3,698
Views
74
CrossRef citations to date
0
Altmetric
Articles

The architectural framework of a cyber physical logistics system for digital-twin-based supply chain control

, &
Pages 5721-5742 | Received 25 Feb 2020, Accepted 22 Jun 2020, Published online: 06 Jul 2020

References

  • Adolphs, P., S. Auer, H. Bedenbender, M. Billmann, M. Hankel, R. Heidel, M. Hoffmeister, et al. 2016. Structure of the Administration Shell. ZVEI and VDI, Status Report.
  • Alam, K. M., and A. El Saddik. 2017. “C2PS: A Digital Twin Architecture Reference Model for the Cloud-Based Cyber-Physical Systems.” IEEE Access 5: 2050–2062. doi:10.1109/ACCESS.2017.2657006.
  • Barreto, L., A. Amaral, and T. Pereira. 2017. “Industry 4.0 Implications in Logistics: An Overview.” Procedia Manufacturing 13: 1245–1252. doi:10.1016/j.promfg.2017.09.045.
  • Bedenbender, H., M. Billmann, U. Epple, T. Hadlich, M. Hankel, R. Heidel, O. Hillermeier, et al. 2017. Examples of the Asset Administration Shell for Industrie 4.0 Components – Basic Part. ZVEI White Paper.
  • Ben-Ammar, O., B. Bettayeb, and A. Dolgui. 2019. “Integrated Production Planning and Quality Control for Linear Production Systems Under Uncertainties of Cycle Time and Finished Product Quality.” International Journal of Production Research, 1–17. doi:10.1080/00207543.2019.1613580.
  • da Cruz, M. A. A., J. J. P. C. Rodrigues, J. Al-Muhtadi, V. V. Korotaev, and V. H. C. de Albuquerque. 2018. “A Reference Model for Internet of Things Middleware.” IEEE Internet of Things Journal 5 (2): 871–883. doi:10.1109/JIOT.2018.2796561.
  • Deb, K., A. Pratap, S. Agarwal, and T. Meyarivan. 2002. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6 (2): 182–197. doi:10.1109/4235.996017.
  • Ding, K., F. T. Chan, X. Zhang, G. Zhou, and F. Zhang. 2019. “Defining a Digital Twin-based Cyber-Physical Production System for Autonomous Manufacturing in Smart Shop Floors.” International Journal of Production Research 57 (20): 6315–6334.
  • Dolgui, A., D. Ivanov, and M. Rozhkov. 2020. “Does the Ripple Effect Influence the Bullwhip Effect? An Integrated Analysis of Structural and Operational Dynamics in the Supply Chain.” International Journal of Production Research 58 (5): 1285–1301. doi:10.1080/00207543.2019.1627438.
  • Dolgui, A., D. Ivanov, S. P. Sethi, and B. Sokolov. 2019. “Scheduling in Production, Supply Chain and Industry 4.0 Systems by Optimal Control: Fundamentals, State-of-the-Art and Applications.” International Journal of Production Research 57 (2): 411–432. doi:10.1080/00207543.2018.1442948.
  • Dolgui, A., and C. Prodhon. 2007. “Supply Planning Under Uncertainties in MRP Environments: A State of the Art.” Annual Reviews in Control 31 (2): 269–279. doi:10.1016/j.arcontrol.2007.02.007.
  • Dorst, W. 2015. Umsetzungsstrategie Industrie 4.0: Ergebnisbericht der Plattform Industrie 4.0. Bitkom Research GmbH.
  • Fragapane, G., D. Ivanov, M. Peron, F. Sgarbossa, and J. O. Strandhagen. 2020. “Increasing Flexibility and Productivity in Industry 4.0 Production Networks with Autonomous Mobile Robots and Smart Intralogistics.” Annals of Operations Research, 1–19. doi:10.1007/s10479-020-03526-7.
  • Frazzon, E. M., A. Albrecht, M. Pires, E. Israel, M. Kück, and M. Freitag. 2018. “Hybrid Approach for the Integrated Scheduling of Production and Transport Processes Along Supply Chains.” International Journal of Production Research 56 (5): 2019–2035. doi:10.1080/00207543.2017.1355118.
