A study has been carried out on one of the first generation automotive assembly plant in Nigeria on their current level of assembly operations, automation and how to migrate to the industry 4.0. In the process, a comprehensive review of disruptive technology in the automotive manufacturing sector was carried out to find out the level of disruptive technology in the global automotive manufacturing industries. It was discovered that the industry 4.0 technology is already fully operational in the key global automotive manufacturing and assembly plants. This has positively impacted the automotive manufacturing industries and it comes with many benefits like employability, technology advancement, increases in revenue to the industry, and decarburization of the environment. The research has shown that with the knowledge of maturity model for the adoption of industry 4.0 in the manufacturing process, the organization could determine their industry 4.0 level at every point in time and the adoption could begin from a section in the organization before expanding to other sections, units or department. There is a need for the Nigeria automotive industries to start to migrate to the industry 4.0 level from either the body welding operation or the paint shop.
KeywordsIndustry 4.0Disruptive TechnologyAutomotive IndustryManufactur-ing Technology and Robotics
Anthony, E. W. (2018). Reconsidering the Industrial Revolution: England and Wales. Journal of Interdisciplinary History, 49, 9-42. https://doi.org/10.1162/jinh_a_01230
Antoniolli, I., Guariente, P., Pereira, T., Ferreira, L. P., & Silva, F. J. G. (2017). Standardization and Optimization of an Automotive Components Production Line. Procedia Manufacturing, 13, 1120-1127. https://doi.org/10.1016/j.promfg.2017.09.173
Araújo, W. F. S., Silva, F. J. G., Campilho, R. D. S. G., & Matos, J. A. (2017). Manufacturing Cushions and Suspension Mats for Vehicle Seats: A Novel Cell Concept. International Journal of Advanced Manufacturing Technology, 90, 1539-1545. https://doi.org/10.1007/s00170-016-9475-6
Auboin, M., Bacchetta, M., Beverelli, C. et al. (2014). World Trade Report 2014: Trade and Development: Recent Trends and the Role of the WTO. https://www.wto.org/english/res_e/booksp_e/world_trade_report14_e.pdf
Bär, T. (2008). Flexibility Demands on Automotive Production and Their Effects on Virtual Production Planning. In Proceedings of the 2nd CIRP Conference on Assembly Technologies and Systems (Toronto, Canada). YUMPU.
Barbosa, B., Pereira, M. T., Silva, F. J. G., & Campilho, R. D. S. G. (2017). Solving Quality Problems in Tyre Production Preparation Process: A Practical Approach. Procedia Manufacturing, 11, 1239-1246. https://doi.org/10.1016/j.promfg.2017.07.250
Batth, R. S., Nayyar, A., & Nagpal, A. (2018). Internet of Robotic Things: Driving Intelligent Robotics of Future-Concept, Architecture, Applications and Technologies. In 2018 4th International Conference on Computing Sciences (ICCS). IEEE. https://doi.org/10.1109/ICCS.2018.00033
Bauernhansl, T., Ten Hompel, M., & Vogel-Heuser, B. (2014). Industry 4.0 in Production, Automation und Logistic: Technologies-Migration. Springer. https://doi.org/10.1007/978-3-658-04682-8
Costa, M. J. R., Gouveia, R. M., Silva, F. J. G., & Campilho, R. D. S. G. (2018). How to Solve Quality Problems by Advanced Fully-Automated Manufacturing Systems. The International Journal of Advanced Manufacturing Technology, 94, 3041-3063. https://doi.org/10.1007/s00170-017-0158-8
Costa, R. J. S., Silva, F. J. G., & Campilho, R. D. S. G. (2017b). A Novel Concept of Agile Assembly Machine for Sets Applied in the Automotive Industry. The International Journal of Advanced Manufacturing Technology, 91, 4043-4054. https://doi.org/10.1007/s00170-017-0109-4
Costa, T., Silva, F. J. G., & Ferreira, L. P. (2017a). Improve the Extrusion Process in Tire Production Using Six-Sigma Methodology. Procedia Manufacturing, 13, 1104-1111. https://doi.org/10.1016/j.promfg.2017.09.171
David, O. (2015). African & Nigerian Automotive Industry Market Journal 2015 and Beyond. https://www.linkedin.com/pulse/african-nigerian-automotive-industry-market-journal-2015-oladele
Davis, J., Edgar, T., Porter, J., Bernaden, J., & Sarli, M. (2012). Smart Manufacturing, Manufacturing Intelligence and Demand-Dynamic Performance. Computers & Chemical Engineering, 47, 145-156. https://doi.org/10.1016/j.compchemeng.2012.06.037
Deloitte (2016). Deloitte Africa Automotive Insights: Navigating the African Automotive Sector: Ethiopia, Kenya and Nigeria. https://www2.deloitte.com/content/dam/Deloitte/za/Documents/deloitteafrica/ZA_Deloitte-Africa-automotive-insights-Ethiopia-Kenya-Nigeria-Apr16-2017.pdf
Fisel, J., Exner, Y., Stricker, N., & Lanze, G. (2018). Variant Flexibility in Assembly Line Balancing under the Premise of Feasibility Robustness. Procedia CIRP, 72, 774-779. https://doi.org/10.1016/j.procir.2018.03.049
Gottschalk, B., & Kalmbach, R. (2007). Mastering Automotive Challenge in Automotive Industry and Trade—Management. Kogan Page.
