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

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 p...

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Bibliographic Details
Published inProduction & manufacturing research Vol. 7; no. 1; pp. 335 - 349
Main Authors Khan, Zalan Mahmood Ayaz, Saeidlou, Salman, Saadat, Mozafar
Format Journal Article
LanguageEnglish
Published Taylor & Francis 01.01.2019
Taylor & Francis Group
Subjects
decision tree
ontology
Predictive model
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Waikato environment for knowledge analysis WEKA
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Summary: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.
ISSN:2169-3277
2169-3277
DOI:10.1080/21693277.2019.1621228