  • Fujimoto, R. M. 2016. “Research Challenges in Parallel and Distributed Simulation.” ACM Transactions on Modeling and Computer Simulation 26 (4): 1–29. doi:10.1145/2866577.
  • Gabor, T., L. Belzner, M. Kiermeier, M. T. Beck, and A. Neitz. 2016. “A Simulation-based Architecture for Smart Cyber-physical Systems.” 2016 IEEE international conference on Autonomic Computing (ICAC), July 374–379. doi: https://doi.org/10.1109/ICAC.2016.29
  • Garraghan, P., D. McKee, X. Ouyang, D. Webster, and J. Xu. 2015. “SEED: A Scalable Approach for Cyber-Physical System Simulation.” IEEE Transactions on Services Computing 9 (2): 199–212. doi:10.1109/TSC.2015.2491287.
  • Giannakis, M., and M. Louis. 2011. “A Multi-Agent Based Framework for Supply Chain Risk Management.” Journal of Purchasing and Supply Management 17 (1): 23–31. doi:10.1016/j.pursup.2010.05.001.
  • Grieves, M. 2014. Digital Twin: Manufacturing Excellence Through Virtual Factory Replication. White paper: 1–7.
  • Hankel, M., and B. Rexroth. 2015. The Reference Architectural Model Industrie 4.0 (RAMI 4.0). ZVEI.
  • International Electronical Commission. 2016. Industrial-process measurement, control and automation - Digital factory framework - Part 1: General principles (IEC TS 62832-1:2016). https://webstore.iec.ch/publication/33023.
  • Ivanov, D. 2018. Structural Dynamics and Resilience in Supply Chain Risk Management. Springer International Publishing. doi:10.1007/978-3-319-69305-7.
  • Ivanov, D., and A. Dolgui. 2020. “A Digital Supply Chain Twin for Managing the Disruption Risks and Resilience in the Era of Industry 4.0.” Production Planning & Control, 1–14. doi:10.1080/09537287.2020.1768450.
  • Ivanov, D., A. Dolgui, A. Das, and B. V. Sokolov. 2019a. “Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility.” In Handbook of Ripple Effects in the Supply Chain, edited by C. C. Price, 209–332. Cham: Springer.
  • Ivanov, D., A. Dolgui, and B. Sokolov. 2019b. “The Impact of Digital Technology and Industry 4.0 on the Ripple Effect and Supply Chain Risk Analytics.” International Journal of Production Research 57 (3): 829–846. doi:10.1080/00207543.2018.1488086.
  • Ivanov, D., A. Dolgui, B. V. Sokolov, F. Werner, and M. Ivanova. 2016. “A Dynamic Model and an Algorithm for Short-term Supply Chain Scheduling in the Smart Factory Industry 4.0.” International Journal of Production Research 54 (2): 386–402. doi:10.1080/00207543.2014.999958.
  • Ivanov, D., S. Sethi, A. Dolgui, and B. Sokolov. 2018. “A Survey on Control Theory Applications to Operational Systems, Supply Chain Management, and Industry 4.0.” Annual Reviews in Control 46: 134–147. doi:10.1016/j.arcontrol.2018.10.014.
  • Ivanov, D., and B. Sokolov. 2013. “Control and System-Theoretic Identification of the Supply Chain Dynamics Domain for Planning, Analysis and Adaptation of Performance Under Uncertainty.” European Journal of Operational Research 224 (2): 313–323. doi:10.1016/j.ejor.2012.08.021.
  • Ivanov, D., B. Sokolov, and J. Kaeschel. 2010. “A Multi-Structural Framework for Adaptive Supply Chain Planning and Operations Control with Structure Dynamics Considerations.” European Journal of Operational Research 200 (2): 409–420. doi:10.1016/j.ejor.2009.01.002.
  • Ivanov, D., B. Sokolov, F. Werner, and A. Dolgui. 2020. “Proactive Scheduling and Reactive Real-Time Control in Industry 4.0.” In Scheduling in Industry 4.0 and Cloud Manufacturing, edited by C. C. Price, 11–37. Cham: Springer.
  • Kagermann, H., W. Wahlster, and J. Helbig. 2013. Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group. Forschungsunion.
  • Kuhl, F., R. Weatherly, and J. Dahmann. 1999. Creating Computer Simulation Systems: An Introduction to the High-Level Architecture. New Jersey: Prentice Hall PTR.
