Optimize the average annual cost of a bus fleet has become an increasing concerning in transport companies management around the world. Nowadays, there are many tools available to assist managerials decisions and, one of the most used, is the cost analysis of the life cycle of an asset, known as ''Life Cycle Cost''. Characterized by performing deterministcs analysis of the situation, allows the administration evaluate the process of fleet replacement however is limited by not contemplating certain intrinsic variations related to vehicles and for disregarding variables related to contingencies of fleet use. The main purpose of this study is to develop a combined model of support to asset management based in the association of the Life Cycle Cost tool and the math model of Monte Carlo Simulation, by performing a stochastic analysis considering both, age and average annual mileage, for optimum vehicle replacement. The utilized method was applied in a spanish urban transport fleet and the results indicates that the use of the stochastic model was more effective than the use of the deterministic model.
Resumo:Otimizar o valor do custo médio anual, de uma frota de ônibus, tem se tornado uma preocupação, cada vez maior, na gestão das empresas de transporte em todo mundo. Atualmente, existem várias ferramentas disponíveis para auxiliar as decisões gerenciais e, uma da mais utilizadas, é a análise do custo do ciclo de vida de um ativo, conhecida como "Life Cycle Cost". Caracterizada por executar uma análise determinística da situação, permite à gestão, avaliar o processo de substituição da frota, porém, mostra-se limitada, por não contemplar certas variações intrínsecas aos veículos e por, desconsiderar variáveis relacionadas às contingências de uso da frota. O objetivo principal deste trabalho é desenvolver um modelo combinado de apoio ao gerenciamento de ativos, baseado na associação entre a ferramenta Life Cycle Cost e o modelo matemático de Simulação de Monte Carlo, mediante a realização de uma análise estocástica, considerando tanto a idade, quanto a quilometragem média anual para substituição ótima de um veículo. O método utilizado foi aplicado em uma frota de transporte urbano brasileira, e os resultados indicam que o uso do modelo estocástico foi mais eficiente que a utilização de modelo único determinístico.
Palavras-chaves:Life Cycle Cost. Simulação de Monte-Carlo. Otimização. Substituição de Frota. Análise de Custo.
Abstract:The optimization of the annual average cost for a bus fleet had become an important issue for the managers of transport companies worldwide. Currently, there are several available tools to support managerial decision making. One of the most used techniques to analyze is the deterministic method named "Life Cycle Cost" which allows the user to assess the replacement moment. However, this method is limited because it does not consider all the possible intrinsic variations in the equipment or the possible modifications in the utilization level. This paper objective is to develop a tool to support asset's management through the combination of the Life Cycle Cost and the Monte Carlo Simulation approaches, which forms a stochastic analytical model that considers age, annual mileage for the optimal replacement fleet. For this paper's development, data obtained from a Brazilian company were employed. The results show that the use of this combined tool is more efficient that the deterministic model.
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