Learning Needs Determination for Industry 4.0 Maturity Development in Automotive Organisations in Slovakia
Abstract
Purpose: This paper aims to present the results of the study focused on the assessment of Industry 4.0 (I4.0) maturity level and adoption level of Quality 4.0 (Q4.0) intelligent technologies in organisations operating in the automotive industry in Slovakia (OEMs, Tier 1 and Tier 2 suppliers). The results serves as inputs for identification of learning and development needs.
Methodology/Approach: The background of the study was a literature review and quantitative research. The I4.0 maturity model published by PwC (2016) was used in the study, while dimension elements were adjusted to the specifics of the automotive industry.
Findings: Tier 1 and Tier 2 automotive suppliers are in the early stages of I4.0 maturity and adoption of Q4.0 intelligent technologies. OEMs achieve the level of horizontal collaborators in most of the dimensions. Q4.0 intelligent technologies are mostly adopted at an average level. Further development of OEMs to achieve the level of digital champions requires new disruptive business models and a fully integrated partner ecosystem.
Research Limitation/Implication: The research is limited by the sample size and target levels of particular dimensions, related elements and Q4.0 intelligent technologies, which were not examined.
Originality/Value of paper: The results bring more in-depth insight into the current state of I4.0 maturity and Q4.0 technology adoption level of the automotive organisations in Slovakia. There is no evidence of the study examining holistically the I4.0 maturity and Q4.0 technologies in the automotive.References
Alcácer, V. and Cruz-Machado, V., 2019. Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems. Engineering Science and Technology, an International Journal [e-journal], 22(3), pp.899-919. doi: 10.1016/j.jestch.2019.01.006.
Asdecker, B. and Felch, V., 2018. Development of an Industry 4.0 maturity model for the delivery process in supply chains. Journal of Modelling in Management [e-journal], 13(4), pp.840-883. doi: 10.1108/JM2-03-2018-0042.
Athanasopoulou, A., Reuver, M., Nikou, S. and Bouwman, H., 2019. What technology enabled services impact business models in the automotive industry? An exploratory study. Futures [e-journal], 109, pp.73-83. doi: 10.1016/j.futures.2019.04.001.
Bakertilly, 2019. Industry 4.0 and the Industrial Internet of Things (IIoT). [online] Available at: < https://bakertilly.com/industry-4.0/ > [Accessed 09 January 2020].
Becker, J., Knackstedt, R. and Pöppelbuß, J., 2009. Developing Maturity Models for IT Management: A Procedure Model and its Application for IT Management. Business & Information Systems Engineering [e-journal], 1(3), pp.213-222. doi: 10.1007/11576-009-0167-9.
Berger, R., 2014. Industry 4.0: The New Industrial Revolution. Munich: Operations Strategy Competence Center.
Bibby, L. and Dehe, B., 2018. Defining and assessing industry 4.0 maturity levels– case of the defence sector. Production Planning & Control, 29(12), pp.1030-1043.
Boyes, H., Hallaq, B., Cunningham, J. and Watson, T., 2018. The industrial internet of things (IIoT): An analysis framework. Computers in Industry [e-journal], 101, pp.1-12. doi: 10.1016/j.compind.2018.04.015.
Buchi, G., Cugno, M. and Castagnoli, R., 2020. Smart factory performance and Industry 4.0. Technological Forecasting and Social Change [e-journal], 150, 119790. doi: 10.1016/j.techfore.2019.119790.
Capgemini, 2018. Industry 4.0 Maturity Model – Mirroring today to sprint into the future. [online] Available at: < https://www.capgemini.com/fi-en/2018/09/industry-4-0-maturity-model-mirroring-today-to-sprint-into-the-future/ > [Accessed 10 May 2019].
Dan, J., 2017. LNS research. [online] Available at: < https://blog.lnsresearch.com/quality40 > [Accessed 05 May 2019].
European Automobile Manufacturers Association (ACEA), 2018. EU Motor Vehicle Production. [online] Available at: < https://www.acea.be/statistics/article/motor-vehicle-production-in-the-eu > [Accessed 20 Juny 2020].
