The training of maintenance personnel for industry 4.0


  • Patricia Avitia-Carlos Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario 1000, Unidad Valle de Las Palmas, 22260 Tijuana, Baja California, México
  • Alex Bernardo Pimentel-Mendoza Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario 1000, Unidad Valle de Las Palmas, 22260 Tijuana, Baja California, México
  • José Luis Rodríguez-Verduzco Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario 1000, Unidad Valle de Las Palmas, 22260 Tijuana, Baja California, México
  • Bernabé Rodríguez-Tapia Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario 1000, Unidad Valle de Las Palmas, 22260 Tijuana, Baja California, México



Industry 4.0, industrial maintenance, technical formation


Industry 4.0 (I4.0) is characterized by the incorporation of digital technologies into manufacturing processes, giving them flexibility and the ability to adapt in real-time. The development of this type of industry is considered a competitive factor worldwide. However, the maintenance of I4.0 requires the presence of competent technical personnel capable of carrying out tasks of improvement and maintenance of highly digitized manufacturing systems. The Tijuana-Tecate metropolitan area is home to the manufacturing industry in the electronic, biomedical, and aerospace sectors, among others. The presence of this industry is fundamental to the region's economic activities. The objective of the work was to identify the training needs associated with the effective exercise of maintenance activities of technical and engineering personnel working in local companies; as well as the strategies they follow to retrain, and update said personnel. In this exploratory work, a documentary review is carried out regarding the technical skills required for the development and maintenance of Industry 4.0, followed by a semi-structured interview with five members of the local industry responsible for industrial maintenance areas. The instrument investigated dimensions such as 4.0 technologies used, local availability of qualified personnel, required skills, internal training schemes, and strategies for the retention and development of personnel. Results show that interviewed companies do not collaborate with education institutions to meet the training and updating needs of the sector. It is also identified a delay in the implementation of industry 4.0 technologies in the local industry and the predominance of traditional maintenance models since only one company reports the use of reliability-based maintenance. Future work consists of expanding the study focusing on a single sector of the manufacturing industry and conducting in-depth interviews aimed at designing joint industry-academia activities to register training standards that result in the certification of specific competencies.


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M. Compare, P. Baraldi and E. Zio, "Challenges to IoT-enabled Predictive Maintenance for Industry 4.0," IEEE Internet of Things Journal, pp. 1-13, 2019. DOI:

Y. Lu, "Industry 4.0: A survey of technologies, applications and open research issues," Journal of Industrial Information Integration, pp. 1-10, 2017. DOI:

A. Benešová and J. Tupa, "Requirements for Education and Qualification of People in Industry 4.0," Procedia Manufacturing, p. 2195 - 2202, 2017. DOI:

E. Jantunen, P. Sharma, J. Campos and D. Baglee, "Digitalization of Maintenance," in 2nd International Conference on System Reliability and Safety, Chengdu, China, 2017. DOI:

P. Poor, J. Basl and D. Zenisek, "Predictive Maintenance 4.0 as next evolution step in industrial maintenance development," in International Research Conference on Smart Computing and Systems Engineering (SCSE), Sri Lanka, 2019. DOI:

T. Zheng, M. Ardolino, A. Bacchetti and M. Perona, "The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review," International Journal of Production Research, vol. 59, no. 6, pp. 1922-1954, 2021. DOI:

J. M. Müller, "Business model innovation in small- and medium-sized enterprises," Journal of Manufacturing Technology Management, vol. 30, no. 8, pp. 1127-1142, 2019. DOI:

J. W. Veile and D. Kiel, "Lessons learned from Industry 4.0 implementation in the German manufacturing industry," Journal of Manufacturing Technology Management, vol. 31, no. 5, pp. 977-997, 2020. DOI:

"A new dynamic predictive maintenance framework using deep learning for failure prognostics," Reliability Engineering and System Safety, no. 188, pp. 251-262, 2019. DOI:

"Industry 4.0 technologies: Implementation patterns in manufacturing companies," International Journal of Production Economics, no. 210, pp. 15-26, 2019. DOI:

S. Ayad, L. S. Terrissa and N. Zerhouni, "An IoT Approach for Smart Maintenance," in International Conference on Advanced Systems and Electric Technologies (IC_ASET), Túnez, 2018. DOI:

D. Pal, J. Vain, S. Srinivasan and S. Ramaswamy, "Model-based maintenance scheduling in flexible modular automation systems," in 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2017. DOI:

D. TRAN ANH, K. DĄBROWSKI and K. SKRZYPEK, "The predictive maintenance concept in the maintenance department," Foundations of Management, vol. 10, 2010.

