Assessment of Ergonomic Compatibility on the Selection of Advanced Manufacturing Technology

  • Aide Maldonado-MacíasEmail author
  • Arturo Realyvásquez
  • Jorge Luis García-Alcaraz
  • Giner Alor-Hernández
  • Jorge Limón-Romero
  • Liliana Avelar-Sosa
Part of the Intelligent Systems Reference Library book series (ISRL, volume 120)


This paper proposes the development of an expert system for ergonomic compatibility assessment on the selection of Advanced Manufacturing Technology (AMT). Actual models for AMT assessment neglect Human Factors and Ergonomic (HFE) attributes and present deficiencies such as high time consumption and complexity. This approach proposes a novel axiomatic design methodology under fuzzy environment including two stages: the generation of fuzzy If-Then rules using Mamdani’s fuzzy inference system and the development of the system by mean of experts’ opinions. A numerical example is presented for the selection of three CNC milling machines using the Weighted Ergonomic Incompatibility Content (WEIC). The expert system leads to the selection of the best alternative containing the minimum WEIC, as the one that better satisfies ergonomic requirements. Development and application of the system may help provide an easier, faster, single or group ergonomic assessment on AMT selection by promoting safer and more ergonomic workplaces in manufacturing companies.


Advanced manufacturing technology assessment Ergonomic incompatibility content Expert system 



Authors wish to acknowledge all the reviewers who helped improve this paper through their valuable suggestions and comments. Similarly, we are sincerely thankful to the experts in Advanced Manufacturing Technology and Human Factors and Ergonomics from CENALTEC—National Center of High Technology of Ciudad Juarez, the Autonomous University of Ciudad Juarez, FESTO-Juarez automation, and the Technological Institute of Ciudad Juarez for their priceless contribution of knowledge in this project.