European Commision, 2019. Integration of Digital Technology: DESI Report. Brussels: European Commision.
Facchini, F., Oleśków-Szłapka, J., Ranieri, L. and Urbinati, A., 2020. A Maturity Model for Logistics 4.0: An Empirical Analysis and a Roadmap for Future Research. Sustainability [e-journal], 12(1), pp.1-18. doi: 10.3390/su12010086.
Felch, V., Asdecker, B. and Sucky, E., 2019. Maturity Models in the Age of Industry 4.0 – Do the Available Models Correspond to the Needs of Business Practice? In: Tung Bui, ed. 52nd Hawaii International Conference on System Sciences. Maui, Hawaii, 08 - 11 January 2019. Honolulu: HICSS. pp.5165-5174. doi: 10.24251/hicss.2019.620.
Geissbauer, R., Vedsø, J. and Schrauf, S., 2016. A Strategist’s Guide to Industry 4.0. Srategy + Business, 83(3), pp.10-18.
Grieger, M. and Ludwig, A., 2019. On the move towards customer-centric business models in the automotive industry - a conceptual reference framework of shared automotive service systems. Electronic Markets [e-journal], 29(3), pp.473-500. doi: 10.1007/s12525-018-00327-6.
Hevner, A., March, S. and Park, J.R.S., 2004. Design science in information systems research. MIS Quarterly [e-journal], 28(1), pp.75-105. doi: 10.2307/25148625.
Konrad, K. and Stagl, S., 2018. Competitiveness of the European automotive manufacturing industry. Berlin: Institute for Innovation and Technology.
Krubasik, S., Dirlea, V., Kidambi, R. and Sachseneder, C., 2017. A.T.Kearney. [online] Available at: < https://www.atkearney.com/industrial-goods-services/article/?/a/quality-4-0-preventive-holistic-future-proof > [Accessed 28 May 2019].
Lichtblau, K., Stich, V., Bertenrath, R., Blum, M., Bleider, M., Millack, A., Schmitt, K., Schmitz, E. and Schröter, M., 2015. Industrie 4.0 Readiness. Cologne: Aachen University.
Llopis-Albert, C., Rubio, F. and Valero, F., 2021. Impact of digital transformation on the automotive industry. Technological Forecasting and Social Change [e-journal], 162, 120343. doi: 10.1016/j.techfore.2020.120343.
Markulik, Š., Sinay, J. and Pa?aiová, H., 2019. Quality Assurance in the Automotive Industry and Industry 4.0. In: D. Cagáňová, M. Balog, L. Knap?íková, J. Sociar and S. Mezarcioz, eds. 2019. Smart Technology Trends in Industrial and Business Management. Switzerland: Springer. pp.217-225. doi: 10.1007/978-3-319-76998-1_15.
Mohelska, H. and Sokolova, M., 2018. Management Approaches for Industry 4.0 – The Organizational Culture Perspective. Technological and Economic Development of Economy [e-journal], 24(6), pp.2225-2240. doi: 10.3846/tede.2018.6397.
Nagyová, A., Pa?aiová, H., Gobanová, A. and Turisová, R., 2019. An Empirical Study of Root-Cause Analysis in Automotive Supplier Organisation. Quality Innovation Prosperity [e-journal], 23(2), pp.34-45. doi: 10.12776/qip.v23i2.1243.
Organisation for Economic Cooperation and Development (OECD), 2019. OECD Economic Surveys: Slovac Republic 2019. OECD.
Pereira, A. and Romero, F., 2017. A review of the meanings and the implications of the Industry 4.0 concept. Procedia Manufacturing [e-journal], 13, pp.1206-1214. doi: 10.1016/j.promfg.2017.09.032.
PricewaterhouseCoopers (PwC), 2016. Industry 4.0 Self Assessment. [online] Available at: < https://i40-self-assessment.pwc.nl/i40/landing/ > [Accessed 05 March 2019].
Radziwill, N., 2018. Let’s Get Digital: The many ways the fourth industrial revolution is reshaping the way we think about quality. Quality Progress, pp.24-29.
