Modeling of Production of Injected Plastic Product Using Forecasting, Aggregate Planning and Linear Programming Approach

The project is on production planning of modeling of automotive plastic parts. The
focus is on forecasting, aggregate planning and linear programming. The sales data
for year 2003 was used as the basis of the planning. Causal forecasting using
regression, 3-period moving average, 5-period moving average and also exponential
smoothing with a = 0.2 and a = 0.5 were used for forecasting models. Results from
the forecasting were used to develop for aggregate planning for year 2004. Excel
software were used extensively for forecasting, aggregate planning and linear
programming. Results from analysis indicate that 3-period moving average provide
the best mean absolute deviation (MAD) for the forecasting. While for the case of
aggregate planning, constant workforce planning with backorder provides the
rrunimum cost.