An Industry 4.0 Maturity Model Applied to the automotive supply chain

Luis Rigato Vasconcellos; Paulo Gobo Junior; Fabiano Rodrigues

doi:10.20397/2177-6652/2021.v21i4.2189

Authors

Luis Rigato Vasconcellos FGV / EAESP https://orcid.org/0000-0002-4472-7258
Paulo Gobo Junior https://orcid.org/0000-0001-5395-4076
Fabiano Rodrigues ESPM https://orcid.org/0000-0002-0313-9492

DOI:

https://doi.org/10.20397/2177-6652/2021.v21i4.2189

Keywords:

, indústria 4.0, cadeia de suprimentos, nível de maturidade, setor automotivo

Abstract

Objetivo do estudo: apresentar um modelo de maturidade que analise a indústria no contexto 4.0, possibilitando a identificação das principais diferenças existentes entres os níveis de maturidade dos participantes de uma cadeia de suprimentos.

Metodologia/abordagem: a partir da revisão de literatura foi proposto um modelo de maturidade dos conceitos da indústria 4.0 através da utilização de questionário. Esse modelo foi validado por especialistas, para em seguida ser aplicado em três empresas fabricantes de autopeças na região da Grande São Paulo (SP) e em três fornecedores relevantes em suas cadeias.

Originalidade/Relevância: preencher uma lacuna de pesquisa existente ao fornecer um modelo aberto e disponível para se analisar a maturidade dos conceitos da indústria 4.0 de uma cadeia de suprimentos no cenário brasileiro.

Principais resultados: Verificou-se que as empresas estudadas apresentaram notas baixas na maior parte das seis dimensões propostas do modelo. O resultado obtido pela análise das respostas do questionário demonstra também um baixo nível de implementação da metodologia da Indústria 4.0

Contribuições teóricas: é realizada uma revisão teórica sobre os componentes relavantes para a indústria 4.0, bem como uma síntese com quinze modelos que a literatura disponibiliza para a análise do grau de maturidade desses conceitos.

Contribuições para a gestão: tornar disponível para toda a comunidade acadêmica e profissional um questionário estruturado com 66 questões testado para a análise do grau de maturidade da indústria 4.0 para uma cadeia de suprimentos.

Author Biographies

Luis Rigato Vasconcellos, FGV / EAESP

Possui Doutorado em Engenharia de Produção pela Escola Politécnica de São Paulo (2010); Mestrado em Administração de Empresas pela Fundação Getulio Vargas - SP (2002) e Graduação em Engenharia de Produção pela Faculdade de Engenharia Industrial - FEI (1995). Ampla experiência na área de Operações, atuando como executivo e consultor. Atualmente é coordenador do curso de especialização Master Business Management - MBM da Fundação Getulio Vargas de São Paulo - FGV EAESP.

Fabiano Rodrigues, ESPM

Fabiano Rodrigues is a professor, Head of the Business Transformation and Management Center and Integrated Projects Supervisor at ESPM. PhD in Administration from FEA-USP, master and graduated in Production Engineering from POLI-USP. Member of the Society for Decision Professionals. Additional training in Strategic Decisions and Risk Management, by the Stanford University professional certification program.

References

Bangemann, T., Riedl, M., Thron, M., & Diedrich, C. (2016). Integration of classical components into industrial Cyber-Physical Systems. Proceedings of the IEEE, v. 104, n. 5, p. 947-959. https://doi.org/10.1109/jproc.2015.2510981

Basseto, A. L. C. (2019). Modelo de maturidade para a análise das indústrias no contexto da Indústria 4.0. 2019. Dissertação (Mestrado em Engenharia de Produção) –Universidade Tecnológica Federal do Paraná, Paraná, Brasil.

Conti, M., Passarella, A., Das, S. K. (2017). The Internet of People (IoP): A new wave in pervasive mobile computing. Pervasive and Mobile Computing, v. 41, p. 1-27, 2017. https://doi.org/10.1016/j.pmcj.2017.07.009

De Bruin, T., Freeze, R., Kulkarni, U., & Rosemann, M. (2005). Understanding the main phases of developing a maturity assessment model. In:16th Australasian Conference on Information Systems. Sydney, p. 8-19.

