Dimensionamento de equipes de trabalho por meio de modelos probabilísticos
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Data
2018-05-18
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Editor
Universidade Federal de Goiás
Resumo
This work proposes the modeling of a production system with three manufacturing units, in
order to allow the optimal dimensioning of maintainers and the accomplishment of a sensitivity
analysis that allows to evaluate the reliability of the obtained results. A Quasi-Birthand-
Death (QBD) process is used to model the productive units, and through infinitesimal
generators, the input probabilities for the developed code are obtained. Organizations usually
define their supporter teams empirically, which can compromise organizational strategies.
Thus, the code offers assistance in the decision making of these professionals. Thus,
three production units X, Y and Z were modeled and the minimum dimensioning of maintainers
that each unit had to be performed. Thus, the X unit with two maintainers provides
a 70% probability of remaining in operation, the Y unit with three provides 76%, and finally,
the Y unit with only one maintainer allows an 80% chance of remaining in operation. Bymeans
of the sensitivity analysis, it was noticed thatwhen disturbing the infinitesimal generator
the values of probability of operation tend to approximate to 100% whereas a maintainer is
added, however, when the fourth maintainer is added, there is little variation in the system.
However,when the system is stressed by the growth of the randomvariable t, the reliability of
the results tends to decrease, whereas with a maintainer, the probability of functioning falls
considerably over time, and in contrast, with four maintainers, the permanence of operating
state tends to be distant.
Descrição
Palavras-chave
Sistemas de produção, Processo de quase nascimento e morte, Demanda, Estratégias organizacionais, Systems of production, Quasi-birth–death process, Demand, Organizational strategies
Citação
FREITAS, C. M. F. Dimensionamento de equipes de trabalho por meio de modelos probabilísticos. 2018. 125 f. Dissertação (Mestrado em Modelagem e Otimização) - Universidade Federal de Goiás, Catalão, 2018.