Kalman filter based production control of a failure-prone single-machine single-product manufacturing system with imprecise demand and inventory information

•Control policy that adapts to imprecise inventory record and variable demand rate is proposed.•Kalman filter is used to obtain inventory and demand rate estimates.•Prediction module provides demand forecast to be used in cost function computation.•Estimation and forecasting results are incorporated...

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Vydáno v:Journal of manufacturing systems Ročník 56; s. 558 - 572
Hlavní autoři: Polotski, V., Kenne, J.-P., Gharbi, A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.07.2020
Témata:
Forecasting
Kalman filter
Manufacturing
State estimation
Stochastic processes
Uncertainty
Uncertainty
Manufacturing
Forecasting
State estimation
Stochastic processes
Kalman filter
ISSN:0278-6125
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Shrnutí:•Control policy that adapts to imprecise inventory record and variable demand rate is proposed.•Kalman filter is used to obtain inventory and demand rate estimates.•Prediction module provides demand forecast to be used in cost function computation.•Estimation and forecasting results are incorporated into feedback production control loop. An adaptive production control structure for failure-prone manufacturing systems under inventory and demand uncertainty is proposed. It contains estimation and forecasting modules incorporated into a control loop. The customer demand is unknown and its rate is composed of ramp-type, seasonal and random components. Information available to decision maker consists of imprecise inventory records, and the Kalman filter technique is used for estimating the inventory level and demand rate online from noisy inventory measurements. Estimates obtained are shown to converge to the actual values in stochastic sense. They are subsequently used for demand component forecasting, once the estimation errors become sufficiently small. A forecasting algorithm allows estimating ramp-type and seasonal demand components, together with their potential errors. Obtained estimates are incorporated into production control procedures, recently developed for manufacturing systems under variable and uncertain demand. Optimality conditions in the form of Hamilton-Jacobi-Bellman equations are obtained. A constructive numerical method for computing sub-optimal production policies is proposed and validated through numerical simulations.
ISSN:0278-6125
DOI:10.1016/j.jmsy.2020.07.010