Multiple Unreliable Resources Research Articles

Maximally Permissive Robustness Analysis of Automated Manufacturing Systems With Multiple Unreliable Resources

For real-world automated manufacturing systems (AMSs), the failures of multiple unreliable resources are very common. Maximal permissiveness is a key aspect for evaluating the performance of robust control strategies of failure-prone AMSs. However, there exist fewer works in the existing literature that can achieve maximally permissive robustness analysis. This may impede the applicability of existing robust control strategies in realistic AMSs. This article tackles the issue in the paradigm of Petri nets (PNs). We present an innovative mechanism to formalize unreliable resource failures by preventing all ingoing transitions of unreliable resource places from firing. Both reachability graph-based and integer linear programming-based methods are proposed to analyze the robustness of AMSs with either single or multiple unreliable resources. Several examples are proposed to illustrate the approach.

Robust deadlock control in automated manufacturing systems with unreliable resources based on an algebraic way

In automated manufacturing systems (AMSs), because of unpredictable failures, resources can lose functions such that the deadlock control methods, in existence, are invalidated. In this paper, a robust deadlock control approach is proposed for AMSs with multiple unreliable resources. The considered AMSs modelled by Petri nets (PNs) allow to acquire different types of resources at each processing stage. In order to visualise the fact that resource failures occur in AMSs, recovery subnets are designed for the modelling AMSs to depict the failures and recoveries of resources. Based on a siphon detection method performed by a set of integer linear programming formulations, a control specification is proposed. Control places (monitors) with their control variables are designed for the detected unmarked siphons at a marking to guarantee that they are always marked even if some unreliable resources break down. Iteratively, all unmarked siphons are detected and controlled. Therefore, a robust deadlock supervisor is synthesised to ensure the controlled system's liveness no matter there exist resource failures or not. The theoretical analyses and proof are given to verify the correctness of the proposed method. Finally, the comparative studies are presented to expound the proposed method's effectiveness and efficiency.

Petri Net-Based Robust Supervisory Control of Automated Manufacturing Systems With Multiple Unreliable Resources

In recent years, there has been a growing concern for robust supervisory control policies that can handle both deadlock and blockage propagation in automated manufacturing systems in the event of resource failures. This work proposes a novel robust supervisory control policy for automated manufacturing systems with multiple unreliable resources without using central buffers. The policy permits legal states as many as possible and ensures that parts not requiring unreliable resources can be automatically processed without human intervention if one or multiple unreliable resources fail. It is based on the modified neighborhood policy, namely single route neighborhood, which handles the allocation of failure-prone resources in a system. To guarantee deadlock-free operations in the remaining parts of the system, monitors are designed for emptiable strictly minimal siphons. Through examples, the applicability of the proposed policy is demonstrated.

Robust Deadlock Detection and Control of Automated Manufacturing Systems With Multiple Unreliable Resources Using Petri Nets

In recent years, the research on robust deadlock control has become increasingly popular in automated manufacturing systems (AMSs) because resource failures may lead any system to stagnation, e.g., deadlock. In this article, we study robust supervisory control issues in AMSs with multiple unreliable resources. Petri nets are used to model the considered AMSs that allow multi-quantity and multi-type of resource acquisitions. A set of integer linear programming formulations are introduced to detect a class of deadlocks that have the maximal number of dead transitions. By analysis, a deadlock is characterized by a saturated circuit, which only consists of a set of unmarked resources and a set of critical transitions. Based on the circuit, a linear marking constraint is developed to prevent such circuits from being saturated. A control place (monitor) with its control variable is thus designed for the constraint to prevent the deadlock from appearing even if some resource failures occur. Therefore, we can synthesize a robust deadlock supervisor, which can guarantee that the controlled system can implement the continual operations even if some unreliable resources fail. Finally, the theoretical analysis and comparative study are provided to elucidate the effectiveness and efficiency of our proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In practice, resource failures in automated manufacturing systems (AMSs) are common. Deadlock prevention control in AMSs allowing resource failures has gained more and more attention from researchers and practitioners. Most prior research is based on the enumeration of either siphons or perfect resource transition circuits whose number exponentially increases with the system scale. This means that the synthesized supervisor has a much complex structure. In this article, based on a special kind of circuits at a deadlock marking detected by using a set of mathematical formulations, we develop an effective and efficient method for AMSs with multiple unreliable resources to iteratively control deadlocks such that the controlled system can continue to operate smoothly even if some unreliable resources fail. The computational and comparative results show that our proposed approach can acquire more permissive states with a simpler supervisor.

Robust deadlock avoidance policy for automated manufacturing system with multiple unreliable resources

This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To reach this goal, we propose a new modified Banker’s algorithm ( MBA ) to ensure that all resources required by these jobs can be freed. Moreover, a Petri net based deadlock avoidance policy ( DAP ) is introduced to ensure that all jobs remaining in the system after executing the new MBA can complete their processing smoothly when their required unreliable resources are operational. The new MBA together with the DAP forms a new DAP that is robust to the failures of unreliable resources. Owing to the high permissiveness of the new MBA and the optimality of the DAP, it is tested to be more permissive than state-of-the-art control policies.

