TÜRK LOJİSTİK FİRMALARINDAN BİRİNDE ENDÜSTRİ 4.0’A GEÇİŞ

Dördüncü Sanayi Devrimi (Endüstri 4.0) tüm sektörler için yeni bir çağdır ve akıllı tesislere geçiştir. Bu çalışmada, bir lojistik firmasında Endüstri 4.0 yaklaşımı; taşımacılık, depolama, yükleme/boşaltma ve bilgi hizmetleri birimlerinde incelenmiştir. Bu yaklaşımın amacı, Endüstri 4.0’ ın ilkelerini bu hizmet birimlerinde değerlendirmektir. Çalışmada, bu konulara odaklanan bir literatür çalışması sunulmuştur ve bu alanda lojistik firmalarını tasarlamak için gerekli temel ilkelere karar verilmiştir. Endüstri 4.0’a geçiş için önemli olan otonom taşıma, otonom stok yönetimi, 3D depolar, küresel kaynak planlama ve gerçek zamanlı rotalama gibi kriterlerin önceliklendirilmesi için bir bulanık yöntem kullanılmıştır ve yöntem, geçiş için gereklilikleri anlamaya yardımcı olmaktadır. Ayrıca, mevcut uygulamalar, fırsatlar ve öneriler, lojistik firması için sunulmuştur.

THE TRANSITION TO INDUSTRY 4.0 IN ONE OF THE TURKISH LOGISTICS COMPANY

Fourth Industry Revolution (Industry 4.0) is a new era for all sectors and a transition to smart facilities. In this paper, Industry 4.0 approach at a logistics company is examined in transportation, warehousing, loading/unloading and information service units. The purpose of this approach is to evaluate Industry 4.0 principles in these service units. In this study, a literature survey focusing on these issues is presented and the key principles to design the logistics companies in this field are determined. The fuzzy method is used to prioritize criteria, which are important for transition to Industry 4.0 such as autonomous transportation, autonomous inventory management, 3D warehouse, global resource planning, real time routing and provides to understand the transition requirements. Additionally, current applications, opportunities and suggestions for the logistics company are presented.

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  • [1] Drath, R., Horch ,A. (2014) . Industrie 4.0: Hit or Hype? [Industry Forum]. Industrial Electronics Magazine, IEEE 8, 56-58.
  • [2] Hermann, M., Pentek, T., Otto, B. (2015). Design principles for Industrie 4.0 scenarios: a literature review. Technische Universität Dortmund, Dortmund.
  • [3] Li, X., Li, D., Wan, J., Vasilakos, A.V. (2015). A review of industrial wireless networks in the context of Industry 4.0, Wireless Networks 23 (1):1-19.
  • [4] Posada, J., Toro, C., Barandiran, I., Oyarzun, D., Stricker, D., Amicis, R., Vallarino, I., (2015). Visual computing as a key enabling technology for Industrie 4.0 and industrial internet, IEEE Comput. Graphics Appl. 35(2): 26-40.
  • [5] Singer, P. (2016). Are you ready for Industry 4.0? Solid State Technol. 58 (8) 2-2.
  • [6] Warfield, J. (2007). Systems science serves enterprise integration: a tutorial, Enterp. Inf. Syst. 3(4):409-424.
  • [7] Xu, L. (2011). Enterprise system: state-of-art and future trends, IEEE Trans. Ind. Inf. 7(4) 630-640.
  • [8] Bagheri, B., Yang, S., Kao, H.-A., Lee, J. (2015.) Cyber-physical Systems Architecture for Self-Aware Machines in Industry 4.0 Environment. IFAC Papers Online 48, 1622-1627.
  • [9] Harrison, R., Vera, D., Ahmad, B. (2016). Engineering methods and tools for cyber-physical automation systems, Proc. IEEE 104 (5):973-985.
  • [10] Shafiq, S.L, Sanin, C., Toro, C., Szczerbicki, E., (2015). Virtual engineering object: toward experience-based design and manufacturing for Industry 4.0, Cybern. Syst. 46 (1-2):35-50.
  • [11] Chen, Z., Xing, M., (2015). Upgrading of textile manufacturing based on Industry 4.0, 5th International Conference on Advanced Design and Manufacturing Engineering, Atlantis Press.
  • [12] Oses, N. Legarretaetxebarria, A., Quartulli, M., Garcia, I., Serrano, M. (2016). Uncertainty reduction in measuring and verification of energy savings by statistical learning in manufacturing environments, Int. J. Interact. Des. Manuf. (IJIDEM) 10(3):1-9.
  • [13] Sanders, A. Elangeswaran, C., Wulfsberg, J. (2016). Industry 4.0 implies lean manufacturing: research activities in Industry 4.0 function as enablers for lean manufacturing. J. Ind. Eng. Manage. 9 (3):811-833.
  • [14] Wang, S., Wan, J., Shang, D., Li, D., Zhang, C. (2016). Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination, Compt: Networks 101 158-168.
  • [15] Long, F., Zeiler, P., Bertsche, B. (2016). Modelling the production systems in industry 4.0 and their availability with high-level Petri nets, IFAC- Papers Online 49 (12):145-150.
  • [16] Gorecky, D., Schmitt, M., Loskyll, M., Zuhlke, D. (2014). Human-machine interaction in the Industry 4.0 era, in: 2014 12th IEEE International Conference on Industrial Informatics (INDIN), IEEE, 289-294.
  • [17] Thoben, K.D., Busse, M., Denkena, B., Gausemeier, J. (2016). Editorial: System- integrated Intelligence- new challenges for product and production engineering in the context of Industry 4.0, Procedia Technol. 15 1-4.
  • [18] Lasi, H. Fetteke, H.G., Kemper, T., Feld, M. (2014). Industry 4.0, Bus. Inf. Syst. Eng. 6(4):239.
  • [19] Roblek, V., Mesko, M., Krapez, A. (2016). A complex view of Industry 4.0, SAGE Open 6(2).
  • [20] Hofmann, E. & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics, Computers in Industry 89:23-24.
  • [21] Witkowski, K. (2017). Internet of Things, Big Data, Industry 4.0- Innovative Solutions in Logistics and Supply Chains Management, 7th International Conference on Engineering, Project and Production Management, 182 :763-769.
  • [22] Sun, C. (2012). Application of RFID Technology for Logistics on Internet of Things, AASRI Procedia 1, 105-111.
  • [23] Obitko, M., Jirkovský, V., Bezdíček, J. (2013). Big data challenges in industrial automation. In: Marik, V., Lastra, J.L., Skobelev, P. (eds.) HoloMAS 2013. LNCS, 8062:305–316. Springer, Heidelberg.
  • [24] http://www.ekol.com/en/services/, (2017.09.15).