Current Status of Industry 4.0 in Material Handling Automation and In-house Logistics

Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

Abstract:

In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3566333

References:

[1] Kagermann, V. H., Lukas, W.-D., & Wahlster, W. (2011). Industrie 4 0 Mit dem Internet der Dinge auf dem Weg zur vierten industriellen Revolution 2. Retrieved from VDI nachrichten website: http://www.wolfgang-wahlster.de/wordpress/wp-content/uploads/Industrie_4_0_Mit_dem_Internet_der_Dinge_auf_dem_Weg_zur_vierten_industriellen_Revolution_2.pdf
[2] Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, Vol. 6, 1–10. https://doi.org/10.1016/j.jii.2017.04.005
[3] Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, Vol. 117, 408–425. https://doi.org/10.1016/j.psep.2018.05.009
[4] Li, X., Li, D., Wan, J., Vasilakos, A. V., Lai, C. F., & Wang, S. (2017). A review of industrial wireless networks in the context of industry 4.0. Wireless networks, 23(1), 23-41. https://doi.org/10.1007/s11276-015-1133-7
[5] Givehchi, O., Trsek, H., & Jasperneite, J. (2013, September). Cloud computing for industrial automation systems—A comprehensive overview. In 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA) (pp. 1-4). IEEE. https://ieeexplore.ieee.org/document/6648080
[6] Bahrin, M. A. Kamarul, Othman, M. F., Nor Azli, N. H., & Talib, M. F. (2016). Industry 4.0: A Review on Industrial Automation and Robotic. Jurnal Teknologi, 78(6–13). https://doi.org/10.11113/jt.v78.9285
[7] Wang, L., & Wang, G. (2016). Big data in cyber-physical systems, digital manufacturing and industry 4.0. International Journal of Engineering and Manufacturing (IJEM), 6(4), 1-8. https://doi.org/10.5815/ijem.2016.04.01
[8] Fraga-Lamas, P., Fernández-Caramés, T. M., Blanco-Novoa, Ó., & Vilar-Montesinos, M. A. (2018). A review on industrial augmented reality systems for the industry 4.0 shipyard. IEEE Access, 6, 13358-13375. https://doi.org/10.1109/ACCESS.2018.2808326
[9] Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T. (2017). Intelligent manufacturing in the context of industry 4.0: a review. Engineering, 3(5), 616-630. https://doi.org/10.1016/J.ENG.2017.05.015
[10] Uhlemann, T. H. J., Lehmann, C., & Steinhilper, R. (2017). The digital twin: Realizing the cyber-physical production system for industry 4.0. Procedia Cirp, 61, 335-340. https://doi.org/10.1016/j.procir.2016.11.152
[11] Ngo, T. D., Kashani, A., Imbalzano, G., Nguyen, K. T., & Hui, D. (2018). Additive manufacturing (3D printing): A review of materials, methods, applications and challenges. Composites Part B: Engineering, 143, 172-196. https://doi.org/10.1016/j.compositesb.2018.02.012
[12] Pereira, A. C., & Romero, F. (2017). A review of the meanings and the implications of the Industry 4.0 concept. Procedia Manufacturing, Vol. 13, 1206–1214. https://doi.org/10.1016/j.promfg.2017.09.032
[13] Strandhagen, J. O., Vallandingham, L. R., Fragapane, G., Strandhagen, J. W., Stangeland, A. B. H., & Sharma, N. (2017). Logistics 4.0 and emerging sustainable business models. Advances in Manufacturing, 5(4), 359–369. https://doi.org/10.1007/s40436-017-0198-1
[14] Tjahjono, B., Esplugues, C., Ares, E., & Pelaez, G. (2017). What does Industry 4.0 mean to Supply Chain? Procedia Manufacturing, 13, 1175–1182. https://doi.org/10.1016/j.promfg.2017.09.191
[15] Kagermann, V. H. (2014). Change Through Digitization—Value Creation in the Age of Industry 4.0. Management of Permanent Change, 23–45. https://doi.org/10.1007/978-3-658-05014-6_2
