Abstract
With the introduction of Industry 4.0 in many industrial environments, many changes are going to take place in the manufacturing processes. Blockchain can help the collaboration between organisations, by improving and leading the way for a decentralised future, where transactions can happen much faster while ensuring that a more knowledgeable and demanding consumer has its expectations fulfilled. In this work we propose a model that uses blockchain and multi-agent systems to help represent an organisation in a network of entities, as well to create a system that is capable of handling entity transactions and provide a way of improving decision-making by enabling decisions to be done faster in a rapidly changing environment.
This work has been supported by national funds through FCT - Fundação para a Ciência e Tecnologia through project UIDB/04728/2020.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abeyratne, S.A., Monfared, R.P.: Blockchain ready manufacturing supply chain using distributed ledger. Int. J. Res. Eng. Technol. 05(09), 1–10 (2016). https://doi.org/10.15623/ijret.2016.0509001. http://esatjournals.net/ijret/2016v05/i09/IJRET20160509001.pdf
Adeyeri, M.K., Mpofu, K., Adenuga, O.T.: Integration of agent technology into manufacturing enterprise: a review and platform for industry 4.0. In: 2015 International Conference on Industrial Engineering and Operations Management (IEOM). IEEE, March 2015. https://doi.org/10.1109/ieom.2015.7093910
Ameri, F., McArthur, C.: A multi-agent system for autonomous supply chain configuration. Int. J. Adv. Manuf. Technol. 66(5–8), 1097–1112 (2012). https://doi.org/10.1007/s00170-012-4392-9
Androulaki, E., et al.: Hyperledger fabric: a distributed operating system for permissioned blockchains. In: Proceedings of the Thirteenth EuroSys Conference on - EuroSys 2018. ACM Press (2018). https://doi.org/10.1145/3190508.3190538
Azadnia, A.H., Saman, M.Z.M., Wong, K.Y.: Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process. Int. J. Prod. Res. 53(2), 383–408 (2015). https://doi.org/10.1080/00207543.2014.935827
Bahga, A., Madisetti, V.K.: Blockchain platform for industrial internet of things. J. Softw. Eng. Appl. 09(10), 533–546 (2016). https://doi.org/10.4236/jsea.2016.910036. http://www.scirp.org/journal/jsea
Blanchet, M., Rinn, T., Von Thaden, G., De Thieulloy, G.: Industry 4.0: the new industrial revolution-how Europe will succeed. Hg. v. Roland Berger Strategy Consultants GmbH. München. Abgerufen am 11.05. 2014 (2014). http://www.rolandberger.com/media/pdf/Roland_Berger_TAB_Industry_4_0_20140403.pdf
Buchanan, B., Naqvi, N.: Building the future of EU: moving forward with international collaboration on blockchain. JBBA 1(1), 1–4 (2018)
Cachin, C., Schubert, S., Vukolić, M.: Architecture of the hyperledger blockchain fabric *. Technical report (2016), www.hyperledger.org
Calvaresi, D., Dubovitskaya, A., Calbimonte, J.P., Taveter, K., Schumacher, M.: Multi-Agent systems and blockchain: results from a systematic literature review. In: Demazeau, Y., An, B., Bajo, J., Fernández-Caballero, A. (eds.) PAAMS 2018. LNCS (LNAI), vol. 10978, pp. 110–126. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94580-4_9
Casado-Vara, R., Prieto, J., la Prieta, F.D., Corchado, J.M.: How blockchain improves the supply chain: case study alimentary supply chain. Procedia Comput. Sci. 134, 393–398 (2018). https://doi.org/10.1016/j.procs.2018.07.193. https://linkinghub.elsevier.com/retrieve/pii/S187705091831158X
Eddy, Y.F., Gooi, H.B., Chen, S.X.: Multi-agent system for distributed management of microgrids. IEEE Trans. Power Syst. 30(1), 24–34 (2014)
Fiala, P.: Information sharing in supply chains. Omega 33(5), 419–423 (2005). https://doi.org/10.1016/j.omega.2004.07.006
Ghadimi, P., Ghassemi Toosi, F., Heavey, C.: A multi-agent systems approach for sustainable supplier selection and order allocation in a partnership supply chain. Eur. J. Oper. Res. 269(1), 286–301 (2018). https://doi.org/10.1016/j.ejor.2017.07.014. https://linkinghub.elsevier.com/retrieve/pii/S0377221717306410
Glavic, M.: Agents and multi-agent systems: a short introduction for power engineers, pp. 1–21 (2006)
Kang, H.S., et al.: Smart manufacturing: past research, present findings, and future directions. Int. J. Precis. Eng. Manuf.-Green Technol. 3(1), 111–128 (2016). https://doi.org/10.1007/s40684-016-0015-5
Lee, J., Bagheri, B., Kao, H.A.: A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015). https://doi.org/10.1016/j.mfglet.2014.12.001
Lee, J., Kao, H.A., Yang, S.: Service innovation and smart analytics for industry 4.0 and big data environment. Procedia CIRP 16, 3–8 (2014). https://doi.org/10.1016/j.procir.2014.02.001. http://www.sciencedirect.com/science/article/pii/S2212827114000857
