Estimation of demand and supply of pulpwood by artificial neural network: a case study in Tamil Nadu

The annual demand of paper and paperboard, including newsprint is at 11.15 Million Tones (MT) in India. The per-capita consumption is nearly 10.5 kg. The growth in the number of paper mills was from 17 units in 1950 to 759 units in 2010 with the production of 10.11 MT per annum. In Tamil Nadu, Tamil Nadu News prints and Papers Limited (TNPL) and Seshasayee Paper and Board Limited (SPB) are the major pulpwood based paper industries, which require 0.8 to 0.9 MT of pulpwood per year, whereas the availability of pulpwood is nearly 0.6 to 0.65 MT per year. This short supply will affect their performance in the market. Hence, this paper is to assess the factual demand and supply gap of industrial raw materials with different forecasting methods viz., trend analysis, moving average, single exponential smoothing model and Artificial Neural Network (ANN). Based on forecast accuracy, ANN is observed as a reliable method which measures that the demand-supply gap of raw materials will be 0.01 MT and 0.24 MT in 2015 and 2020 respectively. In order to bridge the gap, industries must additionally produce raw materials by promoting resourceful captive plantation and the farm forestry area with profitable business model.