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Various techniques are presented and evaluated for their ability to forecast equipment sales in the agricultural industry. The forecasting methods discussed include trend approximation, time series moving averages, exponential smoothing, Delphi Method, buyer intentions and econometric models. A model that predicts future sales for industrial tractors was presented including a 1978 forecast. Leading indicators for Industrial Tractor Sales were GNP construction dollars, index of prices of construction machinery and new housing starts. Also, a farm tractor sales model and the resulting difficulty in finding leading indicators were discussed. Statistical methods required for econometric forecasting and model validity testing are given.

The new design for a diesel engine chassis mount bracket was fitted with strain gages and placed in a test vehicle instrumented with an on-board data acquisition system to find stress levels under actual service conditions. All experimental stresses were smaller than endurance limit of the part, so the bracket was predicted to have infinite life. In addition, a finite element model of the chassis mount bracket was optimized. The solution suggested removal of three portions of the bracket, reducing the weight by 13.49% and saving some manufacturing costs.

Forecasting the sales of combines and tractors in today's ever changing and volatile marketplace is a difficult task; moreover, it is becoming increasingly important to manufacturers whose goal is to maximize profits with just-in-time policies. Farmers are independent business managers who react to a variety of factors and a unique set of circumstances. Predicting how these individuals will respond to changes in the economic atmosphere is an even more perplexing task than forecasting their business environment. Individually, some farmers may choose to postpone machinery purchases when their cashflow is reduced. Collectively, farmers react to certain factors in a more cohesive manner. For example, if farm commodity prices rise and interest rates are relaxed the agricultural sector will undoubtably increase machinery purchases. Therefore, Federal government policies and also fiscal and monetary policies affect both the farmer's income and the associated agricultural industries sales.

A rule-based expert system for forecasting combine sales in U.S.A. was developed and coupled with an econometric simulation model. The expert rules were built based on domain human experts' knowledges and experiences. The econometric forecasting model was developed based on economic data, statistics and analysis. This combination of simulation and expert system should increase the reliability of a combine sales forecast.