This paper describes the development and application of a simulation model characterising an existing manufacturing system devoted to producing furniture for schools, universities and offices. The simulation model is equipped with dedicated animation and input/output sections, which allow changing various system parameters and monitoring multiple performance measures. The simulation model is also integrated with optimisation algorithms, specifically genetic algorithms. After verification and validation, the simulation model is used to pursue two different objectives: 1) evaluate the economic viability of acquiring new automated machines for the painting department; 2) investigate shop orders scheduling by using genetic algorithms. As far as the first objective is concerned, performance of the current production system is compared with that of the potential production scenario involving automated painting. An economic analysis based on the discounted payback period is also carried out. With respect to shop order scheduling, genetic algorithms are implemented as an additional module able to perform optimisation in terms of two fitness functions (flow time and fill rate).

Using simulation to investigate the performance of a batch order manufacturing system / Longo, Francesco; Nicoletti, L; Solis, A.. - In: INTERNATIONAL JOURNAL OF SERVICE AND COMPUTING ORIENTED MANUFACTURING. - ISSN 2045-1768. - 1:4(2014), pp. 344-367.

Using simulation to investigate the performance of a batch order manufacturing system

LONGO, Francesco;
2014

Abstract

This paper describes the development and application of a simulation model characterising an existing manufacturing system devoted to producing furniture for schools, universities and offices. The simulation model is equipped with dedicated animation and input/output sections, which allow changing various system parameters and monitoring multiple performance measures. The simulation model is also integrated with optimisation algorithms, specifically genetic algorithms. After verification and validation, the simulation model is used to pursue two different objectives: 1) evaluate the economic viability of acquiring new automated machines for the painting department; 2) investigate shop orders scheduling by using genetic algorithms. As far as the first objective is concerned, performance of the current production system is compared with that of the potential production scenario involving automated painting. An economic analysis based on the discounted payback period is also carried out. With respect to shop order scheduling, genetic algorithms are implemented as an additional module able to perform optimisation in terms of two fitness functions (flow time and fill rate).
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/135215
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