Abstract
The industrial process continues its evolution based on the growing technological advances, which provide improvements in production and the satisfaction of environmental needs. The more recent evolution is known as the Industry 4.0 paradigm. In this context, organizations have seen the need to create digital ecosystems and alliances as a competitive strategy. However, there are many aspects to overcome in order to achieve an effective collaboration between organizations with different functions. Some of them are about how to establish collaborative processes, how to identify the possibilities of the contribution of each company, and how to establish functions, responsibilities, and the optimal coordination between them. In light of this situation, we propose a collaborative model for integrating organizations, based on Autonomous Cycles of Data Analysis Tasks, which are self-adaptive to satisfy the changing customer’s needs. All this will be made possible by making intensive use of “Everything mining”, and new technologies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Eberhard, B., Podio, M., Pérez, A., Radovica, E., Avotina, L., Peiseniece, L., Sendon, M.C., Lozano, A.G., Solé-pla, J.: Smart work: the transformation of the labour market due to the fourth industrial revolution. Int. J. Bus. Econ. Sci. Appl. Res. 10, 47–66 (2017)
Mo, Q., Dai, F., Zhu, R., Da, J., Lin, L., Li, T.: A distributed business process collaboration architecture based on entropy in cloud computing. In: International Conference on Cloud Computing, vol. 1, pp. 126–134 (2014)
Costache, A., Popa, C., Dobrescu, T., Cotet, C.: The gap between the knowledge of virtual enterprise actor and knowledge demand of Industry 4.0. In: 28th Daaam International Symposium on Intelligent Manufacturing and Automation, pp. 0743–0749, February 2017
Baicu, A.V.: Methods of assessment and training of a company towards the enterprise 4.0. In: 28th Daaam International Symposium on Intelligent Manufacturing and Automation, pp. 1065–1073 (2017)
Wee, D., Kelly, R., Cattel, J., Breunig, M.: Industry 4.0 - how to navigate digitization of the manufacturing sector. Technical report (2015)
Bullinger, H.J., Neuhüttler, J., Nägele, R., Woyke, I.: Collaborative development of business models in smart service ecosystems. In: 2017 Portland International Conference on Management of Engineering and Technology (PICMET) (2017)
Papa, M., Kaselautzke, D., Radinger, T., Stuja, K.: Development of a safety Industry 4.0 production environment. In: 28th Daaam International Symposium on Intelligent Manufacturing and Automation, Austria, pp. 981–987 (2017)
Trantopoulos, K., Krogh, G.V., Wallin, M.W., Woerter, M.: External knowledge and information technology. MisQuarterly 41(1), 287–300 (2017)
Roja, A., Nastase, M., Valimareanu, I.M.: Collaborative networks and strategic axes. Fundamental pillars of the development of technology entrepreneurial ecosystems. Rev. Int. Comp. Manag. 15(5), 579 (2014)
Nikolic, B., Ignjatic, J., Suzic, N., Stevanov, B., Rikalovic, A.: Predictive manufacturing systems in Industry 4.0: trends, benefits and challenges. In: 28th DAAAM International Symposium on Intelligent Manufacturing and Automation, pp. 796–803 (2017)
Baldassari, P., Roux, J.: Industry 4.0: preparing for the future of work (2017)
Ivanov, D., Dolgui, A., Sokolov, B., Werner, F., Ivanova, M.: A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory Industry 4.0. Int. J. Prod. Res. 54(2), 386–402 (2016)
Kanth, L.: Automation development through robot cells in lean manufacturing system. Airo Int. Res. J. XV, 63012 (2018)
André, S., Elgh, F.: Creating an ability to respond to changing requirements by systematic modelling of design assets and processes. In: 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp. 196–200 (2017)
Aguilar, J., Cordero, J., Buendía, O.: Specification of the autonomic cycles of learning analytic tasks for a smart classroom. J. Educ. Comput. Res. 38 (2017)
Aguilar, J., Buendia, O., Moreno, K., Mosquera, D.: Autonomous cycle of data analysis tasks for learning processes. In: Communications in Computer and Information Science, vol. 658 (2016)
Kitchenham, B.A.: Systematic review in software engineering - where we are and where we should be going. In: EAST 2012 Proceedings of the 2nd International Workshop on Evidential Assessment of Software Technologies (2012)
Schmidt, R., Möhring, M., Härting, R.C., Reichstein, C., Neumaier, P., Jozinović, P.: Industry 4.0 - potentials for creating smart products: empirical research results. Lecture Notes in Business Information Processing, vol. 208, pp. 16–27 (2015)
Kidanu, S., Cardinale, Y., Tekli, G., Chbeir, R.: A multimedia-oriented digital ecosystem: a new collaborative environment. In: 2015 IEEE/ACIS 14th International Conference on Computer and Information Science (ICIS) (2015)
Lee, E.A.: Cyber physical systems: design challenges. Technical report (2008)
Robla-Gomez, S., Becerra, V.M., Llata, J.R., Gonzalez-Sarabia, E., Torre-Ferrero, C., Perez-Oria, J.: Working together: a review on safe human-robot collaboration in industrial environments. IEEE Access 5, 26754–26773 (2017)
Charbonnaud, P., Zbib, N., Archimede, B.: Interoperability service utility model and its simulation for improving the business process collaboration. In: Proceedings of the I-ESA Conferences on Enterprise Interoperability V, London. Springer (2012)
Andres, B., Sanchis, R., Poler, R., Saari, L.: Collaborative calculation of the materials requirement planning in the automotive industry. In: Proceedings of 2017 International Conference on Engineering, Technology and Innovation: Engineering, Technology and Innovation Management Beyond 2020: New Challenges, New Approaches, ICE/ITMC 2017, January 2018, pp. 496–503 (2018)
Friedl, A.: Meeting Industrie 4.0 challenges with S-BPM. In: S-BPM One 2018 Proceedings of the 10th International Conference on Subject-Oriented Business Process Management, April, pp. 1–6 (2018)
Quinones, H., Yang, Y.: Intelligent automation; key factor for high mix manufacturing. In: 2017 International Conference on Electronics Packaging, ICEP 2017, pp. 308–311 (2017)
Alexakos, C., Kalogeras, A.: Exposing MES functionalities as enabler for cloud manufacturing. In: Proceedings of IEEE International Workshop on Factory Communication Systems, WFCS (2017)
Wang, S., Wan, J., Zhang, D., Li, D., Zhang, C.: Towards smart factory for Industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput. Netw. 101, 158–168 (2016)
Vizcarrondo, J., Aguilar, J., Exposito, E., Subia, A.: MAPE-K as a service-oriented architecture. IEEE Lat. Am. Trans. 15(6), 1163–1175 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lopez, CP., Santórum, M., Aguilar, J. (2019). Autonomous Cycles of Collaborative Processes for Integration Based on Industry 4.0. In: Rocha, Á., Ferrás, C., Paredes, M. (eds) Information Technology and Systems. ICITS 2019. Advances in Intelligent Systems and Computing, vol 918. Springer, Cham. https://doi.org/10.1007/978-3-030-11890-7_18
Download citation
DOI: https://doi.org/10.1007/978-3-030-11890-7_18
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-11889-1
Online ISBN: 978-3-030-11890-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)