Stochastic Flow Model using Kalman Filters for parameter estimation ⋆
نویسندگان
چکیده
Attaining high quality from manufacturing systems requires utilizing appropriate system-level quality performance modeling and analysis tools. This paper describes the application of the stochastic-flow-modeling (SFM) approach to represent the quality output behavior of a manufacturing system. To do this, a basic one-product type SFM is extended to that of a multiple-product manufacturing system. This work also provides a novel addition to the SFM approach through the use of a Kalman filter to estimate quality parameters. After a presentation of the reference manufacturing system, results are given for different examples and the effectiveness of the SFM model is examined in terms of accuracy and convergence.
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