Croston (1972) [2] presented an idea and method to separate ordinary exponential smoothing in two parts;In the time between demand, or withdrawals, and demand size. The idea with the modification in Levén and Segerstedt (2004) [3] is that time between demand and demand size is not independent. But this modification has shown poor results. Therefore Wallström and Segerstedt (2010) [8] suggest another modification, "forward coverage".By applying moving average of past two months demands to "forward Coverage" (Wallström and Segerstedt (2010)) [8] method, shows that the new one produces better forecast, if the time between demands and demanded quantity are not independent. The different techniques are compared Mean Squared Error (MSE).
Every day, Tamilnadu Newsprint and Papers Ltd managers must make decisions about Production delivery without knowing what will happen in the future. Forecasts enable them to anticipate the future and plan, many forecasting methods are available to Tamilnadu Newsprint and Papers Ltd managers for planning, to estimate future demand or any other issues at hand. However, for any type of forecast to bring about later success, it must follow a step-by-step process comprising five major steps: 1) goal of the forecast and the identification of resources for conducting it; 2) time horizon; 3) selection of a forecasting technique; 4) conducting and completing the forecast; and 5) monitoring the accuracy of the forecast. Accordingly Linear Regression method is a widely used to predict this kind of demand. In this paper, we forecast the Production of Papers in TamilNadu Newsprint and Papers Ltd from the past 15 years of Production using the Linear Regression method
The overall efficiency of the supply chain depends not only the improvement of the infrastructure, but also the comprehensive information exchanges and seamless coordination between different units of the entire supply chain. Among these units the forecasting one plays an important role for the effectiveness of a supply chain. In this paper based on the business practice of a supply chain management company, the role of the forecasting unit is discussed and some potential prediction models for the application of this specific application are investigated. Furthermore, the computational experiments are conducted to choose the most suitable prediction model for the practice.
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