Simulação como Tecnologia Habilitadora da Indústria 4.0: Uma Revisão da Literatura
Abstract
No atual contexto de desenvolvimento das organizações rumo a Indústria 4.0, processos industriais são diariamente bombardeados por uma diversidade de variáveis cada vez maior, além da necessidade constante de melhorias e evoluções tecnológicas exigidas pelo mercado. Neste cenário a simulação computacional aplicada tem papel fundamental, assim como outras ferramentas, constituem as chamadas tecnologias habilitadoras. Este estudo busca compreender como esta ferramenta habilitadora está sendo percebida e implementada. Para tanto foi realizada Revisão Sistemática da Literatura, apresentando uma visão de como os artigos científicos estão sendo publicados quanto a sua distribuição geográfica, autorias, áreas de pesquisas, entre outras características. A tecnologia da simulação como ferramenta de auto aprendizado proporciona autonomia a sistemas de manufatura inteligentes, gerando tomada de decisão dinâmica e automática. Realizando feedback ao sistema tomador de decisão, a simulação gera oportunidades de melhorias de performance e previsão de riscos, aumentando os níveis de segurança. Também, extrapola os paradigmas da simulação como ferramenta de otimização estatística e posiciona-se cada vez mais no mundo da virtualização através de imagens, realidade virtual, layout fabril, entre outras representações gráficas.
References
Kahndakar Ahmed; Jan O. Blech; Mark A. Gregory et al.; “Software Defined Networks in Industrial Automation”, Journal of Sensor and Actuator Networks, vol. 7, n. 3, 2018.
Vitor Alcácer, Virgilio Cruz-Machado, “Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems”, Engineering Science and Technology, an International Journal, Volume 22, Issue 3, Pages 899-919, 2019.
Pablo J. Alhama Blanco; Fares J. Abu-Dakka; Mohamed Abderrahim; “Practical Use of Robot Manipulators as Intelligent Manufacturing Systems”, Sensors, vol. 18, n. 9, 2018.
Luis Osmar Alpala; Maria del Mar Eva Alemany; Diego Hernán Peluffo-Ordoñez et al.; “Methodology for the design and simulation of industrial facilities and production systems based on a modular approach in an "industry 4.0" context”, Dyna, 85, n. 207, p. 243-252, 2018.
Stefan J. Bloechl; Mathias Michalicki; Markus Schneider; “Simulation Game for Lean Leadership - Shopfloor Management combined with Accounting for Lean”, In: METTERNICH, J. e GLASS, R. (Ed.). 7th Conference on Learning Factories, v. 9, p. 97-105, 2017. (PROCEDIA MANUFACTURING).
Stefan J. Bloechl; Markus Schneider; “Simulation Game for Intelligent Production Logistics - The PuLL (R) Learning Factory”, In: MARTINSEN, K. (Ed.). 6th Cirp Conference on Learning Factories, 2016. vol. 54, p. 130-135. (PROCEDIA CIRP).
Juan José-Bullon Perez; Angelica Gonzales Arrieta; Ascension Hernandes Encinas et al.; “Manufacturing processes in the textile industry. Expert Systems for fabrics production”, Adcaij-Advances in Distributed Computing and Artificial Intelligence Journal, vol. 6, n. 4, p. 15-23, 2017.
Alessandra Caggiano; Roberto Teti; “Digital factory technologies for robotic automation and enhanced manufacturing cell design”, Cogent Engineering, vol. 5, n. 1, 2018.
Fiorella Caputo et al., “Workplace design ergonomic validation based on multiple human factors assessment methods and simulation”. Production and Manufacturing Research-an Open Access Journal, vol. 7, n. 1, p. 195-222, 2019.
Carmen L. Constantinescu; Emmanuel Francalanza; Davide Matarazzo; “Towards knowledge capturing and innovative human-system interface in an open-source factory modelling and simulation environment”, In: TETI, R. (Ed.). 9th Cirp Conference on Intelligent Computation in Manufacturing Engineering - Cirp Icme '14, vol. 33, p. 23-28, 2015. (PROCEDIA CIRP).
Patrick Dallasega; Rafael A. Rojas; Erwin Rauch et al.; “Simulation based Validation of Supply Chain Effects through ICT enabled Real-Time-Capability in ETO Production Planning”, In: PELLICCIARI, M. e PERUZZINI, M. (Ed.). 27th International Conference on Flexible Automation and Intelligent Manufacturing, Faim 2017, v. 11, p. 846-853, 2017. (PROCEDIA MANUFACTURING).
Andrea De Giorgio; Mario Romero; Mauro Onori et al.; “Human-machine collaboration in virtual reality for adaptive production engineering”. In: PELLICCIARI, M. e PERUZZINI, M. (Ed.). 27th International Conference on Flexible Automation and Intelligent Manufacturing, Faim2017, v. 11, p. 1279-1287, 2017. (PROCEDIA MANUFACTURING).
