作者: Constantin Filote , Calin Ciufude
DOI: 10.5772/10238
关键词: Markov model 、 Markov chain 、 Computer science 、 Component (UML) 、 Production line 、 Downstream (manufacturing) 、 Process (computing) 、 Downtime 、 State (computer science) 、 Reliability engineering
摘要: A manufacturing system includes a set of machines performing different operations, linked by material handling system. major consideration in designing is its availability. When machine or any other hardware component the fails, reconfiguration often less than perfect. It shown that, if these imperfections constitute even very small percent all possible faults, availability may be considerably reduced. The computed as sum probabilities operational states. state when performance better threshold value. In order to calculate system, states (each corresponding an acceptable level) are determined. level production capacity satisfied. To analyze with failure/repair process, Markov models used. As large number components processes, system-level model becomes computationally intractable. this paper, decomposition approach for analysis systems decomposed cells. chain constructed and solved each cell i determine probability at least Ni time t. satisfies requirement i. determined so that carriers provide service required between i, Ni+1 i+1. i=1,...,n t, where n cells Production lines sets arranged produce finished product product. Machines typically unreliable experience random breakdowns, which lead unscheduled downtime losses. Breakdown affects causing blockage those upstream starvation downstream. minimize such perturbations, finite buffers separate machines. empty space protects against full starvation. Thus, modeled connected according certain topology. From theoretic perspective, 2