  1. 1.
    O’kane, J., Spenceley, J., Taylor, R.: Simulation as an essential tool for advanced manufacturing technology problems. J. Mater. Process. Technol. 107(1), 412–424 (2000)Google Scholar
  2. 2.
    Mohanty, R., Deshmukh, S.: Advanced manufacturing technology selection: a strategic model for learning and evaluation. Int. J. Prod. Econ. 55(3), 295–307 (1998)CrossRefGoogle Scholar
  3. 3.
    Ordoobadi, S.M., Mulvaney, N.J.: Development of a justification tool for advanced manufacturing technologies: system-wide benefits value analysis. J. Eng. Tech. Manage. 18(2), 157–184 (2001). doi: 10.1016/S0923-4748(01)00033-9 CrossRefGoogle Scholar
  4. 4.
    Maldonado, A.: Modelo de Evaluación Ergonómica para la Planeación y Selección de Tecnología de Manufactura Avanzada. Instituto Tecnológico de Ciudad Juárez, Disertación Doctoral (2009)Google Scholar
  5. 5.
    Bandrés, M.: Ergonomía. 20 preguntas para aplicar la Ergonomía en la empresa, Segunda edición, p. 25. MAPFRE, Madrid (2001)Google Scholar
  6. 6.
    Chuu, S.-J.: Selecting the advanced manufacturing technology using fuzzy multiple attributes group decision making with multiple fuzzy information. Comput. Ind. Eng. 57(3), 1033–1042 (2009). doi: 10.1016/j.cie.2009.04.011 CrossRefGoogle Scholar
  7. 7.
    Ertugrul Karsak, E., Tolga, E.: Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments. Int. J. Prod. Econ. 69(1), 49–64 (2001). doi: 10.1016/S0925-5273(00)00081-5 CrossRefGoogle Scholar
  8. 8.
    Maldonado, A., García, J.L., Alvarado, A., Balderrama, C.O.: A hierarchical fuzzy axiomatic design methodology for ergonomic compatibility evaluation of advanced manufacturing technology. Int. J. Adv. Manuf. Technol. 66(1–4), 171–186 (2013)CrossRefGoogle Scholar
  9. 9.
    Maldonado-Macías, A., Guillén-Anaya, L., Barrón-Díaz, L., García-Alcaraz, L.: Evaluación Ergonómica para la Selección de Tecnología de Manufactura Avanzada: una Propuesta de SoftwareGoogle Scholar
  10. 10.
    He, W., Zhang, Y., Lee, K., Fuh, J., Nee, A.: Automated process parameter resetting for injection moulding: a fuzzy-neuro approach. J. Intell. Manuf. 9(1), 17–27 (1998)CrossRefGoogle Scholar
  11. 11.
    Prasad, N.R., Walker, C.L. Walker, E.A.: A First Course in Fuzzy and Neural Control: CHAPMAN and HALL/CRC-2003 (2003)Google Scholar
  12. 12.
    Azadegan, A., Porobic, L., Ghazinoory, S., Samouei, P., Saman Kheirkhah, A.: Fuzzy logic in manufacturing: a review of literature and a specialized application. Int. J. Prod. Econ. 132(2), 258–270 (2011). doi: 10.1016/j.ijpe.2011.04.018 CrossRefGoogle Scholar
  13. 13.
    Sivanandam, S., Sumathi, S., Deepa, S.: Introduction to Fuzzy Logic Using Matlab, vol. 1. Springer (2007)Google Scholar
  14. 14.
    Iancu, I.: A Mamdani type fuzzy logic controller: INTECH Open Access Publisher (2012)Google Scholar
  15. 15.
    Kahraman, C., Çebı˙, S.: A new multi-attribute decision making method: hierarchical fuzzy axiomatic design. Expert Syst. Appl. 36(3, Part 1), 4848–4861 (2009). doi: 10.1016/j.eswa.2008.05.041
  16. 16.
    Suh, N.P.: Axiomatic design theory for systems. Res. Eng. Design 10(4), 189–209 (1998)CrossRefGoogle Scholar
  17. 17.
    Karwowski, W.: Ergonomics and human factors: the paradigms for science, engineering, design, technology and management of human-compatible systems. Ergonomics 48(5), 436–463 (2005)CrossRefGoogle Scholar
  18. 18.
    Celik, M., Kahraman, C., Cebi, S., Er, I.D.: Fuzzy axiomatic design-based performance evaluation model for docking facilities in shipbuilding industry: the case of Turkish shipyards. Expert Syst. Appl. 36(1), 599–615 (2009)CrossRefGoogle Scholar
  19. 19.
    Azadeh, A., Fam, I.M., Khoshnoud, M., Nikafrouz, M.: Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSE) and ergonomics system: the case of a gas refinery. Inf. Sci. 178(22), 4280–4300 (2008). doi: 10.1016/j.ins.2008.06.026 CrossRefGoogle Scholar
  20. 20.
    Corlet, E., Clark, T.: The ergonomics of workspaces and machines. Taylor & Francis, Bristol (1995)Google Scholar
  21. 21.
    Atalay, K.D., Eraslan, E.: Multi-criteria usability evaluation of electronic devices in a fuzzy environment. Human Factors Ergon. Manuf. Serv. Ind. 24(3), 336–347 (2014)CrossRefGoogle Scholar
  22. 22.
    Balogh, I., Ohlsson, K., Hansson, G.-Å., Engström, T., Skerfving, S.: Increasing the degree of automation in a production system: consequences for the physical workload. Int. J. Ind. Ergon. 36(4), 353–365 (2006)CrossRefGoogle Scholar
  23. 23.
    Battini, D., Faccio, M., Persona, A., Sgarbossa, F.: New methodological framework to improve productivity and ergonomics in assembly system design. Int. J. Ind. Ergon. 41(1), 30–42 (2011)CrossRefGoogle Scholar
  24. 24.
    Battini, D., Persona, A., Sgarbossa, F.: Innovative real-time system to integrate ergonomic evaluations into warehouse design and management. Comput. Ind. Eng. 77, 1–10 (2014)CrossRefGoogle Scholar
  25. 25.
    Besnard, D., Cacitti, L.: Interface changes causing accidents. An empirical study of negative transfer. Int. J. Hum. Comput. Stud. 62(1), 105–125 (2005)CrossRefGoogle Scholar
  26. 26.
    Maldonado-Macías, A., Alvarado, A., García, J.L., Balderrama, C.O.: Intuitionistic fuzzy TOPSIS for ergonomic compatibility evaluation of advanced manufacturing technology. Int. J. Adv. Manuf. Technol. 70(9–12), 2283–2292 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Aide Maldonado-Macías
    • 1
    Email author
  • Arturo Realyvásquez
    • 1
  • Jorge Luis García-Alcaraz
    • 1
  • Giner Alor-Hernández
    • 2
  • Jorge Limón-Romero
    • 3
  • Liliana Avelar-Sosa
    • 1
  1. 1.Departamento de Ingeniería Industrial y de ManufacturaUniversidad Autónoma de Ciudad JuárezCiudad JuarezMexico
  2. 2.Division of Research and Postgraduate StudiesInstituto Tecnológico de OrizabaOrizabaMexico
  3. 3.Universidad Autónoma de Baja CaliforniaEnsenadaMexico

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