Gestão & Produção
https://www.gestaoeproducao.com/article/doi/10.1590/0104-530x5619-20
Gestão & Produção
SEÇÃO TEMÁTICA

Highlighting the benefits of Industry 4.0 for production: an agent-based simulation approach

Julio Takashi Cavata; Alexandre Augusto Massote; Rodrigo Filev Maia; Fábio Lima

Downloads: 0
Views: 798

Abstract

Abstract: Advanced Manufacturing or Industry 4.0 concepts bring new advances and challenges to current industrial processes. Such concepts are not always well understood and their results in terms of production performance may not be clear. This work proposes a comparison between a traditional manufacturing process and an advanced manufacturing process, both modelled by a multiagent society. In the traditional manufacturing simulation, the agents follow the defined times of each process, including the maintenance times. In the advanced manufacturing simulation, the decision about when to stop a piece of equipment for maintenance is defined by the agent according to data received from sensors and the definitions of the process. The results indicate a significant improvement in equipment usage and consequently higher production in the same time interval. The process simulation clearly indicates that the application of advanced manufacturing concepts in industry is relevant in order to increase the efficiency of production processes. Among the main concepts introduced in advanced manufacturing models are the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Artificial Intelligence (AI). The models generated are computationally simulated using an agent-based simulation method from the software AnyLogic. The results obtained should contribute to encouraging small and medium sized enterprises to adopt the concepts of Industry 4.0 in their businesses.

Keywords

Smart manufacturing, Industry 4.0, Cyber Physical Systems, Multi-Agent Systems, Simulation

Referências

Recommendations for implementing the strategic initiative INDUSTRIE 4.0. 2013:1-78.

Adeyeri M. K., Mpofu K., Adenuga O. T. Integration of agent technology into manufacturing enterprise: a review and platform for Industry 4.0.. 2015:1-10.

Alsina E. F., Cabri G., Regattieri A. An agent-based approach to simulate production, degradation, repair, replacement and preventive maintenance of manufacturing systems.. 2014:24-31.

Balaji P. G., Srinivasan D. An introduction to multi-agent systems.. (Eds.), Innovations in multi-agent systems and applications - 1. 2010:1-27.

Borshchev A. The big book of simulation modeling – multimethod modeling with AnyLogic 6. 2014.

Büth L., Broderius N., Herrmann C., Thiede S. Introducing agent-based simulation of manufacturing systems to industrial discrete-event simulation tools. 2017:1141-6.

Dafflon B., Essamlali M. T. E., Sekhari A., Bouras A. A reactive agent-based decision-making system for SBCE. 2016:746-53.

Feng Y., Fan W. A hybrid simulation approach to dynamic multi-skilled workforce planning of production line. 2014:1632-43.

Hermann M., Pentek T., Otto B. Design principles for Industrie 4.0 scenarios.. 2016:3928-37.

Industrial internet reference architecture. 2015:1-101.

Jules G., Saadat M. Agent cooperation mechanism for decentralized manufacturing scheduling. IEEE Transactions on Systems, Man, and Cybernetics. Systems. 2017;47(12):3351-62.

Kadera P., Novák P. Automatic compilation of performance models for industrial Multi-Agent Systems. 2015:1-8.

Kang H. S., Lee J. Y., Choi S., Kim H., Park J. H., Son J. Y., Kim B. H., Noh S. D. Smart manufacturing: past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing Green Technology. 2016;3(1):111-28.

Lee J., Bagheri B., Kao H.-A. Cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters. 2015;3:18-23.

Leitão P., Karnouskos S., Ribeiro L., Lee J., Strasser T., Colombo A. W. Smart agents in industrial cyber-physical systems. Proceedings of the IEEE. 2016;104(5):1086-101.

Leitão P., Marík V., Vrba P. Past, present, and future of industrial agent applications. IEEE Transactions on Industrial Informatics. 2013;9(4):2360-72.

Metzger M., Polaków G. A. A survey on applications of agent technology in industrial process control. IEEE Transactions on Industrial Informatics. 2011;7(4):570-81.

Novak P., Kadera P., Wimmer M. Agent-based modeling and simulation of hybrid cyber-physical systems. 2018:1-8.

Scholz M., Oberschachtsiek S., Donhauser T., Franke J. Software-in-the-loop testbed for multi-agent-systems in a discrete event simulation: Integration of the Java agent development framework into plant simulation. 2017:1-6.

Schwab K. The fourth industrial revolution. 2016.

Shpilevoy V., Shishov A., Skobelev P., Kolbova E., Kazanskaia D., Shepilov Y, Tsarev A. Multi-agent system “Smart Factory” for real-time workshop management in aircraft jet engines production. IFAC Proceedings Volumes. 2013;46(7):204-9.

Trappey A. J. C., Trappey C. V., Govindarajan U. H., Sun J. J., Chuang A. C. A review of technology standards and patent portfolios for enabling cyber-physical systems in advanced manufacturing. IEEE Access : Practical Innovations, Open Solutions. 2016;4:7356-82.

Reference architecture model industrie 4.0 (RAMI 4.0). 2015.

Vrba P., Tichý P., Marík V., Hall K. H., Staron R. J., Maturana F. P., Kadera P. Rockwell automation’s holonic and multiagent control systems compendium. IEEE Transactions on Systems, Man, and Cybernetics. 2011;41(1):14-30.

5f7b65080e8825831867ca72 gp Articles

Gest. Prod.

Share this page
Page Sections