Rainer Drath, Alexander Horch, “Industrie 4.0: Hit or Hype?”, IEEE Industrial Electronics Magazine, vol. 8(2), pp. 56-58, 2014.
Radoslaw Dukalski; Argun Cencen; Doris Aschenbrenner et al.; “Portable rapid visual workflow simulation tool for human robot coproduction”. In: PELLICCIARI, M. e PERUZZINI, M. (Ed.). 27th International Conference on Flexible Automation and Intelligent Manufacturing, Faim2017, vol. 11, p. 185-197, 2017. (PROCEDIA MANUFACTURING).
Gustavo Rodrigues Fraga; Tulio Almeida Peixoto; João José de Assis Rangel; “Simulation Optimization in Dosing Process Control System in Real Time in a Free and Open-Souce Sofwtare”, Pesquisa Operacional, vol. 38, n. 2, p. 273-289, 2018.
Yaping Fu; Mengchu Zhou; Xiwang Guo et al., “Artificial-Molecule-Based Chemical Reaction Optimization for Flow shop Scheduling Problem With Deteriorating and Learning Effects”, Ieee Access, vol. 7, p. 53429-53440, 2019.
Radovan Furmann; Beata Furmannova; Dorota Wiecek; “Interactive design of reconfigurable logistics systems”, In: BUJNAK, J. e GUAGLIANO, M. (Ed.). 12th International Scientific Conference of Young Scientists on Sustainable, Modern and Safe Transport, vol. 192, p. 207-212, 2017.
Quezia Manuela Gonçalves Laurindo; Tulio Almeida Peixoto; João José de Assis Rangel; “Communication mechanism of the discrete event simulation and the mechanical project softwares for manufacturing systems”, Journal of Computational Design and Engineering, vol. 6, n. 1, p. 70-80, 2019.
Lixiong Gong; Bingqian Zou; Zhiqun Kan; “Modeling and Optimization for Automobile Mixed Assembly Line in Industry 4.0,” Journal of Control Science and Engineering, vol. 2019, Article ID 3105267, 10 pages, 2019.
Mario Hermann; Tobias Pentek; Boris Otto; ‘‘Design principles for industry 4.0 scenarios’’, Working Paper, Tech. Univ. Dortmund, Dortmund, Germany, Feb. 2015.
Liam Y. Hsieh; Edward Huang; Chun-Hung Chen; “Equipment Utilization Enhancement in Photolithography Area Through a Dynamic System Control Using Multi-Fidelity Simulation Optimization With Big Data Technique”. Ieee Transactions on Semiconductor Manufacturing, vol. 30, n. 2, p. 166-175, 2017.
Jan Jatzkowski; Peer Adelt; Achim Rettberg; “Hierarchical Scheduling for Plug-and-Produce”, In: TRACHTLER, A.;DENKENA, B., et al (Ed.). 3rd International Conference on System-Integrated Intelligence: New Challenges for Product and Production Engineering, vol. 26, p. 227-234, 2016. (PROCEDIA Technology).
Botond Kadar; Peter Egri; Gianfranco Pedone et al.; “Smart, simulation-based resource sharing in federated production networks”, Cirp Annals-Manufacturing Technology, vol. 67, n. 1, p. 503-506, 2018.
Damian Krenczyk; Wojciech M. Kempa; Krumm Kalinowski et al.; “Integration of manufacturing operations management tools and discrete event simulation”, In: OANTA, E.;NAITO, M., et al (Ed.). Modtech International Conference - Modern Technologies in Industrial Engineering Vi, vol. 400, 2018. (IOP Conference Series-Materials Science and Engineering).
Kaustav Kundu; Matteo Rossini; Alberto Portioli-Staudacher; “Analysing the impact of uncertainty reduction on WLC methods in MTO flow shops”, Production and Manufacturing Research-an Open Access Journal, vol. 6, n. 1, p. 328-344, 2018.
Heiner Lasi et al., “Industry 4.0,” Business & Information Systems Engineering, vol. 6, n. 4, pp. 239-242, 2014. https://doi.org/10.1007/s12599-014-0334-4
Hoon-Gi Lee; Jun-Ho Huh; “A Cost-Effective Redundant Digital Excitation Control System and Test Bed Experiment for Safe Power Supply for Process Industry 4.0”, Processes, vol. 6, n. 7, 2018.
Matheus E. Leusin; Enzo M. Frazzon; Mauricio Uriona Maldonado et al.; “Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era”, Technologies, vol. 6, n. 4, 2018.
Tzuu-Hseng S. Li; Chih-Yin Liu; Ping-Huan Kuo et al.; “A Three-Dimensional Adaptive PSO-Based Packing Algorithm for an IoT-Based Automatede-Fulfillment Packaging System”, Ieee Access, vol. 5, p. 9188-9205, 2017.
