Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment
Due to changes in individual demand, manufacturing processes have become more complex and dynamic. To cope with respective fluctuations as well as machine breakdowns, capacity adjustment is one of the major effective measures. Instead of labor-oriented methods, we propose a machinery-based approach...
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doaj-841b3eeefff64447942f712649c4b64e2020-11-25T00:25:37ZengBVLLogistics Research1865-035X1865-03682019-02-0112110.23773/2019_3Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity AdjustmentQiang Zhang0Michael Freitag1Jürgen Pannek2University of Bremen, International Graduate School for Dynamics in Logistics, Faculty of Production Engineering, Bremen, GermanyBIBA – Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, University of Bremen, Faculty of Production Engineering, Bremen, GermanyBIBA – Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, University of Bremen, Research Cluster LogDynamics and Faculty of Production Engineering, Bremen, GermanyDue to changes in individual demand, manufacturing processes have become more complex and dynamic. To cope with respective fluctuations as well as machine breakdowns, capacity adjustment is one of the major effective measures. Instead of labor-oriented methods, we propose a machinery-based approach utilizing the new type of reconfigurable machine tools for adjusting capacities within a job shop system. To economically maintain desired work in process levels for all workstations, we impose a model predictive control scheme. For this method we show stability of the closed-loop for any feasible initial state of the job shop system using a terminal condition argument. For a practical application, this reduces the computation of a suitable prediction horizon to controllability of the initial state. To illustrate the effectiveness and plug-and-play availability of the proposed method, we analyze a numerical simulation of a four workstation job shop system and compare it to a state-of-the-art method.https://www.bvl.de/lore/all-volumes--issues/volume-12/issue-1/stability-of-predictive-control-in-job-shop-system-with-reconfigurable-machine-tools-for-capacity-adjustmentReconfigurable machine toolCapacity adjustmentModel predictive controlStability |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qiang Zhang Michael Freitag Jürgen Pannek |
spellingShingle |
Qiang Zhang Michael Freitag Jürgen Pannek Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment Logistics Research Reconfigurable machine tool Capacity adjustment Model predictive control Stability |
author_facet |
Qiang Zhang Michael Freitag Jürgen Pannek |
author_sort |
Qiang Zhang |
title |
Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment |
title_short |
Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment |
title_full |
Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment |
title_fullStr |
Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment |
title_full_unstemmed |
Stability of Predictive Control in Job Shop System with Reconfigurable Machine Tools for Capacity Adjustment |
title_sort |
stability of predictive control in job shop system with reconfigurable machine tools for capacity adjustment |
publisher |
BVL |
series |
Logistics Research |
issn |
1865-035X 1865-0368 |
publishDate |
2019-02-01 |
description |
Due to changes in individual demand, manufacturing processes have become more complex and dynamic. To cope with respective fluctuations as well as machine breakdowns, capacity adjustment is one of the major effective measures. Instead of labor-oriented methods, we propose a machinery-based approach utilizing the new type of reconfigurable machine tools for adjusting capacities within a job shop system. To economically maintain desired work in process levels for all workstations, we impose a model predictive control scheme. For this method we show stability of the closed-loop for any feasible initial state of the job shop system using a terminal condition argument. For a practical application, this reduces the computation of a suitable prediction horizon to controllability of the initial state. To illustrate the effectiveness and plug-and-play availability of the proposed method, we analyze a numerical simulation of a four workstation job shop system and compare it to a state-of-the-art method. |
topic |
Reconfigurable machine tool Capacity adjustment Model predictive control Stability |
url |
https://www.bvl.de/lore/all-volumes--issues/volume-12/issue-1/stability-of-predictive-control-in-job-shop-system-with-reconfigurable-machine-tools-for-capacity-adjustment |
work_keys_str_mv |
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1725347930585432064 |