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<records>
  <record>
    <language>eng</language>
    <publisher>Science and Education Publishing</publisher>
    <journalTitle>American Journal of Industrial Engineering</journalTitle>
    <eissn>2377-4339</eissn>
    <publicationDate>2026-04-19</publicationDate>
    <volume>10</volume>
    <issue>1</issue>
    <startPage>8</startPage>
    <endPage>11</endPage>
    <doi>10.12691/ajie-10-1-1</doi>
    <publisherRecordId>AJIE20261011</publisherRecordId>
    <documentType>article</documentType>
    <title language="eng">Performance-Based Selection of Diesel Generator Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)</title>
    <authors>
      <author>
        <name>Friday Erhimudia Ukrakpor</name>
        <email>ukrakporf@gmail.com</email>
        <affiliationId>1</affiliationId>
      </author>
      <author>
        <name>Musa Momodu Omokhafe</name>
        <affiliationId>1</affiliationId>
      </author>
      <author>
        <name>Chukwuka Uboh</name>
        <affiliationId>1</affiliationId>
      </author>
    </authors>
    <affiliationsList>
      <affiliationName affiliationId="1">Department of Mechanical Engineering, Delta State University, Abraka, Nigeria</affiliationName>
    </affiliationsList>
    <abstract language="eng">The selection of diesel generators is a critical decision in environments requiring reliable and uninterrupted power supply. This study presents a structured multi-criteria decision-making (MCDM) approach for evaluating and selecting the most suitable diesel generator using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Four key performance criteria, fuel consumption, lifespan, estimated maintenance time, and mean time between failures (MTBF)were considered. Criteria weights were determined using the Analytic Hierarchy Process (AHP), ensuring consistency and objectivity. A case study involving four 75 kVA diesel generator alternatives was conducted. The results indicate that Alternative C achieved the highest closeness coefficient (0.970), making it the most preferred option due to its superior reliability, longer lifespan, and lower maintenance requirements. The study demonstrates the effectiveness of integrating AHP and TOPSIS for rational and data-driven decision-making in equipment selection.</abstract>
    <fullTextUrl format="pdf">https://pubs.sciepub.com/ajie/10/1/1/ajie-10-1-1.pdf</fullTextUrl>
    <keywords language="eng">
      <keyword>Diesel generator</keyword>
      <keyword>TOPSIS</keyword>
      <keyword>AHP</keyword>
      <keyword>multi-criteria decision-making</keyword>
      <keyword>MTBF</keyword>
      <keyword>performance evaluation</keyword>
    </keywords>
  </record>
</records>