{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T03:12:30Z","timestamp":1764645150548},"reference-count":22,"publisher":"World Scientific Pub Co Pte Lt","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Unc. Fuzz. Knowl. Based Syst."],"published-print":{"date-parts":[[2012,10]]},"abstract":"<jats:p> The purpose of this paper is to present a hybridized technique for analyzing the behavior of an industrial system stochastically by utilizing vague, imprecise, and uncertain data. If the collected data are used as such in the analysis, then they high range of uncertainties occurred in the analysis and hence performance of the system cannot be done up to desired levels. For this, two important tools namely Lambda-Tau methodology and particle swarm optimization are used to formulate the hybridized technique PSOBLT (Particle swarm optimization based Lambda-Tau) to analyze the behavior of the complex industrial systems stochastically up to a desired degree of accuracy using available information. Six reliability indices namely failure rate, repair time, mean time between failures(MTBF), expected number of failures (ENOF), availability and reliability of the system are used for the analysis of system's behavior. Expressions of these reliability indices are obtained using Lambda-Tau methodology and particle swarm optimization (PSO) is used to construct their membership function utilizing the quantified information of the system in the form of triangular fuzzy number. The washing unit of a medium size paper plant situated in the northern part of India has been considered to demonstrate the approach. The behavior analysis results computed by PSOBLT technique have a reduced region of prediction in comparison of existing technique region, i.e. uncertainties involved in the analysis are reduced. Thus, it may be a more useful analysis tool to assess the current system conditions and involved uncertainties. <\/jats:p>","DOI":"10.1142\/s0218488512500341","type":"journal-article","created":{"date-parts":[[2012,10,3]],"date-time":"2012-10-03T06:38:13Z","timestamp":1349246293000},"page":"741-761","source":"Crossref","is-referenced-by-count":18,"title":["STOCHASTIC BEHAVIOR ANALYSIS OF AN INDUSTRIAL SYSTEMS USING PSOBLT TECHNIQUE"],"prefix":"10.1142","volume":"20","author":[{"given":"HARISH","family":"GARG","sequence":"first","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. P.","family":"SHARMA","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"MONICA","family":"RANI","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2012,10,2]]},"reference":[{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1016\/0026-2714(95)00145-X"},{"key":"rf3","first-page":"137","volume":"16","author":"Arora N.","journal-title":"Int. J. 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