Ontology-based decision tree model for prediction in a manufacturing network

Zalan Mahmood Ayaz Khan, Salman Saeidlou, Mozafar Saadat

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
97 Downloads (Pure)

Abstract

This paper aims to create a predictive model, which will assist in the allocation of newly received orders in a manufacturing network. The manufacturing network, which is taken as a case study in this research, consists of more than 300 small manufacturing enterprises with a central company as the project managing integrator. The methodology presents the mapping of a PROSA (Product-Resource-Order-Staff Architecture) based ontology model on a decision tree, which was created with the Waikato Environment for Knowledge Analysis (WEKA) application. Furthermore, the methodology also demonstrates the formulation of the Semantic Web Rule Language (SWRL) rules from the WEKA decision tree with the help of MATLAB programming. The paper validated the result generated by the ontology model with the results of the decision tree model.
Original languageEnglish
Pages (from-to)335-349
Number of pages15
JournalProduction & Manufacturing Research
Volume7
Issue number1
Early online date30 May 2019
DOIs
Publication statusPublished - 2019

Keywords

  • Predictive model
  • ontology
  • decision tree
  • Waikato environment for knowledge analysis WEKA
  • Protege

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