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

Authors: Francesco Longo; Letizia Nicoletti; Adriano O. Solis

Addresses: Department of Mechanical, Energy, and Management Engineering, University of Calabria, 87036 Rende, Cosenza, Italy ' Department of Mechanical, Energy, and Management Engineering, University of Calabria, 87036 Rende, Cosenza, Italy ' School of Administrative Studies, York University, Toronto, Ontario M3J 1P3, Canada

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).

Keywords: industrial plants; batch orders; modelling; simulation; economic analysis; genetic algorithms; performance evaluation; batch order manufacturing; furniture manufacturing; performance measures; flow time; fill rate; automated painting machines; shop order scheduling.

DOI: 10.1504/IJSCOM.2014.066496

International Journal of Service and Computing Oriented Manufacturing, 2014 Vol.1 No.4, pp.344 - 367

Received: 05 Mar 2014
Accepted: 24 Jul 2014
Published online: 31 Dec 2014 *

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