Control of deadlock and blocking for production systems with unreliable workstations

Lawley, Mark

doi:10.1080/00207540210155792

Cited by 31 publications

(21 citation statements)

References 24 publications

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“…Also, the policies presented here provide more allocation flexibility than the approaches presented in both [30] and [31].…”

Section: Robust Supervisory Control For Production Systems With Multimentioning

confidence: 89%

“…(Reference [30] contrasts the approach presented here with that of [24], [25], [27], and [33].) In [30] and [31], we develop controllers that allocate resources so that the failure of a single resource does not propagate to stall larger portions of the system. Our concern is not with repairing the failed resource.…”

Section: Robust Supervisory Control For Production Systems With Multimentioning

confidence: 98%

“…While the work presented in [30] and [31] develops robust supervisors for systems with a single unreliable resource, the work presented here develops supervisors for systems with multiple unreliable resources. Also, the policies presented here provide more allocation flexibility than the approaches presented in both [30] and [31].…”

Section: Robust Supervisory Control For Production Systems With Multimentioning

confidence: 98%

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Robust supervisory control for Production Systems with multiple resource failures

Chew

Lawley

2006

IEEE Trans. Automat. Sci. Eng.

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Supervisory control for deadlock-free resource allocation has been an active area of manufacturing systems research. To date, most work assumes that allocated resources do not fail. Little research has addressed allocating resources that may fail. In our previous work, we assumed a single unreliable resource and developed supervisory controllers to ensure robust deadlock-free operation in the event of resource failure. In this paper, we assume that several unreliable resources may fail simultaneously. In this case, a controller must guarantee that a set of resource failures does not propagate through blocking to stall other portions of the system. That is, the controller must ensure that every part type not requiring any of the failed resources should continue to produce smoothly without disruption. To do this, the controller must constrain the system to states that serve as feasible initial states for: 1) a reduced system when resource failures occur and 2) an upgraded system when failed resources are repaired. We develop the properties that such a controller must possess and then develop supervisory controllers that satisfy these properties.Note to Practitioners-For the past decade or so, researchers have begun to actively address the issue of ensuring smooth and continuous operation for flexibly automated manufacturing systems. This research effort has been motivated by the many failed attempts to implement flexible automation throughout the 1980s. During this time, much has been learned about modeling the control functions of a flexible, automated system. In fact, ladder logic control code can now be generated automatically from mathematical models, such as Petri nets, which compactly capture the required operating system logic. Because the code is based on a formal model with well-established properties, it is guaranteed to ensure proper operation without significant startup troubleshooting. One area that has not been investigated is controlling these systems when machines or tools "fail." The question is not how to fix what has failed, but rather how to control the system so that if something does fail, the system can continue producing items that do not require the failed elements. This is essential work since automated manufacturing systems consist of thousands of components, any of which are subject to failure. If failures in the system are not handled gracefully, it becomes difficult to keep the automated system running, in which case, system production does not meet expectations. In our previous work, we investigated ensuring smooth operation for systems with a single unreliable resource. We developed supervisory controllers to guarantee this requirement for these systems. In this paper, we extend the previous results to a more general class of systems where there are multiple unreliable resources. We establish a set of desired properties that the supervisory controller must possess in order to guarantee robust operation for these systems, and then develop a number of controllers that satisfy these pro...

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“…Also, the policies presented here provide more allocation flexibility than the approaches presented in both [30] and [31].…”

Section: Robust Supervisory Control For Production Systems With Multimentioning

confidence: 89%

Section: Robust Supervisory Control For Production Systems With Multimentioning

confidence: 98%

Section: Robust Supervisory Control For Production Systems With Multimentioning

confidence: 98%

See 1 more Smart Citation

Robust supervisory control for Production Systems with multiple resource failures

Chew

Lawley

2006

IEEE Trans. Automat. Sci. Eng.