  • Kumar, A. 2007. “From Mass Customization to Mass Personalization: A Strategic Transformation.” International Journal of Flexible Manufacturing Systems 19: 533–547. doi:10.1007/s10696-008-9048-6.
  • Lee, J., B. Bagheri, and H.-A. Kao. 2015. “A Cyber-Physical Systems Architecture for Industry 4.0-based Manufacturing Systems.” Manufacturing Letters 3: 18–23. doi:10.1016/j.mfglet.2014.12.001.
  • Lee, Y. H., M. K. Cho, S. J. Kim, and Y. B. Kim. 2002. “Supply Chain Simulation with Discrete–Continuous Combined Modeling.” Computers & Industrial Engineering 43 (1–2): 375–392. doi:10.1016/S0360-8352(02)00080-3.
  • Lee, J., H. Davari, J. Singh, and V. Pandhare. 2018. “Industrial Artificial Intelligence for Industry 4.0-based Manufacturing Systems.” Manufacturing Letters 18: 20–23. doi:10.1016/j.mfglet.2018.09.002.
  • Leng, J., H. Zhang, D. Yan, Q. Liu, X. Chen, and D. Zhang. 2019. “Digital Twin-driven Manufacturing Cyber-physical System for Parallel Controlling of Smart Workshop.” Journal of Ambient Intelligence and Humanized Computing 10 (3): 1155–1166. doi:10.1007/s12652-018-0881-5.
  • Marmolejo-Saucedo, J. A., M. Hurtado-Hernandez, and R. Suarez-Valdes. 2019. “Digital Twins in Supply Chain Management: A Brief Literature Review.” In International Conference on Intelligent Computing & Optimization, 653–661. Cham: Springer. doi:10.1007/978-3-030-33585-4_63.
  • Mohammed, M. A., M. K. A. Ghani, R. I. Hamed, S. A. Mostafa, M. S. Ahmad, and D. A. Ibrahim. 2017. “Solving Vehicle Routing Problem by Using Improved Genetic Algorithm for Optimal Solution.” Journal of Computational Science 21: 255–262. doi:10.1016/j.jocs.2017.04.003.
  • Monostori, L., B. Kádár, T. Bauernhansl, S. Kondoh, S. Kumara, G. Reinhart, O. Sauer, G. Schuh, W. Sihn, and K. Ueda. 2016. “Cyber-Physical Systems in Manufacturing.” CIRP Annals 65 (2): 621–641. doi:10.1016/j.cirp.2016.06.005.
  • Oliveira, J. B., R. S. Lima, and J. A. B. Montevechi. 2016. “Perspectives and Relationships in Supply Chain Simulation: A Systematic Literature Review.” Simulation Modelling Practice and Theory 62: 166–191. doi:10.1016/j.simpat.2016.02.001.
  • Park, K. T., S. J. Im, Y.-S. Kang, S. D. Noh, Y. T. Kang, and S. K. Yang. 2019a. “Service-oriented Platform for Smart Operation of Dyeing and Finishing Industry.” International Journal of Computer Integrated Manufacturing 32 (3): 307–326. doi:10.1080/0951192X.2019.1572225.
  • Park, K. T., J. Lee, H.-J. Kim, and S. D. Noh. 2020a. “Digital Twin-based Cyber Physical Production System Architectural Framework for Personalized Production.” The International Journal of Advanced Manufacturing Technology 106 (5-6): 1787–1810. doi:10.1007/s00170-019-04653-7.
  • Park, K. T., D. Lee, and S. D. Noh. 2020b. “Operation Procedures of a Work-center-level Digital Twin for Sustainable and Smart Manufacturing.” International Journal of Precision Engineering and Manufacturing-Green Technology 7: 791–814. doi:10.1007/s40684-020-00227-1.
  • Park, K. T., Y. W. Nam, H. S. Lee, S. J. Im, S. D. Noh, J. Y. Son, and H. Kim. 2019b. “Design and Implementation of a Digital Twin Application for Connected Micro Smart Factory.” International Journal of Computer Integrated Manufacturing 32 (6): 596–614. doi:10.1080/0951192X.2019.1599439.
