• DocumentCode
    3576795
  • Title

    Model of human reliability for manual workers in assembly lines

  • Author

    Baez, Y.A. ; Rodriguez, M.A. ; Limon, J. ; Tlapa, D.A.

  • Author_Institution
    Fac. of Eng., Archit. & Design, Autonomous Univ. of Baja California, Ensenada, Mexico
  • fYear
    2014
  • Firstpage
    1448
  • Lastpage
    1452
  • Abstract
    This study presents the construction of a human reliability model for assembly line manual workers, using Cox´s Proportional Risk model. Nine factors were identified in 120 assembly line operators using psychometric tests. Subsequently, the factors of stress, motivation, memory, and personality were identified, using a multiple linear regression analysis, as those that significantly contribute to the occurrence of human error and, together, are considered as the worker´s operational environment. The parameters were defined for the distribution of base failures for modeling the rate of human risk. The model obtained enables the establishment of the contribution of each factor to the probability that human errors will be committed within a determined period of time.
  • Keywords
    assembling; human resource management; occupational stress; psychometric testing; regression analysis; reliability; risk management; Cox proportional risk model; assembly line manual workers; assembly line operators; assembly lines; base failure distribution; human error probability; human reliability model; human risk rate; memory factor; motivation factor; multiple linear regression analysis; personality factor; psychometric test; stress factor; worker operational environment; Accidents; Assembly; Linear regression; Manuals; Mathematical model; Reliability; Stress; Cox´s Proportional Risk model; Human reliability; errors; multiple linear regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/IEEM.2014.7058878
  • Filename
    7058878