The forecasting of capacity and its utilization is particularly relevant in the aerospace industry because of long product delivery lead-times and the forward-pricing system. The objective of this paper is to develop a method for forecasting both the industry's capacity and its capacity utilization so that decision makers who must rely on this information may have policy guidance. The result shows that the aerospace industry's capacity expansion rate is closely tied to its present and recent past state of capacity utilization, and to anticipated changes in output. Output, in turn, can be predicted by using Five Year Defense Plans data and information on the cyclical nature of commercial business. Based on these findings, we were able to build an accurate model for forecasting aerospace industry capacity utilization.
KEY WORDS Capacity modes Aerospace Budgeting Regression
Box-Jenkins
Manufacturing capacity and its utilization have received considerable attention in recent literature. These studies, however, tend to focus on explaining why the firm invests in production capacity. To those responsibile for public policy or managerial decisions, predicting changes in capacity and capacity utilization is far more important. Unfortunately, no attempt has been made by researchers to examine this issue. This paper examines the capacity expansion behaviour of the U.S. aerospace industry and its relationship to product demand. The forecasting of capacity and its utilization is particularly relevant to the aerospace industry because of long product delivery lead-times and the forwardpricing system. The objective of this paper is to develop a method of forecasting both the aerospace industry's capacity and its utilization rate for those who must rely on this information for decision-making.
The paper is organized as follows. Section 1 discusses the importance of information about the aerospace industry's capacity utilization rate. Section 2 presents a historical picture of the industry's capacity and its utilization rate. Section 3 examines the industry's capacity expansion behaviour. Section 4 presents a method for forecasting industry demand by using publicly