<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume>4</Volume>
      <Issue>Serial Number 12</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>09</Month>
        <Day>20</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Providing a Model for Intelligent Monitoring of Maintenance in the Railway Industry</ArticleTitle>
    <VernacularTitle>Providing a Model for Intelligent Monitoring of Maintenance in the Railway Industry</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>9</LastPage>
    <ELocationID EIdType="doi">10.61838/kman.jrmde.126</ELocationID>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2025</Year>
        <Month>03</Month>
        <Day>17</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The aim of this study was to present a model for intelligent monitoring of maintenance in the railway industry. Therefore, in terms of purpose, it is an applied research, as in addition to its informative and scientific aspects, it also has practical implications for various companies and organizations, particularly in the railway industry. Considering the aim and nature of the study, the research method is qualitative. Moreover, since this research seeks to design a model, it is exploratory in nature. The results indicated that the intelligent monitoring model for maintenance in the railway industry consists of: data and repair management (data management and interactive dashboards, resource management and repair optimization, scalability and integration of systems and sensors), system and maintenance management (sensor management and system maintenance, data analysis and anomaly detection, alert systems and data monitoring), monitoring and integration (data management and system integration, performance monitoring and system optimization, prediction and preventive maintenance), optimization and customization (improving user experience and customization, collecting and analyzing user feedback, system optimization), security and maintenance (maintenance management and production optimization, data analysis and machine learning, data security and regulatory compliance), and usability and human resources (security and user design, monitoring and maintenance, human resource training and development).&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Intelligent monitoring</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">maintenance</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">railway industry</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalrmde.com/index.php/jrmde/article/download/126/162</ArchiveCopySource>
  </Article>
</ArticleSet>
