Irrespective of the type of items manufactured by an industry, environment is now
becoming progressively more and more competitive than the past few decades. To sustain in this
severe competition, companies have no choice but to manage their operations optimally and in this
respect the importance of more accurate demand prediction cannot be exaggerated. This research
presents a forecasting approach tailoring the multiplicative Holt-Winters method with growth
adjustment through incorporation of fuzzy logic. The growth parameter of the time series values is
adjusted with the conventional Holt-Winters method and tested for predicting the real-life demand
of transformer tank experienced by a local company. The result obtained by applying the new
approach shows a significant improvement in the accuracy of the forecasted demand and sheds light
on further enhancement of the proposed method by optimizing other time series parameters through
fuzzy logic application for possible application in prediction of demand having trend, seasonal and
cyclical changes