De Carolis, A., Macchi, M., Negri, E., & Terzi, S. (2017). Guiding manufacturing companies towards digitalization a methodology for supporting manufacturing companies in defining their digitalization roadmap. In: International Conference on Engineering, Technology and Innovation, p. 487-495. https://doi.org/10.1109/ice.2017.8279925

Erol, S., Schumacher, A., & Sihn, W. (2016). Strategic guidance towards Industry 4.0 – a three-stage process model. In: International Conference on Competitive Manufacturing 2016 (COMA16). Stellenbosch, South Africa, p. 495-501.

Faheem, M., & Gungor, V. C. (2018). Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0. Applied Soft Computing Journal, v. 68, p. 910-922. https://doi.org/10.1016/j.asoc.2017.07.045

Freund, G. P., Fagundes, P.B., & Macedo, D. D. J. (2017). Requisitos de Segurança para Provedores de Serviços em Nuvem de Acordo com a Norma ISO 27017. 2017. Recuperado em 24 maio, 2020, de https://repositorio.ufsc.br/bitstream/handle/123456789/180295/ST3.4.pdf?sequence=1&isAllowed=y

Galaske N., Arndt A., Friedrich H., Bettenhausen K.D., & Anderl R. (2018). Workforce Management 4.0 - Assessment of Human Factors Readiness Towards Digital Manufacturing. In: Trzcielinski S. (eds) Advances in Ergonomics of Manufacturing: Managing the Enterprise of the Future. AHFE 2017. Advances in Intelligent Systems and Computing, vol 606. Springer, Cham. https://doi.org/10.1007/978-3-319-60474-9_10

Gill, M., & Vanboskirk, S. (2016). Digital Maturity Model 4.0. Benchmarks: Digital Transformation Playbook. Recuperado em 15 fevereiro, 2020, de https://forrester.nitro-digital.com/pdf/Forrester-s%20Digital%20Maturity%20Model%204.0.pdf

Gökalp E., Şener U., & Eren P.E. (2017) Development of an Assessment Model for Industry 4.0: Industry 4.0-MM. In: Mas A., Mesquida A., O'Connor R., Rout T., Dorling A. (eds) Software Process Improvement and Capability Determination. SPICE 2017. Communications in Computer and Information Science, vol 770. Springer, Cham. https://doi.org/10.1007/978-3-319-67383-7_10

Hofmann, E., & Rusch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, v. 89, p. 23-34. https://doi.org/10.1016/j.compind.2017.04.002

Isoherranen, V., Karkkainen, M. K., & Kess, P. (2015). Operational excellence driven by process maturity reviews: a case study of the ABB corporation. In: IEEE - International Conference on Industrial Engineering and Engineering Management. Dubai, p. 1372-1376. https://doi.org/10.1109/ieem.2015.7385872

Jæger B., Halse L.L. (2017) The IoT Technological Maturity Assessment Scorecard: A Case Study of Norwegian Manufacturing Companies. In: Lödding H., Riedel R., Thoben KD., von Cieminski G., Kiritsis D. (eds) Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing. APMS 2017. IFIP Advances in Information and Communication Technology, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-319-66923-6_17

Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, B. H., & Noh, S. (2016). Smart Manufacturing: Past Research, Present Findings, and Future Directions. International Journal of Precision Engineering and Manufacturing-Green Technology, v. 3, n. 1, p. 111-128. https://doi.org/10.1007/s40684-016-0015-5

Katsma, C., Moonen, H., & van Hillegersberg, J. (2011). Supply chain systems maturing towards the Internet-of-Things: a framework. In: 24th Bled eConference eFuture: Creating Solutions for the Individual, Organisations and Society Proceedings, pp. 478–494.

