Title :
Analyzing system reliability using non-regenerative stochastic Petri nets
Author :
Sugasawa, Y. ; Vidale, R.F. ; Jin, Q.
Author_Institution :
Dept. of Math. Eng., Nihon Univ., Narashino, Japan
Abstract :
We extend the class of Markov models that can be described by a stochastic Petri net and describe analytical techniques for solving the resulting model. We consider a generalization of the Markov renewal process in which some of the states may not constitute regeneration points. We present a non-regenerative stochastic Petri net (NRSPN) that generates such a process, discuss its solution, and present an example of a spare-parts inventory system using the NRSPN model. After reviewing SPNs and Markov renewal processes, we define the NRSPN model in the context of a generalized Markov renewal process. Numerical results for specific distributions are given
Keywords :
Markov processes; Petri nets; probability; reliability theory; state-space methods; stock control; Markov models; Markov renewal process; non-regenerative stochastic Petri nets; spare-parts inventory system; state space; stock control; system reliability; Computer industry; Educational institutions; Information science; Markov processes; Materials requirements planning; Petri nets; Reliability engineering; Stochastic processes; Stochastic systems; Systems engineering and theory;
Conference_Titel :
Emerging Technologies and Factory Automation, 1995. ETFA '95, Proceedings., 1995 INRIA/IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-2535-4
DOI :
10.1109/ETFA.1995.496740