Productivity improvement in the wood industry using simulation and artificial intelligence

Felipe Baesler · Milton Moraga · Francisco J. Ramis

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Simulation Techniques and Applications Scheduling and Optimization Algorithms Simulation and Modeling Applications

Abstract

The objective of this article is to present the results obtained after using a simulation optimization methodology applied to a production line from a secondary manufacturing wood processing plant of a well known Chilean mill. For this reason a simulation model constructed in ARENA, was integrated to a genetic algorithm heuristic. The results obtained show that using a different configuration of the plant resources, it is possible to reduce the total average cycle time in 18%. The resource configuration needed to reach this result was obtained evaluating just 1.6% of the total number of possible combinations.

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1997Using evolutionary algorithms and simulation for the optimization of manufacturing systems

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2004The use of simulation and design of experiments for productivity improvement in the sawmill industry

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