Development and implementation of a generic order release scheme for modelling material requirements planning-controlled finite-capacitated manufacturing environments

Development and implementation of a generic order release scheme for modelling material requirements planning-controlled finite-capacitated manufacturing environments

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Article ID: iaor20043541
Country: United Kingdom
Volume: 17
Issue: 6
Start Page Number: 561
End Page Number: 576
Publication Date: Sep 2004
Journal: International Journal of Computer Integrated Manufacturing
Authors: , ,
Abstract:

This paper presents the development and implementation of a generic order release scheme (ORS) to model material requirements planning (MRP)-controlled finite-capacitated manufacturing environments. The aim of this research work is to provide researchers and practitioners with a method, as described above, that leads to an accurate simulation of an MRP-controlled manufacturing environment, so that the effects of production fluctuations in this environment could be robustly modelled and analysed. The ORS is developed using SIMAN simulation language and visual basic applications (VBA) coding. The ORS is an agent, which integrates a planning and a control platform. The planning platform models an MRP system, whilst the control platform models a finite-capacitated manufacturing system. The planning system is developed using VBA, while the control system is developed using SIMAN and simulated in ARENA simulation software. The integration is achieved through an attributes assignment module, a part tagging module, an order release module and a routing activation module. The design and logic for the platforms and the ORS are discussed. The ORS is verified and validated through a case study approach in simulation. The simulation results show that the ORS has lucratively modelled the MRP commandments. It is suggested that researchers and practitioners could use and adapt the ORS and its generic principles in modelling MRP-controlled finite-capacitated manufacturing environments so that combinations of factors that could disrupt the production process could be examined.

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