Previsão de demanda: uma aplicação dos modelos Box-Jenkins na área de assistência técnica de computadores pessoais

Werner, Liane; Ribeiro, José Luís Duarte

doi:10.1590/s0104-530x2003000100005

Cited by 46 publications

(41 citation statements)

References 3 publications

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“…The residual are checked whether they meet the assumptions required to be used by control charts through diagnostic tests (Box et al 1994;Werner and Ribeiro 2003) S4…”

Section: S3mentioning

confidence: 99%

Control chart based on residues: Is a good methodology to detect outliers?

et al. 2019

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The purpose of this article is to evaluate the application of forecasting models along with the use of residual control charts to assess production processes whose samples have autocorrelation characteristics. The main objective is to determine the efficiency of control charts for individual observations (CCIO) and exponentially weighted moving average (EWMA) charts when they are applied to residuals of models of AR(1) or MA(1) to detect outlier in autocorrelated processes. Considering autocorrelation strength and sign in the data series and the outlier range, the series were simulated accomplishing 640,000 sets. The series were contaminated by anomalous observations at 100th position, an AR(1) or MA(1) model were fitted, and the residuals were evaluated by CCIO and EWMA control charts; the points correctly detected as an autocorrelation were recorded. For the parameters investigated (autocorrelation and outlier range), a detection rate was generated in each chart, and nonparametric comparison tests were applied. The result of the tests showed the superiority (p < 0.05) of the CCIO chart for both models. The study of the influence of the sign and magnitude of the autocorrelation parameter showed no significant (p > 0.05) for either AR(1) or MA(1) charts and models. In this context, control charts for individual observations (CCIO) were confirmed to effectively detect outliers through residuals in industrial autocorrelated processes originated in first-order AR and MA models.

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“…The residual are checked whether they meet the assumptions required to be used by control charts through diagnostic tests (Box et al 1994;Werner and Ribeiro 2003) S4…”

Section: S3mentioning

confidence: 99%

Control chart based on residues: Is a good methodology to detect outliers?

et al. 2019

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“…[52] was used because this mathematical model allows us to describe the behavior of the stationary and non-stationary series and, based on this behavior, to make future forecasts. This gives versatility to a variety of situations [53,54], with the statistical model criteria selected by the Bayesian Information Criterion (BIC), successfully employed for model selection and hypothesis testing procedures [55].…”

Section: Risk Analysismentioning

confidence: 99%

Investment Uncertainty Analysis in Eucalyptus Bole Biomass Production in Brazil

Simões

Dinardi

Silva

2018

Forests

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Forestry investment projects for the biomass production of the eucalyptus bole can be characterized by uncertain environments, which result in economic risk to the forest producer, however that can be measured by applying probabilistic techniques. This was our motivation and justification for analyzing the economic-financial viability of different silvicultural practices for eucalyptus bole biomass production under conditions of uncertainties, running Monte Carlo method for risk management. The experiment was carried out in the state of São Paulo, Brazil, using 5 treatments with spacings of 3 m × 2 m; 3 m × 1 m; 1.5 m × 2 m; 3 m × 0.5 m; and 1.5 m × 1.0 m, i.e., different spacings between planting lines and plants. These treatments were characterized as investment projects. To develop stochastic models, we relied on technical-economic deterministic variables. We evaluated the investment projects based on the cash flows under conditions of uncertainty, discounted at the attractiveness rate calculated by capital asset pricing model. With the results of these economic flows, the net present value, the modified internal rate of return and the profitability index values were estimated, commonly used in the analysis of investments in projects. The results showed that based on economic metrics, the three-year rotation cycle for forest stands for biomass production of the main bole of eucalyptus, with a spacing of three meters between rows and two meters between plants, had an 83% probability of economic success. The sensitivity analysis showed that the bole biomass of eucalyptus is the most important variable for determining the economic-financial feasibility of the investment project.

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“…Quantitative methods use historical data to forecast demand in future periods, and the qualitative use (Pellegrini et Fogliatto 2000;Werner et Ribeiro, 2003).…”

Section: Demand Previsionmentioning

confidence: 99%

Sales Performance Management: A Strategic Initiative to the Growth of Micro and Small Businesses

Galvão

Cotrim

Leal

et al. 2017

BJO&PM

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Micro and small companies are lighting up in numbers and economic importance in the Brazilian market. In the sector of services, they already account for 27% of GDP. Given this importance, the purpose of this paper is to analyze how the integration of tools such as Planning Programming and Control of Production tools, together with the Quality Engineering tools such as performance management through indicators, can help to achieve the objectives of the organizations, especially small business, in the sales area. Boosting thus, strategically, these organizations to achieve and exceed their sales goals, become increasingly competitive, and growing in size and quality of service. The results obtained through the case study were satisfactory in 2014, where the signs of a crisis were already indicated in the country, this small business increased its sales by 12% compared to the year 2013.Keywords: Performance Management; Quality Tools; Sales Strategy; Goals. ABSTRACTABEPRO

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Previsão de demanda: uma aplicação dos modelos Box-Jenkins na área de assistência técnica de computadores pessoais

Abstract: Resumo A previsão de demanda é uma atividade importante para auxiliar na determinação dos recursos

Cited by 46 publications

References 3 publications

Control chart based on residues: Is a good methodology to detect outliers?

Control chart based on residues: Is a good methodology to detect outliers?

Investment Uncertainty Analysis in Eucalyptus Bole Biomass Production in Brazil

Sales Performance Management: A Strategic Initiative to the Growth of Micro and Small Businesses

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