Klotzer, C., & Pflaum, A. (2017). Toward the development of a maturity model for digitalization within the manufacturing industry’s supply chain. In: Proceedings of the 50th Hawaii International Conference on System Sciences. Waikoloa Village, p. 4210-4219. https://doi.org/10.24251/hicss.2017.509

Kohlegger, M., Maier, R., & Thalmann, S. (2009). Understanding Maturity Models Results of a structured Content Analysis.In: IKNOW’ 09 and I-SEMANTICS’ 09. Graz, Austria, p. 51-61. Recuperado em 10 fevereiro, 2020, de http://iwi.uibk.ac.at/download/downloads/Publikationen/KMM.pdf

Leyh, C., Schäffer, T., Bley, K., & Forstenhäusler, S. (2016). SIMMI 4.0-a maturity model for classifying the enterprise-wide it and software landscape focusing on Industry 4.0. In: Federated Conference on Computer Science and Information Systems (FedCSIS), p. 1297- 1302. https://doi.org/10.15439/2016f478

LI, X., Li, D., Wan, J., Vasilakos, A. V., Lai, C-F., & Wang, S. (2017). A review of industrial wireless networks in the context of Industry 4.0. Wireless Networks, v. 23, n. 1, p. 23-41. https://doi.org/10.1007/s11276-015-1133-7

Lictblau, K., Stich, V., Bertenrath, R., Blum, M., Bleider, M., Millack, A., Schmitt, K., Schmitz, E., & Schroter, M. (2015). Industrie 4.0 Readiness. Impuls-Stiftung des VDMA Aachen-Köln, 52, p. 1–77.

Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, v. 6, p. 1-10. https://doi.org/10.1016/j.jii.2017.04.005

Marcon, P., Zezulka, F., Vesely, I., Szabo, Z., Roubal, Z., Sajdi, O., Gescheidtova, E., & Dohnal, P. (2017). Communication technology for industry 4.0. In: Progress In Electromagnetics Research Symposium-Spring (PIERS), p. 1694-1697. https://doi.org/10.1109/piers.2017.8262021

Masteika, I., & Cepinskis, J. (2015). Dynamic capabilities in supply chain management. Procedia – Social and Behavioral Sciences, v. 213, n. 1, p. 830-835. https://doi.org/10.1016/j.sbspro.2015.11.485

Merkel, L., Atug, J., Merthar, L., Schultz, C., Braunreuther, S., & Reinhart, G. (2017). Teaching Smart Production: An Insight into the Learning Factory for Cyber-Physical Production Systems (LVP). Procedia Manufacturing, v. 9, p. 269-274. https://doi.org/10.1016/j.promfg.2017.04.034

Nolan, R. L. Managing the computer resource: a stage hypothesis. Communications of the ACM, v. 16, n. 7, p. 399-405, 1973. https://doi.org/10.1145/362280.362284

O'Donovan, P., Bruton, K., & O'Sullivan, D. T. (2016). IAMM: A maturity model for measuring industrial analytics capabilities in large-scale manufacturing facilities. International. Journal of Prognostics and Health Management, v. 7, n. 32, p. 1-11.

Posada, J., Toro, C., Barandiaran, I., Oyarzun, D., Stricker, D., Amicis, R., Pinto, E. B., Eisert, P., Dollner, J., & Vallarino, I. (2015). Visual Computing as a Key Enabling Technology for Industrie 4.0 and Industrial Internet. IEEE Computer Graphics and Applications, v. 35, n. 2, p. 26-40. https://doi.org/10.1109/mcg.2015.45

Rajnai, Z., & Kocsis, I. (2018). Assessing industry 4.0 readiness of enterprises. In: IEEE 16th World Symposium on Applied Machine Intelligence and Informatics (SAMI), p. 225-230, https://doi.org/10.1109/sami.2018.8324844

Roblek, V., Mesko, M., & Krapez, A. (2016). A complex view of Industry 4.0. Sage Open, v. 6, n. 2. https://doi.org/10.1177/2158244016653987

Rutner, S. M., & Langley, J. C. (2000). Logistics value: definition, process and measurement. The International Journal of Logistics Management, v. 11, n. 2, p. 73-82. https://doi.org/10.1108/09574090010806173

