with the sample of 100 employees working in the manufacturing sector, effects of disruptive technologies on the employment situation, production activity and overall organisation performance were addressed.
Findings of the investigation have confirmed that new technologies have positive impacts on the production activity and overall organisational performance. New technologies are contributing vitally to increasing the production output, production quality, improving the cost of delays, increasing efficient waste management, reliable and consistent growth and enhanced profitability for the manufacturing companies. In contrary, these technologies are also having negative effects on the employment situation such as reduced recruitment, training, compensation, and increased unrest. Lastly, the set of recommendations directing towards introducing governmental regulations and policies for mandatory training, balanced compensation and increased hiring, are expected to have a significant positive contribution for tackling the issue of displacements.
References
Abri, A. G. & Mahmoudzadeh, M., 2015. Impact of information technology on productivity and efficiency in Iranian manufacturing industries. Journal of Industrial Engineering International, 11(1), pp. 143-157.
Armstrong, P., 2017. Disruptive Technologies: Understand, Evaluate, Respond. s.l.:Kogan Page.
Arntz, M., Gregory, T. & Zierahn, U., 2016. The Risk of Automation for Jobs in OECD Countries A COMPARATIVE ANALYSIS. s.l. OECD.
Autor, D. H., Dorn, D. & Hanson, G. H., 2015. Untangling Trade and Technology: Evidence from Local Labour Markets. The Economics Journal, 125(584), pp. 621-646.
BenediktFrey, C. & A.Osborne, M., 2017. The future of employment: How susceptible are jobs to computerisation?*. Technological Forecasting and Social Change, Volume 114, pp. 254-280.
Benyoucef, L. & Grabot, B., 2010. Artificial Intelligence Techniques for Networked Manufacturing Enterprises Management, s.l.: Springer Science & Business Media.
Betz, F., 2011. Managing Technological Innovation: Competitive Advantage from Change, s.l.: John Wiley & Sons.
Cheng, J., Chen, W., Tao, F. & Lin, C.-L., 2018. Industrial IoT in 5G environment towards smart manufacturing. Journal of Industrial Information Integration, Volume 10, pp. 10-19.
Chui, M., Manyika, J. & Miremadi, M., 2016. Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly, July.
Daugherty, P. R. & Wilson, H. J., 2018. Human + Machine: Reimagining Work in the Age of AI, s.l.: Harvard Business Review Press.
Durakbasa, N. M. & Gencyilmaz, M. G., 2018. Proceedings of the International Symposium for Production Research 2018. s.l.: Springer.
Ekekwe, N., 2012. Disruptive Technologies, Innovation and Global Redesign: Emerging Implications: Emerging Implications. Hershey, PA: IGI Global.
ET Online, 2017. Layoffs scare is real, not exaggerated, finds ET's Jobs Disruption survey. Economic Times, 01 June.
European Union, 2017. Current and Emerging Trends in Disruptive Technologies: Implications for the Present and Future of EU’s Trade Policy, s.l.: EP/EXPO/B/I NTA / 2017 / 06 EN.
Grandinetti, L., 2013. Pervasive Cloud Computing Technologies: Future Outlooks and Interdisciplinary Perspectives: Future Outlooks and Interdisciplinary Perspectives. s.l. IGI Global.
Jeffery, R., 2017. At Toyota, The Automation Is Human-Powered. Fast Company, 09 May.
Karsten, J. & West, D. M., 2015. How robots, artificial intelligence, and machine learning will affect employment and public policy. Brookings.Edu, 26 October.
Kautz, K. & Pries-Heje, J., 2013. Diffusion and Adoption of Information Technology: Proceedings of the first IFIP WG 8.6 working conference on the diffusion and adoption of information technology, Oslo, Norway, October 1995. s.l.: Springer.
Kolberg, D. & Zühlke, D., 2015. Lean Automation enabled by Industry 4.0 Technologies. IFAC-PapersOnLine, 48(3), pp. 1870-1875.
Latif, S., Qadir, J., Farooq, S. & Imran, M. A., 2017. How 5G Wireless (and Concomitant Technologies) Will Revolutionize Healthcare?. Future Internet, 9(4), p. 93.
Manyika, J. et al., 2013. Disruptive technologies: Advances that will transform life, business, and the global economy, s.l.: McKinsey Global Institute.
Manyika, J. et al., 2013. Disruptive technologies: Advances that will transform life, business, and the global economy. McKinsey Global Institute, May.
