Abstract The aim of the present work is to define and to optimize an assembly line that processes parts of medium/large dimension. As the assembly line processes large parts, some operational constraints arise, which for example are assembly to order production, just in time production, etc. The objective functions are minimum Earliness and minimum Tardiness stated to a given level of working stations saturation. To achieve these purposes we use two industrial software: the first is a Discrete Event Simulation (DES) package WITNESS 14 by Lanner Group, the second is a design optimization and process integration package, MODE-FRONTIER by Esteco. The DES software allows us to produce a simulation model for the assembly line. The optimization has carried out in three steps. First step is a multi-objective optimization cycle with genetic algorithm that generates a Pareto Frontier solutions; second step is a methodology that clusters the Pareto Frontier in different groups. A set of simplifications characterises this second step with the aim of reducing both the number of inputs and the objective functions. The third step is a mono-objective optimization cycle that allows us to reach a solution by means of a simplex algorithm. This method offers a way to solve scheduling problem of a complex production plant constrained to respect a management policy.

Assembly Line Management: Multi-Objective Optimization

NICOLICH, MARINO;POLONI, CARLO
2015

Abstract

Abstract The aim of the present work is to define and to optimize an assembly line that processes parts of medium/large dimension. As the assembly line processes large parts, some operational constraints arise, which for example are assembly to order production, just in time production, etc. The objective functions are minimum Earliness and minimum Tardiness stated to a given level of working stations saturation. To achieve these purposes we use two industrial software: the first is a Discrete Event Simulation (DES) package WITNESS 14 by Lanner Group, the second is a design optimization and process integration package, MODE-FRONTIER by Esteco. The DES software allows us to produce a simulation model for the assembly line. The optimization has carried out in three steps. First step is a multi-objective optimization cycle with genetic algorithm that generates a Pareto Frontier solutions; second step is a methodology that clusters the Pareto Frontier in different groups. A set of simplifications characterises this second step with the aim of reducing both the number of inputs and the objective functions. The third step is a mono-objective optimization cycle that allows us to reach a solution by means of a simplex algorithm. This method offers a way to solve scheduling problem of a complex production plant constrained to respect a management policy.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11368/2847947
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