Hermann, M., Pentek, T., & Otto, B. (2016). Design Principles for Industrie 4.0 Scenarios. In 2016 49th Hawaii International Conference on System Sciences (HICSS). IEEE. https://doi.org/10.1109/HICSS.2016.488
Kim, S., & Jeong, B. (2007). Product Sequencing Problem in Mixed-Model Assembly Line to Minimize Unfinished Works. Computers & Industrial Engineering, 53, 206-214. https://doi.org/10.1016/j.cie.2007.06.011
Koren, Y., Wang, W., & Gu, X. (2017). Value Creation through Design for Scalability of Reconfigurable Manufacturing Systems. International Journal of Production Research, 55, 1227-1242. https://doi.org/10.1080/00207543.2016.1145821
Kusiak, A. (1990). Intelligent Manufacturing Systems. Prentice Hall Press.
Lee, J., Bagheri, B., & Kao, H.-A. (2015). A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems. Manufacturing Letters, 3, 18-23. https://doi.org/10.1016/j.mfglet.2014.12.001
Lu, Y. (2017). Industry 4.0: A Survey on Technologies, Applications and Open Research Issues. Journal of Industrial Information Integration, 6, 1-10. https://doi.org/10.1016/j.jii.2017.04.005
Magalhães, A. J. A., Silva, F. J. G., & Campilho, R. D. S. G. (2019). A Novel Concept of Bent Wires Sorting Operation between Workstations in the Production of Automotive Parts. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41, Article No. 25. https://doi.org/10.1007/s40430-018-1522-9
McFarlane, D., Sarma, S., Chirn, J. L., Wong, C. Y., & Ashton, K. (2003). Auto ID Systems and Intelligent Manufacturing Control. Engineering Applications of Artificial Intelligence, 16, 365-376. https://doi.org/10.1016/S0952-1976(03)00077-0
Moreira, B. M. D. N., Gouveia, R. M., Silva, F. J. G., & Campilho, R. D. S. G. (2017). A Novel Concept of Production and Assembly Processes Integration. Procedia Manufacturing, 11, 1385-1395. https://doi.org/10.1016/j.promfg.2017.07.268
Nayyar, A., & Kumar, A. (2020). A Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development. Springer. https://doi.org/10.1007/978-3-030-14544-6
Nourmohammadi, A., Eskandari, H., Fathi, M., & Bourani, M. R. (2018). An Integrated Model for Cost-Oriented Assembly Line Balancing and Parts Feeding with Supermarkets. Procedia CIRP, 72, 381-385. https://doi.org/10.1016/j.procir.2018.03.255
Nunes, P. M. S., & Silva, F. J. G. (2013). Increasing Flexibility and Productivity in Small Assembly Operations: A Case Study. In A. Azevedo (Ed.), Advances in Sustainable and Competitive Manufacturing Systems. Lecture Notes in Mechanical Engineering (pp. 329-340). Springer. https://doi.org/10.1007/978-3-319-00557-7_27
Rosa, C., Silva, F. J. G., Ferreir, L. P., Pereira, T., & Gouveia, R. (2018). Establishing Standard Methodologies to Improve the Production Rate of Assembly-Lines Used for Low Added-Value Products. Procedia Manufacturing, 17, 555-562. https://doi.org/10.1016/j.promfg.2018.10.096
Rösiö, C., Aslam, T., Srikanth, K. B., & Shetty, S. (2019). Towards an Assessment Criterion of Reconfigurable Manufacturing Systems within the Automotive Industry. Procedia Manufacturing, 28, 76-82. https://doi.org/10.1016/j.promfg.2018.12.013
Santos, R. F. L., Silva, F. J. G., Gouveia, R. M., Campilho, R. D. S. G. et al. (2018). The Improvement of an APEX Machine Involved in the Tyre Manufacturing Process. Procedia Manufacturing, 17, 571-578. https://doi.org/10.1016/j.promfg.2018.10.098
Stadnicka, D., & Litwin, P. (2019). Value Stream Mapping and System Dynamics Integration for Manufacturing Line Modelling and Analysis. International Journal of Production Economics, 208, 400-411. https://doi.org/10.1016/j.ijpe.2018.12.011
Sternatz, J. (2014). Enhanced Multi-Hoffmann Heuristic for Efficiently Solving Real-World Assembly Line Balancing Problems in Automotive Industry. European Journal of Operational Research, 235, 740-754. https://doi.org/10.1016/j.ejor.2013.11.005
Tang, H. H. (2017). Manufacturing System and Process Development for Vehicle Assembly. An SAE International Book. SAE.
Wang, S., Wan, J., Zhang, D., Li, D., & Zhang, C. (2016a). Towards Smart Factory for Industry 4.0: A Self-Organized Multi-Agent System with Big Data Based Feedback and Coordination. Computer Network, 101, 158-168. https://doi.org/10.1016/j.comnet.2015.12.017
Wang, S., Wan, Y., Li, D., & Zhang, C. (2016b). Implementing Smart Factory of Industries 4.0: An Outlook. International Journal of Distributed Sensor Networks, 12. https://doi.org/10.1155/2016/3159805