S. Gallego García and M. García García, "Industry 4.0 implications in production and maintenance management: An overview," in 8th Manufacturing Engineering Society International Conference, Madrid, 2019. DOI:

T. Zonta, C. A. da Costa, R. da Rosa Righi, M. J. de Lima, E. S. da Trindade and G. Pyng Li, "Predictive maintenance in the industry 4.0: A systematic literature review," Computers and Industrial Engineering, vol. 150, 2020. DOI:

M. D. Nardo, M. Madonna, P. Addonizio and M. Gallab, "A mapping analysis of maintenance in Industry 4.0," Journal of Applied Research and Technology, vol. 19, pp. 653-675, 2021. DOI:

"Maintenance transformation through Industry 4.0 technologies: A systematic literature review," Computers in Industry, no. 123, pp. 1-16, 2020. DOI:

G. Di Bona, V. Cesarotti, G. Arcese, and T. Gallo, "Implementation of Industry 4.0 technology: new opportunities and challenges for maintenance strategy," in International Conference on Industry 4.0 and Smart Manufacturing, 2021. DOI:

L. A. González Torres, M. A. Ibarra Cisneros and K. E. Cervantes Collado, "El impacto de las tecnologías de la información y comunicación en la industria manufacturera de Baja California," Región y sociedad, pp. 153-183, 2017. DOI:

J. Carrillo, R. Gomis, S. De los Santos, L. Covarrubias and M. Matus, "¿Podrán transitar los ingenieros a la Industria 4?0? Análisis industrial en Baja California," Entreciencias: Diálogos en la Sociedad del Conocimiento, vol. 22, no. 8, pp. 1-22, 2020. DOI:

IMPLAN, "Parques Industriales," Sociedad en Movimiento, no. XI, pp. 1-5, Julio-septiembre 2014.

A. Reyes Mendoza, M. d. l. Á. Silva-Olvera and K. Ramírez Barón, "Liderazgo emprendedor y la innovación en empresas manufactureras de Tecate, B.C., México," VinculaTégica, pp. 267-273, 2018.

Universidad Autónoma de Baja California, "Evaluación externa e interna del Programa Educativo Ingeniero en Mecatrónica," Mexicali, 2018.

D. Horváth and R. Z. Szabó, "Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities?" Technological Forecasting & Social Change, no. 146, pp. 119-132, 2019. DOI:

Monitor Económico, "Monitor Económico de Baja California," 2022. [Online]. Available: [Accessed 2022].

"Industry 4.0 and the human factor - A systems framework and analysis methodology for successful development," International Journal of Production Economics, no. 233, pp. 1-16, 2021. DOI:

S. M. Lee, D. Lee and Y. S. Kim, "The quality management ecosystem for predictive maintenance in the industry 4.0 era," International Journal of Quality Innovation, pp. 1-11, 2019. DOI:

Z. M. Çınar, A. A. Nuhu, Q. Zeeshan, O. Korhan, M. Asmael and B. Safaei, "Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0," Sustainability, pp. 1-42, 2020. DOI:

A. Bousdekis, D. Apostolou, and G. Mentzas, "Predictive Maintenance in the 4th Industrial Revolution: Benefits, Business Opportunities and Managerial Implications," IEEE Engineering Management Review, 2019. DOI:

A. Cachada, J. Barbosa, P. Leitão, C. A. S. Geraldes, L. Deusdado, J. Costa, C. Teixeira, J. Teixeira, A. H. Moreira, P. M. Moreira and L. Romero, "Maintenance 4.0: Intelligent and Predictive Maintenance System Architecture," in 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Torino, Italy, 2018. DOI:

J. Gebhardt, A. Grimm and L. M. Neugebauer, "Developments 4.0 Prospects on future requirements and impacts on work and vocational education," Journal of Technical Education (JOTED), pp. 117-133, 2015.

Technologies used by the companies interviewed. The order of presentation corresponds to the frequency of mention obtained in the responses. Source: Own elaboration based on the answers provided by the interviewees.



How to Cite

Avitia-Carlos, P., Pimentel-Mendoza, A. B., Rodríguez-Verduzco, J. L., & Rodríguez-Tapia, B. (2022). The training of maintenance personnel for industry 4.0 . REVISTA DE CIENCIAS TECNOLÓGICAS, 5(4), e192.

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