This chapter considers the problem of deadlock avoidance in flexibly automated manufacturing systems, one of the most prevalent supervisory control problems that challenges the effective deployment of these environments. The problem is addressed through the modeling abstraction of the (sequential) resource allocation system (RAS), and the pursued analysis uses concepts and results from the formal modeling framework of finite state automata (FSA). A notion of optimality is defined through the notion of maximal permissiveness, but the computation of the optimal DAP is shown to be NP-Hard. Hence, the last part of the chapter discusses some approaches that have been developed by the relevant research community in its effort to deal with this negative complexity result. IntroductionContemporary manufacturing is characterized by (i) an ever increasing emphasis on automation and by (ii) a quest for broader product lines and more customized product offerings [22].Indeed, since the beginning of the industrial revolution, automation has been at the core of the mass-production concept and practices, enabling activities and tasks that frequently transcend the human element in terms of capability, consistency, durability and speed [21]. More recently, automation has also been advocated as a key enabler for controlling the overall production cost, especially in economies where labor cost is particularly high. Hence, there is an increasing tendency to confine the presence of the human element on the production shop-floor to supervisory and maintenance tasks only, while the actual production activity is taken over by "intelligent" hardware, materialized in the form of numerically controlled (NC) machines, CHAPTER 6. 2 robots, and other material handling equipment. Clearly, enabling the reliable deployment of such an extensive mode of automation is a pretty challenging task. Yet, in the recent years, things have been further complicated, and the aforementioned challenges have been further exacerbated, by the second manufacturing trend mentioned above, i.e., the emphasis that is placed by the global markets upon choice and customization. This trend implies a need to support the production of a broader set of items, in smaller batch sizes, and with shorter life spans. Such demand and production patterns negate the economies of scale and the efficiencies of the dedicated production lines that have been sought by traditional manufacturing, and (re-)places the emphasis on concepts like resource sharing, flexibility, reconfigurability and concurrency [18]. But the current reality has also shown that the effective support of these concepts on the manufacturing shop-floor is highly non-trivial, and it adds an entirely new layer of complexity and challenges to the aforementioned endeavors towards the automated operation of production systems. The manufacturing world has become increasingly conscious of the fact that the successful design and deployment of flexibly automated production systems necessitates the development of a (ma...
The development of efficient deadlock avoidance policies (DAP's) for sequential resource allocation systems (RAS's) is a problem of increasing interest in the scientific community, largely because of its relevance to the design of large-scale flexibly automated manufacturing systems. Much of the work on this problem existing in the literature is focused on the so-called single-unit RAS model, which is the simplest model in the considered class of RAS's. Furthermore, due to a well-established result stating that, even for single-unit RAS's, the computation of the maximally permissive DAP is intractable (NP-hard), many researchers (including our group) have focused on obtaining good suboptimal policies which are computationally tractable (scalable) and provably correct. In the first part of the paper, it is shown, however, that for a large subset (in fact, a majority) of single-unit RAS's, the optimal DAP can be obtained in real-time with a computational cost which is a polynomial function of the system size (i.e., the number of resource types and the distinct route stages of the processes running through the system). The implications of this result for the entire class of single-unit RAS's are also explored. With a result on the design of optimal DAP's for single-unit RAS's, the second part of the paper concentrates on the development of scalable and provably correct DAP's for the more general case of conjunctive RAS's.
Deadlock avoidance in sequential resource allocation systems is a well-de ned problem in Discrete Event System literature, as it underlies the operation of many contemporary technological systems. In the past, the problem has been studied by means of a number of formal frameworks, including the nite state automata (FSA) and Petri nets (PN). In this paper, it is shown that a signi cant class of deadlock avoidance policies (DAP), known as algebraic PK-DAP's, originally developed in the FSA paradigm, can be analyzed using recent results from PN structural analysis. Furthermore, the approach to DAP analysis and design taken in this paper has led to the e ective generalization of the currently available algebraic PK-DAP's, and to their enrichment with new and more exible policy implementations.
In this paper, we apply discrete-event system techniques to model and analyze the execution of concurrent software. The problem of interest is deadlock avoidance in shared-memory multithreaded programs. We employ Petri nets to systematically model multithreaded programs with lock acquisition and release operations. We define a new class of Petri nets, called Gadara nets, that arises from this modeling process. We investigate a set of important properties of Gadara nets, such as liveness, reversibility, and linear separability. We propose efficient algorithms for the verification of liveness of Gadara nets, and report experimental results on their performance. We also present modeling examples of real-world programs. The results in this paper lay the foundations for the development of effective control synthesis algorithms for Gadara nets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.