[16] Edirisuriya, A., Weerabahu, S., & Wickramarachchi, R. (2018). Applicability of Lean and Green Concepts in Logistics 4.0: A Systematic Review of Literature. 2018 International Conference on Production and Operations Management Society (POMS). https://doi.org/10.1109/poms.2018.8629443
[17] LI, F., Sijun, L., & Cui, Y. (2018). Logistics Planning and Its Applications for Engine Plant under ‘Industry 4.0.’ SAE Technical Paper Series. https://doi.org/10.4271/2018-01-1205
[18] Hofmann, E., & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, 23–34. https://doi.org/10.1016/j.compind.2017.04.002
[19] Kayikci, Y. (2018). Sustainability impact of digitization in logistics. Procedia Manufacturing, 21, 782–789. https://doi.org/10.1016/j.promfg.2018.02.184
[20] Barreto, L., Amaral, A., & Pereira, T. (2017). Industry 4.0 implications in logistics: an overview. Procedia Manufacturing, 13, 1245–1252. https://doi.org/10.1016/j.promfg.2017.09.045
[21] Martin, J., May, S., Endres, S., & Cabanes, I. (2017). Decentralized Robot-Cloud Architecture for an Autonomous Transportation System in a Smart Factory. SEMANTICS Workshops.
[22] Lutz, M., Verbeek, C., & Schlegel, C. (2016). Towards a robot fleet for intra-logistic tasks: Combining free robot navigation with multi-robot coordination at bottlenecks. 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA). https://doi.org/10.1109/etfa.2016.7733602
[23] Bechtsis, D., Tsolakis, N., Vouzas, M., & Vlachos, D. (2017). Industry 4.0: Sustainable material handling processes in industrial environments. Computer Aided Chemical Engineering, 2281–2286. https://doi.org/10.1016/b978-0-444-63965-3.50382-2
[24] Naidoo, N., Bright, G., & Stopforth, R. (2019). A Distributed Framework for Programming the Artificial Intelligence of Mobile Robots in Smart Manufacturing Systems. 2019 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA). https://doi.org/10.1109/robomech.2019.8704788
[25] Hussnain, A., Ferrer, B. R., & Lastra, J. L. M. (2018). Towards the deployment of cloud robotics at factory shop floors: A prototype for smart material handling. 2018 IEEE Industrial Cyber-Physical Systems (ICPS). https://doi.org/10.1109/icphys.2018.8387635
[26] Zhou, W., Piramuthu, S., Chu, F., & Chu, C. (2017). RFID-enabled flexible warehousing. Decision Support Systems, 98, 99–112. https://doi.org/10.1016/j.dss.2017.05.002
[27] Zou, O., & Zhong, R. Y. (2018). Automatic Logistics in a Smart Factory using RFID-enabled AGVs. 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). https://doi.org/10.1109/aim.2018.8452349
[28] Mehami, J., Nawi, M., & Zhong, R. Y. (2018). Smart automated guided vehicles for manufacturing in the context of Industry 4.0. Procedia Manufacturing, 26, 1077–1086. https://doi.org/10.1016/j.promfg.2018.07.144
[29] Müller, C., Grunewald, M., & Spengler, T. S. (2016). Redundant configuration of automated flow lines based on “Industry 4.0”-technologies. Journal of Business Economics, 87(7), 877–898. https://doi.org/10.1007/s11573-016-0831-7
[30] Ghafoorpoor Yazdi, P., Azizi, A., & Hashemipour, M. (2019). A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs. Sustainability, 11(5), 1454. https://doi.org/10.3390/su11051454
[31] Delfmann, W., Ten Hompel, M., Kersten, W., Schmidt, T., & Stölzle, W. (2018). Logistics as a science: Central research questions in the era of the fourth industrial revolution. Logistics Research, 11(9), 1–13. https://doi.org/doi:10.23773/2018_9