Lin, I.C., Liao, T.C.: A survey of blockchain security issues and challenges. Int. J. Netw. Secur. 19(5), 653–659 (2017). https://doi.org/10.6633/IJNS.201709.19(5).01. https://pdfs.semanticscholar.org/f61e/db500c023c4c4ef665bd7ed2423170773340.pdf
Marreiros, G., Santos, R., Ramos, C., Neves, J.: Context-aware emotion-based model for group decision making. IEEE Intell. Syst. Mag. 25(2), 31–39 (2010)
Marreiros, G., Santos, R., Ramos, C., Neves, J., Bulas-Cruz, J.: ABS4GD: a multi-agent system that simulates group decision processes considering emotional and argumentative aspects. In: AAAI Spring Symposium Series, pp. 88–95 (2008)
Mettler, T., Rohner, P.: Supplier relationship management: a case study in the context of health care. J. Theoret. Appl. Electron. Commer. Res. 4(3), 58–71 (2009). https://doi.org/10.4067/S0718-18762009000300006
Nikraz, M., Caire, G., Bahri, P.A.: A methodology for the analysis and design of multi-agent systems using JADE. Technical report (2006)
Oprea, M.: Applications of multi-agent systems. In: Reis, R. (ed.) Information Technology. IIFIP, vol. 157, pp. 239–270. Springer, Boston, MA (2004). https://doi.org/10.1007/1-4020-8159-6_9
Pinheiro, P., Macedo, M., Barbosa, R., Santos, R., Novais, P.: Multi-agent systems approach to industry 4.0: enabling collaboration considering a blockchain for knowledge representation. In: Bajo, J., et al. (eds.) PAAMS 2018. CCIS, vol. 887, pp. 149–160. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94779-2_14
Pinheiro, P., Santos, R., Barbosa, R.: Industry 4.0 multi-agent system based knowledge representation through blockchain. In: Novais, P., et al. (eds.) ISAmI2018 2018. AISC, vol. 806, pp. 331–337. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-01746-0_39
Qin, J., Liu, Y., Grosvenor, R.: A categorical framework of manufacturing for industry and beyond. Procedia CIRP 52, 173–178 (2016). https://doi.org/10.1016/j.procir.2016.08.005. http://www.sciencedirect.com/science/article/pii/S221282711630854X?via%3Dihub
Rabah, K.: Overview of blockchain as the engine of the 4th industrial revolution. Mara Res. J. Bus. Manag. 1(1), 125–135 (2016). The Africa Premier Research Publishing Hub www.mrjournals.org Mara Research Journals MR Journal of Business & Management
Schuh, G., Potente, T., Wesch-Potente, C., Weber, A.R., Prote, J.P.: Collaboration mechanisms to increase productivity in the context of industrie 4.0. Procedia CIRP 19, 51–56 (2014). https://doi.org/10.1016/j.procir.2014.05.016. https://linkinghub.elsevier.com/retrieve/pii/S2212827114006453
Sukhwani, H., Wang, N., Trivedi, K.S., Rindos, A.: Performance modeling of hyperledger fabric (permissioned blockchain network). In: 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), pp. 1–8. IEEE, November 2018. https://doi.org/10.1109/nca.2018.8548070
Wang, S., Wan, J., Li, D., Zhang, C.: Implementing smart factory of industrie 4.0: an outlook. Int. J. Distrib. Sens. Netw. 12(1), 3159805 (2016). https://doi.org/10.1155/2016/3159805
Wright, A., Filippi, P.D.: Decentralized blockchain technology and the rise of lex cryptographia. SSRN Electron. J. (2015). https://doi.org/10.2139/ssrn.2580664, http://www.ssrn.com/abstract=2580664
Wust, K., Gervais, A.: Do you need a blockchain? In: 2018 Crypto Valley Conference on Blockchain Technology (CVCBT), pp. 45–54. no. i. IEEE, June 2018. https://doi.org/10.1109/cvcbt.2018.00011, https://ieeexplore.ieee.org/document/8525392/
Zhang, F., Liu, M., Shen, W.: Operation modes of smart factory for high-end equipment manufacturing in the internet and big data era. In: Smc 2017.Org (2017). http://www.smc2017.org/SMC2017_Papers/media/files/0642.pdf
Zhao, J.Y., Wang, Y.J., Xi, X.: Simulation of steel production logistics system based on multi-agents. Int. J. Simul. Model. 16(1), 167–175 (2017). https://doi.org/10.2507/ijsimm16(1)co4, http://www.ijsimm.com/Full_Papers/Fulltext2017/text16-1_167-175.pdf
Zheng, Z., Xie, S., Dai, H., Chen, X., Wang, H.: An overview of blockchain technology: architecture, consensus, and future trends. In: 2017 IEEE International Congress on Big Data (BigData Congress), pp. 557–564. IEEE, June 2017. https://doi.org/10.1109/bigdatacongress.2017.85, http://ieeexplore.ieee.org/document/8029379/
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Pinheiro, P., Santos, R., Barbosa, R. (2020). Improving Collaboration in Industry 4.0: The Usage of Blockchain for Knowledge Representation. In: De La Prieta, F., et al. Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection. PAAMS 2020. Communications in Computer and Information Science, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51999-5_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-51999-5_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51998-8
Online ISBN: 978-3-030-51999-5
eBook Packages: Computer ScienceComputer Science (R0)