Rachinger, M., Rauter, R., Müller, C., Vorraber, W. and Schirgi, E., 2019. Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management [e-journal], 30(8), pp.1143-1160. doi: 10.1108/JMTM-01-2018-0020.
Rockwell Automation, 2014. The Connected Enterprise Maturity Model. Rockwell Automation.
Sanders, A., Elangeswaran, C. and Wulfsberg, J.P., 2016. Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management [e-journal], 9(3), pp.811-833. doi: 10.3926/jiem.1940.
Schumacher, A., Erol, S. and Sihn, W., 2016. A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. Procedia CIRP [e-journal], 52, pp.161-166. doi: 10.1016/j.procir.2016.07.040.
Slimák, I. and Zgodavová, K., 2011. Focus on Sucess. Quality Innovation Prosperity [e-journal], 15(1), pp.1-4. doi: 10.12776/qip.v15i1.36.
Slovak Investment and trade development agency (SARIO), 2018. Automotive Sector in Slovakia. Bratislava: SARIO.
Tká?, M., Verner, R. and Tká?, M., 2019. Perception of trust building mechanisms in EU countries. In: P. Doucek, C. Chroust and V. Oškrdal, eds., IDIMT-2019: Proceedings of the 27th Interdisciplinary Information Management Talks. Kutná Hora, Czech Republic, 04 - 06 September 2019. Linz: TRAUNER Verlag. pp.275-283.
Veile, J., Kiel, D., Muller, J. and Voigt, K., 2019. Lessons learned from Industry 4.0 implementation in the German manufacturing industry. Journal of Manufacturing Technology Management [e-journal], 21p. doi: 10.1108/jmtm-08-2018-0270.
Weber, C., Königsberger, J., Kassner, L. and Mitschang, B., 2017. M2DDM – A Maturity Model for Data-Driven Manufacturing. Procedia CIRP [e-journal], 63, pp.173-178. doi: 10.1016/j.procir.2017.03.309.
Wellner, P., Manolian, A.H. and Laaper, S., 2018. Distinctive traits of digital frontrunners in manufacturing. Deloitte.Insigts [online] 23 August 2018. Available at: < https://www2.deloitte.com/insights/us/en/focus/industry-4-0/digital-leaders-in-manufacturing-fourth-industrial-revolution.html > [Accessed 12 December 2018].
World Economic Forum (WEF), 2018. Readiness for the Future of Production. Geneva: WEF.
Zgodavová, K., 2002. Factors of intensive product and service quality improvement. Ekonomický ?asopis, 50(6), pp.1005-1021.
Zgodavova, K., Hudec, O. and Palfy, P., 2017. Culture of quality: insigth into foreign organisations in Slovakia. Total Quality Management & Business Excellence [e-journal], 28(9-10), pp.1-22. doi: 10.1080/14783363.2017.1309120.
Asdecker, B. and Felch, V., 2018. Development of an Industry 4.0 maturity model for the delivery process in supply chains. Journal of Modelling in Management [e-journal], 13(4), pp.840-883. doi: 10.1108/JM2-03-2018-0042.
Athanasopoulou, A., Reuver, M., Nikou, S. and Bouwman, H., 2019. What technology enabled services impact business models in the automotive industry? An exploratory study. Futures [e-journal], 109, pp.73-83. doi: 10.1016/j.futures.2019.04.001.
Bakertilly, 2019. Industry 4.0 and the Industrial Internet of Things (IIoT). [online] Available at: < https://bakertilly.com/industry-4.0/ > [Accessed 09 January 2020].
Becker, J., Knackstedt, R. and Pöppelbuß, J., 2009. Developing Maturity Models for IT Management: A Procedure Model and its Application for IT Management. Business & Information Systems Engineering [e-journal], 1(3), pp.213-222. doi: 10.1007/11576-009-0167-9.
Berger, R., 2014. Industry 4.0: The New Industrial Revolution. Munich: Operations Strategy Competence Center.
Bibby, L. and Dehe, B., 2018. Defining and assessing industry 4.0 maturity levels– case of the defence sector. Production Planning & Control, 29(12), pp.1030-1043.
