Predicting final purchase quantity for customer service parts using low pass filter element involves seeking local maximum in smoothed order data series, carrying out exponential prediction if present

摘要

Input data containing a customer service lifetime, data reflecting previous production and order data is accessed using a low pass filter on a section of the order data to derive low frequency components representing a smoothed order data series, seeking a local maximum and carrying out an exponential prediction if there is a local maximum to produce a final quantity of parts over the remaining periods. The method involves accessing input data containing a customer service lifetime starting at the end of mass production of an associated product, data reflecting the previously accumulated production of the product and a series of order data reflecting previous amounts of the customer service parts ordered during a certain period, using a low pass filter on at least one section of the order data to derive low frequency components representing a smoothed order data series, seeking a local maximum and carrying out an exponential prediction if there is a local maximum to produce a final quantity of parts over the remaining periods. Independent claims are also included for the following: (a) an arrangement for prediction of final purchase quantity for customer service parts (b) software for prediction of final purchase quantity for customer service parts.