Santos, R.C.; Martinho, J. L. (2019). An Industry 4.0 maturity model proposal. Journal of Manufacturing Technology Management, v. ahead-of-print, n. ahead-of-print. https://doi.org/10.1108/jmtm-09-2018-0284

Schluga, O., Bauer, E., Bicaku, A., Maksuti, S., Tauber., & Wohner, A. (2018). Operations security evaluation of IaaS-cloud backend for industry 4.0. In: Proceedings of the 8th International Conference on Cloud Computing and Services Science, v. 1, p. 392-399. https://doi.org/10.5220/0006683103920399

Schuh, G., Anderl, R., Dumitrescu, R., Kruger, A., & Hompel, M. (2020). Industrie 4.0 maturity index. Managing the Digital Transformation of Companies. ACATECH Study (updated 2020). Recuperado em 5 maio, 2020, de https://en.acatech.de/publication/industrie-4-0-maturity-index-update-2020/

Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, v. 52, p. 161-166, https://doi.org/10.1016/j.procir.2016.07.040

Schwab, K. The Fourth Industrial Revolution. Crown Business: New York, 1 ed., 2016.

Simpson, J.A., & Weiner, E. S. C. The Oxford English dictionary. New York: Oxford University Press, 2 ed., 1989.

Stark J. (2015) Product Lifecycle Management. In: Product Lifecycle Management (Volume 1). Decision Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-17440-2_1

Stock, J. R., & Boyer, S. L. (2009). Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management, v. 39, n. 8, p. 690-711. https://doi.org/10.1108/09600030910996323

Thoben, K-D., Wiesner, S. A., & Wuest, T. (2017). “Industrie 4.0” and smart manufacturing - a review of research issues and application examples. International Journal of Automation Technology, v. 11, n. 1, p. 4-16. https://doi.org/10.20965/ijat.2017.p0004

Tonelli, F., Demartini, M., Loleo, A., & Testa, C. (2016). A novel methodology for manufacturing firms value modeling and mapping to improve operational performance in the industry 4.0 Era. Procedia CIRP, v. 57, p. 122-127. https://doi.org/10.1016/j.procir.2016.11.022

Van Looy, A., De Backer, M., Poels, G., & Snoeck, M. (2013). Choosing the right business process maturity model. Information and Management, v. 50, n. 7, p. 466-488. https://doi.org/10.1016/j.im.2013.06.002

Wang, S., Wan, J., Zhang, D., Li, D., & Zhang, C. (2016). Towards smart factory for industry 4.0: a self-organized multi-agent system with Big-Data based feedback and coordination. Computer Networks, v. 101, p. 158-168. https://doi.org/10.1016/j.comnet.2015.12.017

Weber, C., Königsberger, J., Kassner, L., & Mitschang, B. (2017). M2DDM-a maturity model for data-driven manufacturing. Procedia CIRP, v. 63, p. 173-178. https://doi.org/10.1016/j.procir.2017.03.309

Westermann, T., Anacker, H., Dumitrescu, R., & Czaja, A. (2016). Reference architecture and maturity levels for Cyber-Physical Systems in the mechanical engineering industry. In: International Symposiumon Systems Engineering. Edinburgh: [s. n.], p. 1-6. https://doi.org/10.1109/syseng.2016.7753153

Weyer, S., Schmitt, M., Ohmer, M., & Gorecky, D. (2015). Towards Industry 4.0-Standardization as the crucial challenge for highly modular, multi-vendor production systems. Ifac Papersonline, v. 48, n. 3, p. 579-584. https://doi.org/10.1016/j.ifacol.2015.06.143

Xu, X., Hua, Q. (2017). Industrial Big-Data Analysis in Smart Factory: current status and research strategies. IEEE Access, v. 5, p. 17543-17555. https://doi.org/10.1109/access.2017.2741105

An Industry 4.0 Maturity Model Applied to the automotive supply chain

Authors

DOI:

Keywords:

Abstract

Author Biographies

Luis Rigato Vasconcellos, FGV / EAESP

Fabiano Rodrigues, ESPM

References

Downloads

Published

How to Cite

Issue

Section

License

Make a Submission

indexing

Keywords

visitors