Um modelo hierárquico para conceitos da indústria 4.0

Cordeiro, Raphaella F.; Reis, Luciana P.; Fernandes, June M.

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Resources and Entrepreneurial Development • RAM, Rev. Adm. Mackenzie 24 (2) • 2023 • https://doi.org/10.1590/1678-6971/eRAMR230061.en copiar

Um modelo hierárquico para conceitos da indústria 4.0

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

Objetivo:

Esta pesquisa tem como objetivo estruturar um modelo hierárquico que integre os conceitos da indústria 4.0 (I4.0) e padronizar conceitos com base na literatura.

Originalidade/valor:

Kamble et al. (2018)Kamble, S. S., Gunasekaran, A., & Sharma, R. (2018). Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry. Computers in Industry, 101, 107–119. https://doi.org/ 10.1016/j.compind.2018.06.004
https://doi.org/ 10.1016/j.compind.2018.... apontam para a falta de uma arquitetura para representar os conceitos I4.0. Este artigo traz uma abordagem para a relação entre esses conceitos de I4.0. Ele expande os es- tudos de Ghobakhloo (2018)Ghobakhloo, M. (2018). The future of manufacturing industry: A strategic roadmap toward Industry 4.0. Journal of Manufacturing Technology Management, 29(6), 910–936. https://doi.org/10.1108/JMTM-02-2018-0057
https://doi.org/10.1108/JMTM-02-2018-005... e Liao et al. (2017)Liao, Y., Deschamps, F., Loures, E. D. F. R., & Ramos, L. F. P. (2017). Past, present, and future of Industry 4.0–A systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3609-3629. https://doi.org/10.1080/00207543.2017.1308576
https://doi.org/10.1080/00207543.2017.13... e homogeneíza termos presentes na literatura.

Design/metodologia/abordagem:

A partir de uma revisão sistemática da literatura nas bases de dados Scopus e ScienceDirect, de 2011 a 2019, foram revisados 91 artigos, dos quais 58 foram analisados.

Resultados:

A partir da literatura, os termos relacionados com I4.0 foram agrupados em três categorias: tecnologias, princípios e dimensões. Os clusters de tecnologia representam ferramentas utilizadas para promover mudanças e transformações nos processos, aqui chamados de princípios. Essas mudanças e transformações criam novos padrões da indústria, permitindo a integração de processos para a solução de problemas, contribuindo para a implementação do gerenciamento inteligente. A relação entre essas categorias resulta em um modelo hierárquico.

Palavras-chave:
indústria 4.0; dimensões; tecnologias; princípios; modelo hierárquico

Revolution	Period	Characteristics
1st Industrial Revolution	18th and 19th centuries	– Emergence of steam engines – Hydraulic energy – Mechanization
2nd Industrial Revolution	Second half of the 19th century	– United States serial production by Henry Ford
3rd Industrial Revolution	Second half of the 20th century	– Emergence of electronics – Appearance of robotics – Emergence of computers – Emergence of information technology – Automation in manufacturing processes
4th Industrial Revolution	Since 2011	– Increased data and connectivity, especially new wide-area networks – Emergence of analytical capabilities and business intelligence – Emergence of new forms of human-machine interaction, such as touch interfaces and augmented reality systems – Improvement in transfer of digital instructions to the physical world, such as with advanced robotics and 3D printing