Boyes, H., Hallaq, B., Cunningham, J. and Watson, T., 2018. The industrial internet of things (IIoT): An analysis framework. Computers in Industry [e-journal], 101, pp.1-12. doi: 10.1016/j.compind.2018.04.015.
Buchi, G., Cugno, M. and Castagnoli, R., 2020. Smart factory performance and Industry 4.0. Technological Forecasting and Social Change [e-journal], 150, 119790. doi: 10.1016/j.techfore.2019.119790.
Capgemini, 2018. Industry 4.0 Maturity Model – Mirroring today to sprint into the future. [online] Available at: < https://www.capgemini.com/fi-en/2018/09/industry-4-0-maturity-model-mirroring-today-to-sprint-into-the-future/ > [Accessed 10 May 2019].
Dan, J., 2017. LNS research. [online] Available at: < https://blog.lnsresearch.com/quality40 > [Accessed 05 May 2019].
European Automobile Manufacturers Association (ACEA), 2018. EU Motor Vehicle Production. [online] Available at: < https://www.acea.be/statistics/article/motor-vehicle-production-in-the-eu > [Accessed 20 Juny 2020].
European Commision, 2019. Integration of Digital Technology: DESI Report. Brussels: European Commision.
Facchini, F., Oleśków-Szłapka, J., Ranieri, L. and Urbinati, A., 2020. A Maturity Model for Logistics 4.0: An Empirical Analysis and a Roadmap for Future Research. Sustainability [e-journal], 12(1), pp.1-18. doi: 10.3390/su12010086.
Felch, V., Asdecker, B. and Sucky, E., 2019. Maturity Models in the Age of Industry 4.0 – Do the Available Models Correspond to the Needs of Business Practice? In: Tung Bui, ed. 52nd Hawaii International Conference on System Sciences. Maui, Hawaii, 08 - 11 January 2019. Honolulu: HICSS. pp.5165-5174. doi: 10.24251/hicss.2019.620.
Geissbauer, R., Vedsø, J. and Schrauf, S., 2016. A Strategist’s Guide to Industry 4.0. Srategy + Business, 83(3), pp.10-18.
Grieger, M. and Ludwig, A., 2019. On the move towards customer-centric business models in the automotive industry - a conceptual reference framework of shared automotive service systems. Electronic Markets [e-journal], 29(3), pp.473-500. doi: 10.1007/s12525-018-00327-6.
Hevner, A., March, S. and Park, J.R.S., 2004. Design science in information systems research. MIS Quarterly [e-journal], 28(1), pp.75-105. doi: 10.2307/25148625.
Konrad, K. and Stagl, S., 2018. Competitiveness of the European automotive manufacturing industry. Berlin: Institute for Innovation and Technology.
Krubasik, S., Dirlea, V., Kidambi, R. and Sachseneder, C., 2017. A.T.Kearney. [online] Available at: < https://www.atkearney.com/industrial-goods-services/article/?/a/quality-4-0-preventive-holistic-future-proof > [Accessed 28 May 2019].
Lichtblau, K., Stich, V., Bertenrath, R., Blum, M., Bleider, M., Millack, A., Schmitt, K., Schmitz, E. and Schröter, M., 2015. Industrie 4.0 Readiness. Cologne: Aachen University.
Llopis-Albert, C., Rubio, F. and Valero, F., 2021. Impact of digital transformation on the automotive industry. Technological Forecasting and Social Change [e-journal], 162, 120343. doi: 10.1016/j.techfore.2020.120343.
Markulik, Š., Sinay, J. and Pa?aiová, H., 2019. Quality Assurance in the Automotive Industry and Industry 4.0. In: D. Cagáňová, M. Balog, L. Knap?íková, J. Sociar and S. Mezarcioz, eds. 2019. Smart Technology Trends in Industrial and Business Management. Switzerland: Springer. pp.217-225. doi: 10.1007/978-3-319-76998-1_15.
Mohelska, H. and Sokolova, M., 2018. Management Approaches for Industry 4.0 – The Organizational Culture Perspective. Technological and Economic Development of Economy [e-journal], 24(6), pp.2225-2240. doi: 10.3846/tede.2018.6397.
