Abstract

ABSTRACTThis 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.

Highlights

  • In the late 1980s, when transportation became cheap, easier and fast, the manufacturing industry started to become globalized

  • The methodology presents the mapping of a PROSA (Product-ResourceOrder-Staff Architecture) based ontology model on a decision tree, which was created with the Waikato Environment for Knowledge Analysis (WEKA) application

  • The ontology was based on the decision tree model, which was modelled in WEKA

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Summary

Introduction

In the late 1980s, when transportation became cheap, easier and fast, the manufacturing industry started to become globalized. Due to this globalization, the multinational companies connected their geographically dispersed plants by synergetic networks (Ferdows, 1989, 1997; Ghoshal & Bartlett, 1990). Apart from the multinational enterprise perspective, the ease of communication enabled small enterprises to work with large enterprises. Large enterprises outsource their non-core competencies to small enterprises. The collaboration of a large enterprise and a number of small enterprises make up a large manufacturing network (Jules, Saadat, & Saeidlou, 2013). Due to increase in the number of small and medium manufacturing companies, the GFM srl was facing the difficulty of scheduling the newly received orders

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