I2 Technologies Us, Inc.

I2 Technologies, Inc.

Yikang Li

In one embodiment of the present invention, a method for forecasting a Last Time Buy quantity for a service part using a low-pass filter approach is provided. The method includes accessing input data including: (1) a service lifespan beginning at the end of mass production of a product associated with the service part; (2) data reflecting past accumulated production of the associated product for at least a first period beginning at the end of mass production of the associated product; and (3) an order data series reflecting past quantities of the service part ordered in each of a succession of periods beginning with a second period that immediately follows the first period and ending with a current period. A low-pass filter is applied to at least a portion of the order data series to extract low frequency components representing a smoothed order data series. A local maximum is sought within the smoothed order data series subject to predetermined conditions. If a local maximum is found within the smoothed order data series, exponential forecasting is performed according to the smoothed order data series to generate an estimated Last Time Buy quantity for the service part over all remaining periods of the service lifespan following the current period. The estimated Last Time Buy quantity for the service part is made available for use in connection with one or more business analyses.

Forecasting a last time buy quantity for a service part using a low-pass filter approach

Within each iteration of an iterative process: (1) a low-pass filter is applied to an actual sales volumes series to extract low frequency components representing a base sales volume series for the iteration; and (2) a locally optimal base sales volume series is determined. A globally optimal base sales volume series is selected from among the locally optimal base sales volume series, comprising an estimated base sales volume for each time period. One or more of the estimated base sales volumes is made available for use in connection with at least one business analysis.

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Bridgewater, NJ, United States of America

Yikang Li