The present research work proposes a simulation-based tool for short period production planning in industrial plants. The tool has been specifically developed for a real manufacturing system that produces high pressure hoses in the south of Italy. During the developmental phase, an advanced simulation approach, based on programming code and tables for information storage, was adopted. As a result the proposed modelling architecture ensures flexibility and high computational efficiency and allows comparison of the system's performances under different production planning scenarios obtained by applying dispatching rules, Genetic Algorithms (GAs) and Ant Colony Optimisation (ACO) algorithms. The suitability of the simulation outputs is ensured by the verification and validation activities carried out in the developmental phase; furthermore, specific subroutines allow the full integration of the simulation model with the company's ERP system. Copyright © 2013 Inderscience Enterprises Ltd.

ON THE SHORT PERIOD PRODUCTION PLANNING IN INDUSTRIAL PLANTS: A REAL CASE STUDY

LONGO, Francesco
2013-01-01

Abstract

The present research work proposes a simulation-based tool for short period production planning in industrial plants. The tool has been specifically developed for a real manufacturing system that produces high pressure hoses in the south of Italy. During the developmental phase, an advanced simulation approach, based on programming code and tables for information storage, was adopted. As a result the proposed modelling architecture ensures flexibility and high computational efficiency and allows comparison of the system's performances under different production planning scenarios obtained by applying dispatching rules, Genetic Algorithms (GAs) and Ant Colony Optimisation (ACO) algorithms. The suitability of the simulation outputs is ensured by the verification and validation activities carried out in the developmental phase; furthermore, specific subroutines allow the full integration of the simulation model with the company's ERP system. Copyright © 2013 Inderscience Enterprises Ltd.
2013
Discrete event simulation; Genetic algorithms; Dispatching rules
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/125714
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