Elementary Siphon-Based Robust Control for Automated Manufacturing Systems With Multiple Unreliable Resources

Resources in a real-world automated manufacturing system may be unreliable, thus paralyzing many existing deadlock control strategies. This paper defines robust legal markings and proposes a two-step robust deadlock control policy for systems of the simple sequential process with resources based on elementary siphons. The first step, called elementary siphons control, derives a live controlled system without considering resource failures. The second step deals with failure-induced deadlocks control issues. With resource failures taken into account, recovery subnets modeling resource failures and recoveries are added to the first-step-derived system, which may cause the occurrence of failure-induced deadlocks, resulting in an unreliable controlled system. In order to make the system reliable, the definition that a resource failure is observed by a monitor is developed. A scenario is exposed that a resource failure does not need to be observed while can be observed by the added monitors. Arcs connecting recovery places and transitions of the initial system are added based on the obtained scenario. The concept of the extend the adjoint set of a siphon is presented due to a resource failure that needs to be observed while cannot be observed by the added monitors, leading to the modification of the arcs added in the first step. Consequently, a robust controlled system is acquired. Finally, examples are presented to demonstrate the proposed method.

Robust deadlock control of automated manufacturing systems with multiple unreliable resources

Over the past decade or so, the deadlock control problem of automated manufacturing systems (AMSs) with unreliable resources received a great deal of research attention. Most existing work to date assumes that the studied AMSs contain a single unreliable resource. Most existing control methods belong to the class of deadlock avoidance ones. This paper focuses on deadlock prevention for AMS with multiple unreliable resources. Our goal is to guarantee the continuous production of those parts not requiring any of the failed resources in case of any resource failure. A Petri net model is developed to characterize the failure and repair of unreliable resources. Based on it, a robust deadlock prevention controller that satisfies the above desired property is proposed. Experimental results indicate its effectiveness and superiority over the state-of-the-art methods.

Two-step approach to robust deadlock control in automated manufacturing systems with multiple resource failures

ABSTRACTIn an automated manufacturing system (AMS), resource failures are inevitable, which renders the existing deadlock control policies for AMSs without considering resource failures ineffective. For the AMSs with multiple unreliable resources, in this paper, a method is developed for robust deadlock resolution using the framework of Petri nets (PNs). The considered AMSs are modeled with PN models called system of simple sequential process with resources (S3PR). An unreliable S3PR (U-S3PR) is obtained by adding recovery subnets that model the resource failures and recovery procedures of the places where resource failures may happen. Based on the model, a two-step approach is developed to design a robust controller. At Step 1, we use a siphon-based deadlock control method to analyze the behavior with resource failures and propose an incomplete robust deadlock controller for a U-S3PR. At Step 2, a reachability-graph-analysis-based method is utilized to consummate the robust deadlock controller. Then, a robust liveness-enforcing supervisor is derived to make an unreliable S3PR live even if multiple types of resources break down. Finally, the proposed method is illustrated by using an example.

Deadlock and blockage control for manufacturing systems with failure‐prone workstations

It is essential to avoid deadlock and blockage in the operation of an automated manufacturing system (AMS) since they cripple a part of the system, if not the whole, and then deteriorate system performance. Though a large number of approaches are developed to resolve this issue, few of them are directly applicable to AMSs with failure-prone resources. This study focuses on the supervision for deadlock avoidance and blockage control in a class of AMSs with multiple unreliable resources, where each resource is a workstation. The authors hope that the system, under the control of a supervisor, can at all time automatically continue producing parts whose processing routes do not contain any of the currently failed workstations. Inspired by the widely known Banker's algorithm and a resource order policy, this study presents a robust supervisory controller that satisfies the above desired requirement. All the evidence shows that authors' policy performs better than the original one in terms of permissiveness. Furthermore, an example AMS from existing literature is used to illustrate the effectiveness of authors' proposed method.

Robust supervision using shared-buffers in automated manufacturing systems with unreliable resources

It has been an active area of research to solve the modeling, analysis, and deadlock control problems for automated manufacturing systems (AMSs). So far, all the system resources are assumed to be reliable in most of the existing approaches for deadlock-free and nonblocking supervisory control. However, many resources of AMSs are subject to failure in the real world. In order to develop a more practical and applicable supervisor, this work takes into consideration of multiple unreliable resources in a class of AMSs. On the basis of two variants of Banker’s Algorithm, this paper presents a robust supervisory control policy to avoid deadlock and blocking in these systems. The policy tries to make the best use of buffers of the shared resources to achieve the control objectives. Our controller is qualified to handle simultaneous multi-resource failures. By using formal language and automata theory, we establish its correctness. Moreover, our proposed method is verified via an AMS example, and we make comparison studies between our policy and some of the other similar type of policies in the literature.

Robust supervisory control policy for avoiding deadlock in automated manufacturing systems with unreliable resources

Developing effective supervisory control policies that guarantee deadlock-free operations for automated manufacturing systems (AMSs) has been an active area of research for the past two decades or so. A great deal of work has been done for the systems with reliable resources; while only a few works are about unreliable resources. This paper addresses the robust deadlock supervisory control problem in AMSs with multiple unreliable resources. The objective is to develop a robust supervisory control policy for AMS under which the system can continue producing all part types not requiring any of the failed resources without manual intervention. Our policy is made up of a modified Banker’s Algorithm and a set of remaining resource capacity constraints. A state is feasible if and only if it satisfies both of them. By using the improved version of the existing Banker’s Algorithm, our control policy has more permissibility. An example is provided to illustrate that the policy gains advantage over the original one in permissiveness.

Robust Supervisory Control for Product Routings With Multiple Unreliable Resources

Manufacturing systems are often subject to resource failure. In past work, we developed ldquorobustrdquo supervisory controllers for the single-unit resource allocation model. These guarantee that if any subset of resources fail, parts in the system requiring failed resources do not block the production of parts not requiring failed resources. To establish supervisor correctness, we assumed that each part type required at most one unreliable resource in its route. We now relax this assumption using a central buffer and present supervisors that guarantee robust operation without assumptions on route structure.

Robust supervisory control for Production Systems with multiple resource failures

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 Little research has addressed allocating resources that may 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 properties.