  • Park, K. T., J. Yang, and S. D. Noh. 2020c. “VREDI: Virtual Representation for a Digital Twin Application in a Work-center-level Asset Administration Shell.” Journal of Intelligent Manufacturing, doi:10.1007/s10845-020-01586-x.
  • Pires, M. C., E. M. Frazzon, A. M. C. Danielli, M. Kück, and M. Freitag. 2018. “Towards a Simulation-based Optimization Approach to Integrate Supply Chain Planning and Control.” Procedia CIRP 72: 520–525. doi:10.1016/j.procir.2018.03.288.
  • Qi, Q., and F. Tao. 2018. “Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison.” IEEE Access 6: 3585–3593. doi:10.1109/ACCESS.2018.2793265.
  • Rabe, M., F.-W. Jäkel, and H. Weinaug. 2006. “Supply Chair Demonstrator Based on Federated Models and HLA Application.” In SimVis 2006: 329–338.
  • Ribeiro, L. 2017. “Cyber-Physical Production Systems’ Design Challenges.” 2017 IEEE 26th international symposium on industrial Electronics (ISIE), Edinburgh, UK, June 19–23.
  • Ribeiro, L., and M. Björkman. 2017. “Transitioning from Standard Automation Solutions to Cyber-Physical Production Systems: An Assessment of Critical Conceptual and Technical Challenges.” IEEE Systems Journal 12 (4): 1–13. doi:10.1109/JSYST.2017.2771139.
  • Schleich, B., N. Anwer, L. Mathieu, and S. Wartzack. 2017. “Shaping the Digital Twin for Design and Production Engineering.” CIRP Annals 66 (1): 141–144. doi:10.1016/j.cirp.2017.04.040.
  • Sztipanovits, J., and S. Ying. 2013. “Foundations for Innovation: Strategic R&D Opportunities for twenty-first Century Cyber-Physical Systems.” National Institute of Standards and Technology (NIST).
  • Tao, F., M. Zhang, and A. Y. C. Nee. 2019. “Digital Twin Driven Smart Manufacturing.” Massachusetts: Academic Press, doi:10.1016/C2018-0-02206-9.
  • Theorin, A., K. Bengtsson, J. Provost, M. Lieder, C. Johnsson, T. Lundholm, and B. Lennartson. 2017. “An Event-driven Manufacturing Information System Architecture for Industry 4.0.” International Journal of Production Research 55 (5): 1297–1311. doi:10.1080/00207543.2016.1201604.
  • Timm, I. J., and F. Lorig. 2015. “Logistics 4.0 - A Challenge for Simulation.” Proceedings of the 2015 Winter Simulation Conference, IEEE Press. doi:10.1109/WSC.2015.7408428.
  • Weyrich, M., and C. Ebert. 2016. “Reference Architectures for the Internet of Things.” IEEE Software 33 (1): 112–116. doi:10.1109/MS.2016.20.
  • Wiktorsson, M., S. D. Noh, M. Bellgran, and L. Hanson. 2018. “Smart Factories: South Korean and Swedish Examples on Manufacturing Settings.” Procedia Manufacturing 25: 471–478. doi:10.1016/j.promfg.2018.06.128.
  • Xu, L. D., W. He, and S. Li. 2014. “Internet of Things in Industries: A Survey.” IEEE Transactions on Industrial Informatics 10 (4): 2233–2243. doi:10.1109/TII.2014.2300753.
  • Yang, Q. H., G. N. Qi, Y. J. Lu, and X. J. Gu. 2007. “Applying Mass Customization to the Production of Industrial Steam Turbines.” International Journal of Computer Integrated Manufacturing 20 (2–3): 178–188. doi:10.1080/09511920601020698.
  • Zezulka, F., P. Marcon, I. Vesely, and O. Sajdl. 2016. “Industry 4.0 – An Introduction in the Phenomenon.” IFAC-PapersOnLine 49 (25): 8–12. doi:10.1016/j.ifacol.2016.12.002.
  • Zhou, G., C. Zhang, Z. Li, K. Ding, and C. Wang. 2020. “Knowledge-driven Digital Twin Manufacturing Cell Towards Intelligent Manufacturing.” International Journal of Production Research 58 (4): 1034–1051. doi:10.1080/00207543.2019.1607978.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.