Adaptive time dynamic model for production volume prediction
نویسنده
چکیده
Data from a continuously operating high volume lathe was collected over a period of a number of months. This machine would periodically fail and unplanned maintenance was often necessary. Failures were due to a myriad of causes. At the beginning of each month, management was required to estimate production output for the month. This paper shows how this goal might be facilitated via a sequence of Bayesian models analysing previous data. The validity of the procedure is justi® ed by an empirical study.
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تاریخ انتشار 2000