DocumentCode :
3131371
Title :
Using stochastic models to effectively schedule hardware test efforts
Author :
Hahn, John
Author_Institution :
Aircraft Div., Naval Air Warfare Center, Indianapolis, IN, USA
Volume :
2
fYear :
1995
fDate :
22-26 May 1995
Firstpage :
825
Abstract :
This paper identifies a stochastic method via which to plan a schedule of qualification or reliability testing of electronic hardware. The technique utilizes a Markov model to anticipate scheduling delays, exhibiting as its inherent advantages the following: (1) mean time between failures (MTBF) need not be known to generate the corresponding Markov statistics; (2) model anticipates random bottlenecks in scheduling that a deterministic model cannot; (3) model readily avails itself to computation of Markov statistics that estimate the time to completion of all tests (and its variance), in addition to the time to completion of each qualification or reliability test (and the respective variances of each test); and (4) a Markov model used in (3) has been translated into a synopsis of a proposed software configuration, to function as guideline via which to generate software that would execute the desired Markov matrix computations, in the event the time to test for a large group of DUTS is to be determined
Keywords :
Markov processes; delays; electronic engineering computing; electronic equipment testing; random processes; reliability theory; DUT; MTBF; Markov matrix computation; Markov model; Markov statistics; deterministic model; device under test; electronic hardware; hardware test; reliability testing; schedule; software configuration; software generation; stochastic models; Delay effects; Delay estimation; Electronic equipment testing; Guidelines; Hardware; Processor scheduling; Qualifications; Software testing; Statistical analysis; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace and Electronics Conference, 1995. NAECON 1995., Proceedings of the IEEE 1995 National
Conference_Location :
Dayton, OH
ISSN :
0547-3578
Print_ISBN :
0-7803-2666-0
Type :
conf
DOI :
10.1109/NAECON.1995.522032
Filename :
522032
Link To Document :
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