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Journal cover: Construction Innovation: Information, Process, Management

Construction Innovation: Information, Process, Management

ISSN: 1471-4175

Online from: 2001

Subject Area: Built Environment

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Modelling construction material logistics system with stochastic Petri nets


Document Information:
Title:Modelling construction material logistics system with stochastic Petri nets
Author(s):S. Thomas Ng, (Department of Civil Engineering, The University of Hong Kong, Hong Kong), Yuan Fang, (Department of Civil Engineering, The University of Hong Kong, Hong Kong), Onuegbu O. Ugwu, (JU Consulting & Research Services Limited, Kowloon, Hong Kong)
Citation:S. Thomas Ng, Yuan Fang, Onuegbu O. Ugwu, (2008) "Modelling construction material logistics system with stochastic Petri nets", Construction Innovation: Information, Process, Management, Vol. 8 Iss: 1, pp.46 - 60
Keywords:Construction materials, Materials management, Modelling, Stochastic modelling
Article type:Research paper
DOI:10.1108/14714170810846512 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – The purpose of this paper is to examine the potential of applying Petri nets to improve construction material logistics analysis and modelling.

Design/methodology/approach – The characteristics of construction logistics are unveiled by analysing the existing practices of logistics management. In views of the dynamic nature of construction logistics problem, a stochastic Petri nets (SPNs) approach is proposed to tackle the time-evolution property. Using a simulation package called PetriTool™ a simulation model is developed. Finally, a case example is applied to illustrate the way in which SPNs is used for analysing and modelling construction material logistics problems.

Findings – The results indicate that the impacts triggered by variations in delivery lead-time and changes in delivery quantities can be approximated thereby facilitating decision makers to devise a more reliable and optimal materials management plan for construction projects.

Research limitations/implications – The complex routing patterns in demand analysis and materials procurement methods that results in the enlarged supply chains have not been considered in this paper.

Practical implications – The lack of a simple but powerful formalism to analyse and model the decision process under a dynamic environment hinders the implementation of efficient logistics systems in the construction industry. The SPNs model presented in this paper can support planners and managers in making construction logistics management decisions under dynamic environment.

Originality/value – This paper demonstrates that the time-based SPNs can offer more enriched solutions especially when modelling the time-evolution behaviours of construction logistics.



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