Fabio Lima; Caroline N. de Carvalho; Mayara B.S. Acardi; et al., “DIGITAL MANUFACTURING TOOLS IN THE SIMULATION OF COLLABORATIVE ROBOTS: TOWARDS INDUSTRY 4.0” , Brazilian Journal of Operations & Production Management, vol. 16, n. 2, p. 261-280, 2019.
Chao Liu; Xun Xu; “Cyber-Physical Machine Tool - the Era of Machine Tool 4.0”, In: TSENG, M. M.;TSAI, H. Y., et al (Ed.). Manufacturing Systems 4.0, v. 63, p. 70-75, 2017. (PROCEDIA CIRP).
Ping Liu; Qiang Zhang; Juergen Pannek; “Development of Operator Theory in the Capacity Adjustment of Job Shop Manufacturing Systems”. Applied Sciences-Basel, vol. 9, n. 11, 2019.
Yejun Liu; Yahe Yang; Pengchao Han et al., “Virtual Network Embedding in Fiber-Wireless Access Networks for Resource-Efficient IoT Service Provisioning”, Ieee Access, vol. 7, p. 65506-65517, 2019.
Rafaela H. C. Machado; André Luis Helleno; Alexandre T. Simon; “Estudo bibliométrico da produção científica internacional sobre a DES aplicado a logística” Revista de Ciência & Tecnologia, vol. 19, Ed. 38, Pag. 17-31, 2016.
Vidosav Majstorovic; Slavenko Stojadinovic; Srdjan Zivkovic et al.; “Cyber-Physical Manufacturing Metrology Model (CPM3) for Sculptured Surfaces - Turbine Blade Application”, In: TSENG, M. M.;TSAI, H. Y., et al (Ed.). Manufacturing Systems 4.0, vol. 63, p. 658-663, 2017. (PROCEDIA CIRP).
Sergio Martiradonna; Giuseppe Piro; Gennaro Boggia; “On the Evaluation of the NB-IoT Random Access Procedure in Monitoring Infrastructures”, Sensors, vol. 19, n. 14, 2019.
David Moher et al., The PRISMA Group (2009) Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097. https://doi.org/10.1371/journal.pmed.1000097
Dimitris Mourtzis, Anastasios Vasilakopoulos, Evagoras Zervas, Nikoletta Boli, “Manufacturing System Design using Simulation in Metal Industry Towards Education 4.0”, PROCEDIA MANUFACTURING, Vol. 31, pag. 155-161, 2019.
Ulf Mueller; Peter Gust; Nico Feller et al.; “WorkDesigner: Consulting application software for the strain-based staffing and design of work processes”, In: AHRAM, T.;KARWOWSKI, W., et al (Ed.). 6th International Conference on Applied Human Factors and Ergonomics, v. 3, p. 379-386, 2015. (PROCEDIA MANUFACTURING).
Hana Neradilova; Gabriel Fedorko; “Simulation of the supply of workplaces by the AGV in the digital factory”, In: BUJNAK, J. e GUAGLIANO, M. (Ed.). 12th International Scientific Conference of Young Scientists on Sustainable, Modern and Safe Transport, vol. 192, p. 638-643, 2017. (PROCEDIA Engineering).
Jae-Han Park; Tae-Woong Yoonç; “Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning”, Complexity, vol. 2018 Article ID 9104720, 23 pags, 2018. https://doi.org/10.1155/2018/9104720.
Adriano Pereira; Eugenio de Oliveira Simonetto; Goran Putnik et al.; “How Connectivity and Search for Producers Impact Production in Industry 4.0 Networks”, Brazilian Journal of Operations & Production Management, vol. 15, n. 4, p. 528-534, 2018.
Ricardo Pimentel et al., “Review of simulation-based Optimization Approaches for the Adaptive Scheduling and Control os Dynamics Production Systems,” 24th International Conference on Production Research, p. 657-662, 2017.
Andras Poppe et al., “Multi-Domain Modelling of LEDs for Supporting Virtual Prototyping of Luminaires”. Energies, vol. 12, n. 10, 2019.
Theofanis P. Raptis; Andrea Passarella; Marco Conti; “Performance Analysis of Latency-Aware Data Management in Industrial IoT Networks”, Sensors, vol. 18, n. 8, 2018.
Carl Roberts, “A Conceptual Framework for Quantitative Text Analysis”, Quality & Quantity: International Journal of Methodology, vol. 34, issue 3, p. 259-274, 2000.
Blaz Rodic, “Industry 4.0 and the New Simulation Modelling Paradigm”, Organizacija, vol. 50, n. 3, p. 193-207, Aug 2017.