Authors/terms	Big data	Big data analytics	Cloud	Cloud computing	CPS	Digital twin	3D printing	Artificial intelligence	Horizontal/vertical integration	Internet of things	Maching learning	Machine-to-machine	Additive manufacturing	Advanced manufacturing	Digital manufacturing	Data mining	Optimization	Augmented reality	Virtual reality	Autonomous robot	Collaborative robot	Advaced robotics	SCADA, MES. ERP, and CLP	Services (IoS)	Simulation	Smart working	RFID technology
Alcácer and Cruz-Machado (2019)Alcácer, V., & Cruz-Machado, V. (2019). Scanning the Industry 4.0: A literature review on technologies for manufacturing systems. Engineering Science and Technology, an International Journal, 22(3), 899–919. https://doi.org/10.1016/j.jestch.2019.01.006 https://doi.org/10.1016/j.jestch.2019.01...	X		X							X															X
Baena et al. (2017)Baena, F., Guarin, A., Mora, J., Sauza, J., & Retat, S. (2017). Learning factory: The path to Industry 4.0. Procedia Manufacturing, 9, 73–80. https://doi.org/10.1016/j.promfg.2017.04.022 https://doi.org/10.1016/j.promfg.2017.04...	X				X			X		X												X		X		X
Bal and Erkan (2019)Bal, H. Ç., & Erkan, Ç. (2019). Industry 4.0 and competitiveness. Procedia computer science, 158, 625–631. https://doi.org/10.1016/j.procs.2019.09.096 https://doi.org/10.1016/j.procs.2019.09....	X	X		X	X	X	X		X	X			X					X		X	X				X	X	X
Bortolini et al. (2017)Bortolini, M., Ferrari, E., Gamberi, M., Pilati, F., & Faccio, M. (2017). Assembly system design in the Industry 4.0 era: A general framework. IFACPapersOnLine, 50(1), 5700–5705. https://doi.org/10.1016/j.ifacol.2017.08.1121 https://doi.org/10.1016/j.ifacol.2017.08...	X	X	X		X		X		X	X	X		X	X			X	X			X	X
Büchi et al. (2020)Büchi, G., Cugno, M., & Castagnoli, R. (2020). Smart factory performance and Industry 4.0. Technological Forecasting and Social Change, 150, 119790. https://doi.org/10.1016/j.techfore.2019.119790 https://doi.org/10.1016/j.techfore.2019....	X			X					X	X			X		X			X							X
Caricato and Grieco (2017)Caricato, P., & Grieco, A. (2017). An application of Industry 4.0 to the production of packaging films. Procedia Manufacturing, 11, 949–956. http://dx.doi.org/10.1016/j.promfg.2017.07.199 http://dx.doi.org/10.1016/j.promfg.2017....		X							X					X											X
Santos (2018)Santos, R. C. (2018). Proposta de modelo de avaliação de maturidade da Indústria 4.0 [Doctoral dissertation, Instituto Superior de Engenharia de Coimbra]. https://comum.rcaap.pt/bitstream/10400.26/25346/1/Reginaldo-Carreiro-Santos.pdf https://comum.rcaap.pt/bitstream/10400.2...		X	X		X			X		X		X				X	X	X	X				X
Castelo-Branco et al. (2019)Castelo-Branco, I., Cruz-Jesus, F., & Oliveira, T. (2019). Assessing Indus- try 4.0 readiness in manufacturing: Evidence for the European Union. Computers in Industry, 107, 22–32. https://doi.org/10. 1016/j.compind.2019.01.007 https://doi.org/10. 1016/j.compind.2019....	X		X		X					X													X

Authors/terms	Adaptability	Self-optimization	Self-configuration	Automation	Conectivity	Consciousness	Customization	Decentralization	Scanning	Availability	Efficiency	Scalability	Flexbility	Integrity	Interoperability	Maintenance	Modularity	Service orientation	Personalization	Predictability	Traceability	Reconfigurability	Real-time response	Security	Sustainability	Virtualization
Alcácer and Cruz-Machado (2019)Alcácer, V., & Cruz-Machado, V. (2019). Scanning the Industry 4.0: A literature review on technologies for manufacturing systems. Engineering Science and Technology, an International Journal, 22(3), 899–919. https://doi.org/10.1016/j.jestch.2019.01.006 https://doi.org/10.1016/j.jestch.2019.01...			X	X			X						X	X	X	X	X		X				X
Bal and Erkan (2019)Bal, H. Ç., & Erkan, Ç. (2019). Industry 4.0 and competitiveness. Procedia computer science, 158, 625–631. https://doi.org/10.1016/j.procs.2019.09.096 https://doi.org/10.1016/j.procs.2019.09....								X						X					X		X			X	X
Bortolini et al. (2017)Bortolini, M., Ferrari, E., Gamberi, M., Pilati, F., & Faccio, M. (2017). Assembly system design in the Industry 4.0 era: A general framework. IFACPapersOnLine, 50(1), 5700–5705. https://doi.org/10.1016/j.ifacol.2017.08.1121 https://doi.org/10.1016/j.ifacol.2017.08...	X						X	X												X
Caricato and Grieco (2017)Caricato, P., & Grieco, A. (2017). An application of Industry 4.0 to the production of packaging films. Procedia Manufacturing, 11, 949–956. http://dx.doi.org/10.1016/j.promfg.2017.07.199 http://dx.doi.org/10.1016/j.promfg.2017....										X					X
Santos (2018)Santos, R. C. (2018). Proposta de modelo de avaliação de maturidade da Indústria 4.0 [Doctoral dissertation, Instituto Superior de Engenharia de Coimbra]. https://comum.rcaap.pt/bitstream/10400.26/25346/1/Reginaldo-Carreiro-Santos.pdf https://comum.rcaap.pt/bitstream/10400.2...	X	X	X	X	X	X	X	X			X	X	X		X	X		X		X	X	X	X
Castelo-Branco et al. (2019)Castelo-Branco, I., Cruz-Jesus, F., & Oliveira, T. (2019). Assessing Indus- try 4.0 readiness in manufacturing: Evidence for the European Union. Computers in Industry, 107, 22–32. https://doi.org/10. 1016/j.compind.2019.01.007 https://doi.org/10. 1016/j.compind.2019....								X	X						X		X	X					X			X

