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Analyzing Pipe Production Fault Rates by Association Rules and Classification According to Working Conditions and Employee Characteristics

  • Deniz Demircioglu DirenEmail author
  • Hussein Al-Sanabani
  • Tugcen Hatipoglu
Conference paper
Part of the Lecture Notes in Management and Industrial Engineering book series (LNMIE)

Abstract

In order to survive in a competitive environment, companies are required to increase the productivity by identifying the factors that affect the failure rates. In this study, fault rates of a pipe manufacturing company are investigated. Therefore, based on data attributes such as demographic characteristics of employees, employee training, physical working conditions, social facilities etc. were gathered. Briefly, data were analyzed by association rules, correlation, and various classification algorithms. The association rules, measurements, and correlations of attributes are examined to understand the current situation. Then, based on this information, various classification algorithms have been used for estimation. The higher accuracy of the prediction, the greater results will occur. Therefore, the accuracy of the classification algorithms is compared and the algorithm with the highest performance is achieved.

Keywords

Association rule technique Classification algorithm Predictive model Descriptive model 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Deniz Demircioglu Diren
    • 1
    Email author
  • Hussein Al-Sanabani
    • 1
  • Tugcen Hatipoglu
    • 2
  1. 1.Department of Industrial EngineeringSakarya UniversitySakaryaTurkey
  2. 2.Department of Industrial EngineeringKocaeli UniversityKocaeliTurkey

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