Anticipating performance of work stations in MMPs at sensor breakdowns

Tung Sun Chan, M. K. Tiwari

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Multi-station Manufacturing Processes (MMPs) occasionally encounters the problem of deviation in the attributes of the products as compared to the design specifications. Sensors are installed in the work stations to detect the sources of errors in the product dimensions. This paper identifies the problem concerned with breakdown of the sensors and proposes an approach that identifies the interdependence relations among the various sensors using Bayesian Networks. Particle Swarm Optimization technique has been used to search the Optimal Bayesian Network. This proposed strategy will aid the manufacturers to check the delay in production time and to control the quality of production at times of sensor breakdown. IEEE.
Original languageEnglish
Title of host publicationProceedings of the 4th IEEE International Conference on Management of Innovation and Technology, ICMIT
Pages1331-1336
Number of pages6
DOIs
Publication statusPublished - 3 Dec 2008
Externally publishedYes
Event4th IEEE International Conference on Management of Innovation and Technology, ICMIT - Bangkok, Thailand
Duration: 21 Sep 200824 Sep 2008

Conference

Conference4th IEEE International Conference on Management of Innovation and Technology, ICMIT
Country/TerritoryThailand
CityBangkok
Period21/09/0824/09/08

Keywords

  • Bayesian networks
  • Multi-station manufacturing Process
  • Particle swarm optimization
  • Sensor breakdown

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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