Maria Rosienkiewicz; Arkadiusz Kowalski; Joanna Helman et al.; “Development of Lean Hybrid Furniture Production Control System based on Glenday Sieve, Artificial Neural Networks and Simulation Modeling”, Drvna Industrija, vol. 69, n. 2, p. 163-173, 2018.
Tamas Ruppert; Janos Abonyi; “Software Sensor for Activity-Time Monitoring and Fault Detection in Production Lines”, Sensors, vol. 18, n. 7, 2018.
Tamas Ruppert; Janos Abonyi; “Worker Movement Diagram Based Stochastic Model of Open Paced Conveyors”, Hungarian Journal of Industry and Chemistry, vol. 46, n. 2, p. 55-62, 2018.
Roman Ruzarovsky; Radovan Holubek; Daynier Rolando Delgado Sobrino; “The Simulation of Conveyor Control System Using the Virtual Commissioning and Virtual Reality”, Advances in Science and Technology-Research Journal, vol. 12, n. 4, p. 164-171, 2018.
Hyun-Jun Shin; Kyoung-Woo Cho; Chang-Heon Oh; “SVM-Based Dynamic Reconfiguration CPS for Manufacturing System in Industry 4.0”, Wireless Communications & Mobile Computing, vol. 2018, article ID 5795037, 13 pages, 2018. https://doi.org/10.1155/2018/5795037
Erika Sujova; Helena Cierna; Iwona Zabinska; “Application of Digitalization Procedures of Production in Practice”, Management Systems in Production Engineering, vol. 27, n. 1, p. 23-28, 2019.
Gian Antonio Susto; Marco Maggipinto; Frederico Zocco et al.; “A Dynamic Sampling Approach for Cost Reduction in Semiconductor Manufacturing”, 28th International Conference on Flexible Automation and Intelligent Manufacturing, vol. 17, p. 1031-1038, 2018.
Michael Teucke; Eike Broda; Axel Boerold et al.; “Using Sensor-Based Quality Data in Automotive Supply Chains”, Machines, vol. 6, n. 4, 2018.
Angella Thomas; David A. Guerra-Zubiaga; John Cohran, “Digital Factory – Simulation Enhancing Production and Engeneering Process”, Proceedings of the ASME 2018; Volume 2: Advanced Manufacturing, V002T02A077. 2018.
Nikolett Toth et al.; “Elaborating Industry 4.0 compatible DSS for enhancing production system effectiveness” In: Xxiii International Conference on Manufacturing, vol. 448, 2018.
Peter Trebuna; Miriam Pekarcikova; Milan Edl; “Digital Value Stream Mapping Using the Tecnomatix Plant Simulation Software”. International Journal of Simulation Modelling, vol. 18, n. 1, p. 19-32, 2019.
Christopher J. Turner; Windo Hutabarat; John Oyekan et al.; “Discrete Event Simulation and Virtual Reality Use in Industry: New Opportunities and Future Trends”, Ieee Transactions on Human-Machine Systems, vol. 46, n. 6, p. 882-894, 2016.
Thomas H.-J. Uhlemann; Christian Lehamnn; Rolf Steinhilper; “The Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0”, In: TAKATA, S.;UMEDA, Y., et al (Ed.). 24th Cirp Conference on Life Cycle Engineering, vol. 61, p. 335-340, 2017. (PROCEDIA CIRP).
Gorka Urbikain; Alvaro Alvarez; Luis Norberto Lopez de Lacalle et al.; “A Reliable Turning Process by the Early Use of a Deep Simulation Model at Several Manufacturing Stages”, Machines, vol. 5, n. 2, 2017.
Ainhoa Goienetxea Uriarte; Amos H.C. Ng; Matias Urenda Moris; “Bringing together Lean and simulation: a comprehensive review”, International Journal of Production Research, vol. 17, n. 3, p. 377-390, 2019.
Antonio Vieira et al., “Setting an Industry 4.0 Research and Development Agenda for Simulation – A Literature Review”, International Journal of Simulation Modelling, vol. 17, n. 3, p. 377-390, 2018.
Wei Wang; Lei Fran; Pu Huang; “A New Data Processing Architecture for Multi-Scenario Applications in Aviation Manufacturing”, Ieee Access, vol. 7, p. 83637-83650, 2019.
Jie Xu et al., “Simulation optimization in the era of Industrial 4.0 and the Industrial Internet”, Journal of Simulation, vol. 10, n. 4, p. 310-320, 2016.
Poorya Ghafoorpoor Yazdi; Aydin Azizi; Majid Hashmemipour; “A Hybrid Methodology for Validation of Optimization Solutions Effects on Manufacturing Sustainability with Time Study and Simulation Approach for SMEs”, Sustainability, vol. 11, n. 5, 2019.
Hao Zhang; Qiang Liu; Xin Chen et al.; “A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line”, Ieee Access, vol. 5, p. 26901-26911, 2017.
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