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Avoidance versus detection and recovery problem in buffer-space allocation of flexibly automated production systems

机译:灵活自动化生产系统的缓冲区空间分配中的回避与检测和恢复问题

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摘要

Motivated by recent developments in the semiconductor manufacturing industry, this paper undertakes an analytical investigation of the problem of selecting optimally the deadlock resolution strategy for buffer space allocation in flexibly automated production systems. In the process, it extends the behavioral models for the aforementioned systems currently considered in the literature, to account for probabilistic uncontrollable effects like the requirement for extra finishing steps and/or rework, and it introduces a new deadlock resolution scheme, characterized as randomized deadlock avoidance. The combination of these two extensions brings the considered system behavior(s) to the realm of probabilistic automata, an area of increasing academic interest. For the resulting model, and under the assumption of Markovian timings, it develops an analytical methodology for selecting the optimal deadlock resolution strategy that maximizes the steady-state system throughput, and it demonstrates its effectiveness through application to a "prototype" system configuration. The obtained results provide an interesting analytical expression of the need to assess the gains obtained by the increased concurrency supported by the deadlock detection and recovery strategy versus the productivity losses experienced under this approach due to increased system blocking, and/or additional material handling overheads. It turns out that, for the considered system configuration, the optimal selection scheme switches between detection and recovery and pure deadlock avoidance, every time that the time cost of deadlock recovery, /spl tau//sub d/, crosses a threshold /spl Theta/, which is a function of the remaining system behavioral and timing parameters. Beyond its own theoretical merit, this last result raises also the question of whether the policy randomization introduced in this work will ever enhance the performance of any configuration in the considered class of Resource Allocation Systems (RAS); this issue will be investigated in a sequel paper.
机译:受到半导体制造业的最新发展的推动,本文对在柔性自动化生产系统中为缓冲空间分配选择最佳死锁解决策略的问题进行了分析研究。在此过程中,它扩展了文献中当前考虑的上述系统的行为模型,以解决概率不可控的影响,例如需要额外的精加工步骤和/或返工,并且引入了一种新的死锁解决方案,其特征是随机死锁回避。这两个扩展的组合将考虑的系统行为带入概率自动机领域,这是一个学术兴趣日益增长的领域。对于生成的模型,并在马尔可夫时序的假设下,它开发了一种分析方法,用于选择可最大化稳态系统吞吐量的最佳死锁解决方案策略,并通过将其应用于“原型”系统配置来证明其有效性。获得的结果提供了一个有趣的分析表达式,表明需要评估死锁检测和恢复策略所支持的并发性增加所带来的收益,以及由于系统阻塞增加和/或额外的物料搬运开销而导致的这种方法下的生产率损失。事实证明,对于所考虑的系统配置,每当死锁恢复的时间成本/ spl tau // sub d /超过阈值/ spl Theta时,最佳选择方案就会在检测与恢复以及避免纯死锁之间进行切换/,它是其余系统行为和计时参数的函数。除了其自身的理论价值外,最后的结果还引发了一个问题,即这项工作中引入的策略随机化是否会增强所考虑的资源分配系统(RAS)类中任何配置的性能;这个问题将在续篇中进行研究。

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