Inventory management is important to the food-processing-and-distribution industry because of the large amount
of products typically stored. In this study, a prediction model composed with factor analysis tool and a prediction
tool is proposed. Through AHP method, the factors could be found through surveying experts. The survey results
could be applied to sequential-pattern analysis to predict the forthcoming materials in an inventory. This study
surveyed 15 experts and found that the quantity of stored foods, the recency of input/output foods, and the
input/output frequency of the same foods are three major concerns of a food-processing-and-distribution company.
This study summarized the above mentioned factors as QFR (quantity, frequency, and recency), and weighted each
factor to calculate the importance of each material in inventory. Through this proposed prediction model, the best
accuracy of inventory prediction could be 66.3%. It is useful for a company to adopt as the inventory prediction.