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A multicriteria decision model to support the selection of suppliers of motor repair services

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Abstract

Electric power consumption by sanitation companies represents the second largest operating cost item, which can be explained by the many electric motors that operate in their facilities. An electric motor is an electric device that is capable of transforming electrical energy to mechanical energy. These devices are responsible for more than 80 % of all electricity consumed in the world. Because they are machines, they can fail, and consequently, repairs are needed. Many companies choose to outsource the repair service of broken electric motors, and most capital cities have many suppliers. Selecting or classifying these suppliers into groups to fulfill strategic goals is a significant challenge. This paper presents a model to classify businesses that provide electric motor repair services. This model can be used to pre-qualify suppliers. To this end, the PROMSORT multicriteria classification method was applied to classify suppliers in a non-compensatory way according to the evaluation criteria. The applied method enabled the classification of the evaluated companies in four groups based on attributes related to their facilities, their professionals, and their experience. The results showed that the model is effective for this application and it can be applied in other contexts also related to classification problem.

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Authors and Affiliations

  1. UFPE, Recife, Brazil

    André Luiz de Oliveira e Silva, Cristiano Alexandre Virginio Cavalcante & Natália Veloso Caldas de Vasconcelos

Authors
  1. André Luiz de Oliveira e Silva
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  2. Cristiano Alexandre Virginio Cavalcante
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  3. Natália Veloso Caldas de Vasconcelos
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Correspondence to Cristiano Alexandre Virginio Cavalcante.

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de Oliveira e Silva, A.L., Cavalcante, C.A.V. & de Vasconcelos, N.V.C. A multicriteria decision model to support the selection of suppliers of motor repair services. Int J Adv Manuf Technol 84, 523–532 (2016). https://doi.org/10.1007/s00170-015-7673-2

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  • DOI: https://doi.org/10.1007/s00170-015-7673-2

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