4 resultados para Monte Carlo, Método de

em Repositório Institucional da Universidade Estadual de São Paulo - UNESP


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Due to the increasing demand from clients and the search for better performances in the heavy vehicles industry, a progressive evolution in technology in a general way was needed. This paper uses a scientific method to validate, prior to its manufacture, the project of an agricultural wheel for sugar cane harvesters. Monte Carlo Simulation is used in conjunction with Finite Elements Method, in order to simulate the wheel's behavior in a cornering test, identify possible failure regions and get an estimate for its life under fatigue. To this end, test conditions according to EUWA Standards were simulated and obeyed, relevant to fatigue. Simulation results were interesting, according to industry experts involved in the project and manufacture of the product in question, and have provided important elements for the decision making regarding improvements that could be made on the product project before its execution

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The automobile industry has a growing importance in the Brazilian economic environment. The industry moves a huge chain that encompasses manufacturers, suppliers of raw materials, auto parts dealers, gas stations, insurance companies, repair shops, tire stores, media companies, advertising agencies, among others. Because of this importance in the current economic environment in Brazil, the federal government, through Law No. 12715 of 17 December 2012 established a Program for the Promotion of Innovation and Densification in the Productive Chain of Motor Vehicles called INOVAR-AUTO in order to support technological development, innovation, safety, environmental protection, energy efficiency and quality of cars, trucks, buses and auto parts. The specific purpose of this study, a simulation for discussion of the viability of the program implementation using the Monte Carlo Simulation combined with the Cash-Flow-at-Risk was performed. To this end, an exploratory and documentary literature on the subject was held as well as a case study in a automobile company of Japanese origin

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This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

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The automobile industry shows relevance inside the Brazilian industrial scenario since it contributes with the development of a significant chain of supply, distributors, workshops, publicity agencies and insurance companies in the internal market, aside from being one of the five biggest worldwide market. Thereby, the federal government decreed in Dec, 17th 2012 by Law nº 12.715 the Inovar-Auto Program. As the Adjusted Present Value (APV) is highly recommended, although not yet widespread to public politics of tax reduction, this work intends to apply the APV method on the cash flow analysis of an automobile sector's company, which has recently installed in national territory and wants to rely with governmental incentives proposed by Inovar-Auto Program. The developed work evaluates the company's current cash flow stochastically from mathematical modeling of variables such as price, demand and interest rate through probability distributions with the assist of Crystal Ball software, a Microsoft Excel Add-in, generating different scenarios from Monte Carlo Simulation. As results probabilities situations have been evaluated until the end of the Inovar-Auto's conducted period, in 2017. Beside APV others indicator such as Internal Rate of Return (IRR) and payback period were estimated for the investment project. For APV a sampling distribution with only 0.057% of risk, IRR of 29% were obtained and estimated project payback period was 4.13 years