Marchetti, N., 2014. Towards the 5th Generation of Wireless Communication Systems, s.l.: Trinity College Dublin, Ireland.
McKinsey Global Institute, 2017. Jobs Lost, Jobs Gained: Workforce Transitions In A Time Of Automation. s.l.: McKinsey Global Institute.
Mehta, S., 2016. Innovation and Employment: A Study of Indian Manufacturing Sector. Millennial Asia, 7(2).
Mellor, S., Hao, L. & Zhang, D., 2014. Additive manufacturing: A framework for implementation. International Journal of Production Economics, Volume 149, pp. 194-201.
OECD, 2018. Transformative technologies and jobs for the future, s.l. MONTREAL, CANADA.
Osseiran, A., Monserrat, J. F. & Marsch, P., 2016. 5G Mobile and Wireless Communications Technology. Cambridge: Cambridge University Press.
Palfrey, J. G. & Gasser, U., 2011. Remote Work and Collaboration: Breakthroughs in Research and Practice: Breakthroughs in Research and Practice, s.l.: ReadHowYouWant.com.
Paul, C. J. M. & Siegel, D. S., 2001. The Impacts of Technology, Trade and Outsourcing on Employment and Labor Composition. The Scandinavian Journal of Economics, 103(2), pp. 241-264.
Poole, D. L. & Mackworth, A. K., 2017. Artificial Intelligence. New York: Cambridge University Press.
Quora, 2018. Technology Has Already Taken Over 90% Of The Jobs Humans Used To Do. Forbes.Com, 18 January.
Rendall, M., 2016. Industrial Robots will replace manufacturing jobs and that a good thing. Tech Crunch, 10 Oct.
Rigby, R., 2016. Job cuts and disruption call for sensitive leadership. Financial Times, 26 February.
Rosen, R. J., 2015. In Praise of Short-Term Thinking. The Atlantic.Com, 03 September.
Sandle, T., 2018. Austria uses 5G technology to improve production. Digital Journal, 24 March.
Saunders, M. N. K. & Lewis, P., 2017. Doing Research in Business and Management. s.l.: Pearson.
Saunders, M. N. K., Lewis, P. & Thornhill, A., 2003. Research Methods for Business Students. s.l.: Pearson.
Shin, D.-I., 2017. An exploratory study of innovation strategies of the internet of things SMEs in South Korea. Asia Pacific Journal of Innovation and Entrepreneurship, 11(2), pp. 171-189.
Shi, Z., 2011. Advanced Artificial Intelligence. s.l. World Scientific.
Shrek, J., 2010. Technology Explains Drop in Manufacturing Jobs. The Heritage Foundation, 12 October.
Spiegel, R., 2018. Robots Are Displacing Manual Labor Jobs. DesignNews, 08 February.
Tarantola, A., 2017. Teaming humans with robotic AI will remake modern manufacturing. Engadget, 19 August.
Thames, L. & Schaefer, D., 2017. Cybersecurity for Industry 4.0: Analysis for Design and Manufacturing. s.l.: Springer.
Tossy, T., 2016. Information Technology Integration for Socio-Economic Development. s.l. IGI Global.
Walker, J., 2018. Machine Learning in Manufacturing – Present and Future Use-Cases. Tech Emergence, 29 May.
Wang, L. & Wang, X. V., 2017. Cloud-Based Cyber-Physical Systems in Manufacturing. s.l.: Springer.
Wang, S. et al., 2016. Towards a smart factory for industry 4.0: a self-organized multi-agent system with big data-based feedback and coordination. Computer Networks, 101(4), pp. 158-168.
Wang, X. V., Wang, L., Mohammed, A. & Givehchi, M., 2017. Ubiquitous manufacturing system based on Cloud: A robotics application. Robotics and Computer-Integrated Manufacturing, Volume 45, pp. 116-125.
West, D. M., 2016. What happens if robots take jobs? The impact of emerging technologies on employment and public policy. Center for Technology Innovations at Brookings, pp. 1-22.
Xiang, W., Zheng, K. & Shen, X. (., 2016. 5G Mobile Communications. s.l.: Springer.
Yang Yang, J. X., Shi, G. & Wang, C.-X., 2017. 5G Wireless Systems: Simulation and Evaluation Techniques. s.l.: Springer.
Downloads
Published
How to Cite
Issue
Section
License
Authors wishing to include figures, tables, or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s) for both the print and online format and to include evidence that such permission has been granted when submitting their papers. Any material received without such evidence will be assumed to originate from the authors.
