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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Bibliographic Details
Main Authors: Qiang Zhang, Michael Freitag, Jürgen Pannek
Format: Article
Language:English
Published: BVL 2019-02-01
Series:Logistics Research
Subjects:
Online Access: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
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spelling 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
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