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

  • US 7,251,614 B1
  • Filed: 05/02/2002
  • Issued: 07/31/2007
  • Est. Priority Date: 05/02/2002
  • Status: Active Grant
First Claim
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1. A method for forecasting a Last Time Buy quantity for a service part using a low-pass filter approach, comprising:

  • accessing input data comprising;

    a service lifespan beginning at the end of mass production of a product associated with the service part;

    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

    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;

    applying a low-pass filter to at least a portion of the order data series to extract low frequency components representing a smoothed order data series;

    performing exponential forecasting according to the smoothed order data series for a local maximum in the smoothed order data series;

    generating an estimated Last Time Buy quantity for the service part over all remaining periods of the service lifespan following the current period, wherein the Last Time Buy quantity is calculated using the following equation;

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