Nagyová, A., Pa?aiová, H., Gobanová, A. and Turisová, R., 2019. An Empirical Study of Root-Cause Analysis in Automotive Supplier Organisation. Quality Innovation Prosperity [e-journal], 23(2), pp.34-45. doi: 10.12776/qip.v23i2.1243.
Organisation for Economic Cooperation and Development (OECD), 2019. OECD Economic Surveys: Slovac Republic 2019. OECD.
Pereira, A. and Romero, F., 2017. A review of the meanings and the implications of the Industry 4.0 concept. Procedia Manufacturing [e-journal], 13, pp.1206-1214. doi: 10.1016/j.promfg.2017.09.032.
PricewaterhouseCoopers (PwC), 2016. Industry 4.0 Self Assessment. [online] Available at: < https://i40-self-assessment.pwc.nl/i40/landing/ > [Accessed 05 March 2019].
Radziwill, N., 2018. Let’s Get Digital: The many ways the fourth industrial revolution is reshaping the way we think about quality. Quality Progress, pp.24-29.
Rachinger, M., Rauter, R., Müller, C., Vorraber, W. and Schirgi, E., 2019. Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management [e-journal], 30(8), pp.1143-1160. doi: 10.1108/JMTM-01-2018-0020.
Rockwell Automation, 2014. The Connected Enterprise Maturity Model. Rockwell Automation.
Sanders, A., Elangeswaran, C. and Wulfsberg, J.P., 2016. Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management [e-journal], 9(3), pp.811-833. doi: 10.3926/jiem.1940.
Schumacher, A., Erol, S. and Sihn, W., 2016. A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. Procedia CIRP [e-journal], 52, pp.161-166. doi: 10.1016/j.procir.2016.07.040.
Slimák, I. and Zgodavová, K., 2011. Focus on Sucess. Quality Innovation Prosperity [e-journal], 15(1), pp.1-4. doi: 10.12776/qip.v15i1.36.
Slovak Investment and trade development agency (SARIO), 2018. Automotive Sector in Slovakia. Bratislava: SARIO.
Tká?, M., Verner, R. and Tká?, M., 2019. Perception of trust building mechanisms in EU countries. In: P. Doucek, C. Chroust and V. Oškrdal, eds., IDIMT-2019: Proceedings of the 27th Interdisciplinary Information Management Talks. Kutná Hora, Czech Republic, 04 - 06 September 2019. Linz: TRAUNER Verlag. pp.275-283.
Veile, J., Kiel, D., Muller, J. and Voigt, K., 2019. Lessons learned from Industry 4.0 implementation in the German manufacturing industry. Journal of Manufacturing Technology Management [e-journal], 21p. doi: 10.1108/jmtm-08-2018-0270.
Weber, C., Königsberger, J., Kassner, L. and Mitschang, B., 2017. M2DDM – A Maturity Model for Data-Driven Manufacturing. Procedia CIRP [e-journal], 63, pp.173-178. doi: 10.1016/j.procir.2017.03.309.
Wellner, P., Manolian, A.H. and Laaper, S., 2018. Distinctive traits of digital frontrunners in manufacturing. Deloitte.Insigts [online] 23 August 2018. Available at: < https://www2.deloitte.com/insights/us/en/focus/industry-4-0/digital-leaders-in-manufacturing-fourth-industrial-revolution.html > [Accessed 12 December 2018].
World Economic Forum (WEF), 2018. Readiness for the Future of Production. Geneva: WEF.
Zgodavová, K., 2002. Factors of intensive product and service quality improvement. Ekonomický ?asopis, 50(6), pp.1005-1021.
Zgodavova, K., Hudec, O. and Palfy, P., 2017. Culture of quality: insigth into foreign organisations in Slovakia. Total Quality Management & Business Excellence [e-journal], 28(9-10), pp.1-22. doi: 10.1080/14783363.2017.1309120.
Authors
Sütőová, A., Šooš, Ľubomír, & Kóča, F. (2020). Learning Needs Determination for Industry 4.0 Maturity Development in Automotive Organisations in Slovakia. Quality Innovation Prosperity, 24(3), 122–139. https://doi.org/10.12776/qip.v24i3.1521
Copyright and license info is not available