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“…Therefore, it is necessary to develop an effective scheduling to optimise the performance of the FMS while avoiding deadlocks. A plenty of deadlock control policies for FMSs have been proposed (Abdallah and Elmaraghy 1998;Chu and Xie 1997;Ezpeleta, Colom, and Martinez 1995;Fanti, Maione, and Turchiano 2001;Fanti and Zhou 2004;Huang et al 2001;Lawley 2002;Li and Zhou 2004;Liu et al Forthcoming;Piroddi, Cordone, and Fumagalli 2008;Reveliotis and Ferreira 1996;Uzam and Zhou 2006;Xing, Hu, and Chen 1996;Xing et al 2009;Xing et al 2011). Ezpeleta, Colom, and Martinez (1995) proposed a class of Petri net (PN) called system of simple sequential processes with resources (S 3 PR).…”

Section: Introductionmentioning

confidence: 99%

Deadlock-free genetic scheduling for flexible manufacturing systems using Petri nets and deadlock controllers

Han

Xing

Chen

et al. 2013

International Journal of Production Research

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In this paper, a new deadlock-free scheduling method based on genetic algorithm and Petri net models of flexible manufacturing systems is proposed. The optimisation criterion is to minimise the makespan. In the proposed genetic scheduling algorithm, a candidate schedule is represented by a chromosome that consists of two sections: route selection and operation sequence. With the support of a deadlock controller, a repairing algorithm is proposed to check the feasibility of each chromosome and fix infeasible chromosomes to feasible ones. A feasible chromosome can be easily decoded to a deadlock-free schedule, which is a sequence of transitions without deadlocks. Different kinds of crossover and mutation operations are performed on two sections of the chromosome, respectively, to improve the performance of the presented algorithm. Computational results show that the proposed algorithm can get better schedules. Furthermore, the proposed scheduling method provides a new approach to evaluate the performance of different deadlock controllers.

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“…To model an FMS and ensure that deadlocks will never occur, Petri nets (PNs), one of the promising modelling tools, have been widely used to deal with deadlock problems in FMSs (Gligor and Shattuck 1980, Lawley and Mittenthal 1999, Lawley 2000, 2002, Tricas et al 2000, Reveliotis 2001, Iordache et al 2002, Chao 2006, Piroddi et al 2008. As a particular Petri net structural object, siphons play an important role in solving deadlock problems in Petri nets, resulting in many deadlock prevention policies (DPP) using siphon control (Ezpeleta et al 1995, Li and Zhou 2004, Huang et al 2006, Uzam et al 2007, Piroddi et al 2009, Li and Li 2010.…”

Section: Introductionmentioning

confidence: 99%

Solving siphons with the minimal cardinality in Petri nets and its applications to deadlock control

Li¹,

Li²

2012

International Journal of Production Research

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Siphons can be used to characterise deadlock states and solve deadlock problems in Petri nets that model flexible manufacturing systems. By modifying the objective function and adding new constraints to the mixedinteger programming (MIP) method proposed by Park and Reveliotis, this paper presents a revised MIP (RMIP) to directly solve siphons, called smart siphons, with the minimal cardinality as well as the minimal number of resource places. Accordingly, an iterative siphon-based control (ISC) method adds a proper control place (CP) to make each smart siphon max-controlled until the controlled system is live. Since any siphon that has more resource places can be composed of those containing less resource places, a small number of CPs are required during the iterative control process due to the solved smart siphons containing the minimal number of resource places. Compared with the existing methods in the literature, the proposed ISC method using the RMIP avoids computing a maximal deadly marked siphon from which a minimal siphon is then derived, adds a small number of proper CPs, and leads to a liveness-enforcing supervisor with a simple structure. Finally, a case study demonstrates the effectiveness of the proposed ISC method.

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Control of deadlock and blocking for production systems with unreliable workstations

Cited by 31 publications

References 24 publications

Robust supervisory control for Production Systems with multiple resource failures

Robust supervisory control for Production Systems with multiple resource failures

Deadlock-free genetic scheduling for flexible manufacturing systems using Petri nets and deadlock controllers

Solving siphons with the minimal cardinality in Petri nets and its applications to deadlock control

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