Groups	Technologies	2014	2015	2016	2018	2019	Number of citations	Percentual
Cyber-physical systems	Machine-to-machine				3	6	10	17%
	Autonomous robot	1			2	10	15	26%
	Collaborative robot				1	8	5	9%
	3D printing or additive manufacturing	1		1	7	14	29	50%
	Simulation			1	4	12	20	34%
	Augmented reality				2	17	20	34%
	Virtual reality				2	2	5	9%
	Digital twin			1	2	4	8	14%
	Horizontal/vertical integration		1		4	11	20	34%
IoT	RFID					6	13	22%
	QR code	1			2	5	8	14%
	Barcodes					4	6	10%
	Sensors	1			2	8	18	31%
On demand availability of computer system resources	Big data	1		3	6	18	32	55%
	Big data analytics/ data mining			1	2	5	8	14%
	Cloud or cloud computing	1		1	8	24	38	66%
Cognitive computing	Artificial intelligence			2	1	7	12	21%
Cognitive computing	Machine learning			1		5	10	17%

Principles	Equivalent nomenclature	Number of citations	Percentual
Real-time response	Decision-making	25	43%
Virtualization	Digitalization	23	40%
Transparency of information	–	11	19%
Technical assistance	–	7	12%
Decentralization	Consciousness	51	88%
	Self-adaptive
	Auto optimization
	Autoconfiguration
	Self-knowledge
	Automation
Modularity	Compositionality	13	22%
Heterogeneity	–	4	7%
Adaptability	Flexibility	21	36%
Adaptability	Reconfigurability	21	36%
Interoperability	Connectivity	33	57%
	Communication
	Interconnection
Personalization	Customization	21	36%
Sustainability	Efficiency	25	43%
Security	Confidentiality	23	40%
Security	Integrity	23	40%
Reliability	Scalability	14	24%
	Robustness
	Resilience
Predictability	Precision	13	22%
Service orientation	–	8	14%
Traceability	–	10	17%

Dimension	Quantity	Percentual
Smart manufacturing	13	31%
Smart products and services	11	24%
Smart supply chain	8	19%
Smart work	5	10%

Dimensions/ Principles	Real-time response	Virtualization	Transparency of information	Technical assistance	Decentralization	Modularity	Adaptability	Interoperability	Personalization	Sustainability	Security	Predictability	Service orientation	Traceability	Total
Smart manufacturing	11%		11%		89%	22%	44%	78%		33%	11%	11%			9
Smart product and service		11%						44%	33%	11%			11%	44%	6
Smart supply chain			22%					56%		11%			33%		4
Smart work		33%		44%				33%		22%					4
Total	1	2	2	1	1	1	1	4	1	4	1	1	2	1

Principles/Technologies	Machine-to-machine	Autonomous robot	Collaborative robot	3D printing	Simulation	Augmented reality	Virtual reality	Digital twin	Horizontal/vertical integration	RFID	Sensors	Big data	Big data analytics	Data mining	Cloud	Artificial intelligence	Machine leraning	Cyber-physical systems (*)	Internet of things (*)	Total
Real-time response						4%							12%					20%		3
Virtualization							4%	4%			4%									3
Transparency of information											4%		8%							2
Technical assistance			8%			4%														2
Decentralization		4%											4%	4%		12%	8%	16%		6
Adaptability		8%		8%																2
Interoperability	4%								12%	16%	12%	20%			8%			12%	32%	8
Personalization				24%					4%				4%							3
Sustainability				8%	8%				4%				8%					4%		5
Security												4%			20%					2
Predictability								4%					4%				8%			3
Traceability										12%								20%	16%	3
Total	1	2	1	3	1	2	1	2	3	2	3	2	6	1	2	1	2	5	2

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[1] Correspondence concerning this article should be addressed to Raphaella F. Cordeiro, Rua Magnólia, 156, João Monlevade, Recanto do Paraíso, MG, Brazil, ZIP code 35930-140. Email: raphaella.cordeiro@aluno.ufop.edu.br