多状态物料搬运系统的可用性和卸载能力评估,随机环境下的运行和物料搬运的随机需求

Sagi Finish, Marina Felshin, I. Frenkel, L. Khvatskin
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引用次数: 0

摘要

我们提出了多状态物料搬运系统的可用性和卸载能力评估,在随机环境下运行,并研究了随机需求对物料搬运的影响。为了确定系统的可用性和卸载能力,我们建立了马尔可夫模型,代表了物料搬运系统中各个元件和子系统的各种卸载能力水平。整个系统可以用96种状态的马尔可夫模型来表示,96种状态表示整个过程的不同性能水平。物料搬运的随机需求被描述为典型的三层马尔可夫模型。整个马尔可夫模型被描述为包含288个微分方程的系统,其求解是一个复杂的问题。为了克服这一障碍,我们提出了一种lz变换方法在多状态物料搬运系统(MSMHS)可用性和卸载能力评估中的应用。结果表明,该方法可应用于与需求、卸载能力和生产过程相关的各种MSS系统的工程决策和构建中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Availability and Unloading Capacity Assessment of Multi-state Material Handling System, Operate in a Stochastic Environment and Material Handling Stochastic Demand
We present availability and unloading capacity assessment of multi-state material handling system, operate in a stochastic environment and investigate an impact of stochastic demands for material handling. In order to determine the system availability and unloading capacity we constructed Markov models, representing the various unloading capacity levels of each element and sub-system in the Material Handling System. The entire system can be represented as Markov model with 96 different states expressing the different performance levels of the entire process. The stochastic demands for material handling is described as three level Markov model, typical for such environment. The entire Markov model is described as system with 288 differential equations, solution of which is complicated problem. To overcome this obstacle we propose an application of the Lz-transform method for availability and unloading capacity assessment of multi-state Material Handling System (MSMHS). We demonstrated that the suggested method can be implemented in engineering decision making and construction of various MSS systems related to requirements, unloading capacity and production processes.
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