Anticipating performance of work stations in MMPs at sensor breakdowns

Tung Sun Chan; M. K. Tiwari

doi:10.1109/ICMIT.2008.4654564

Anticipating performance of work stations in MMPs at sensor breakdowns

Tung Sun Chan, M. K. Tiwari

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-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 language	English
Title of host publication	Proceedings of the 4th IEEE International Conference on Management of Innovation and Technology, ICMIT
Pages	1331-1336
Number of pages	6
DOIs	https://doi.org/10.1109/ICMIT.2008.4654564
Publication status	Published - 3 Dec 2008
Externally published	Yes
Event	4th IEEE International Conference on Management of Innovation and Technology, ICMIT - Bangkok, Thailand Duration: 21 Sept 2008 → 24 Sept 2008

Conference

Conference	4th IEEE International Conference on Management of Innovation and Technology, ICMIT
Country/Territory	Thailand
City	Bangkok
Period	21/09/08 → 24/09/08

Keywords

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

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering

More information

10.1109/ICMIT.2008.4654564

Cite this

@inproceedings{f5b6cdc736a04e239ba7b6e4759ce756,

title = "Anticipating performance of work stations in MMPs at sensor breakdowns",

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.",

keywords = "Bayesian networks, Multi-station manufacturing Process, Particle swarm optimization, Sensor breakdown",

author = "Chan, {Tung Sun} and Tiwari, {M. K.}",

year = "2008",

month = dec,

day = "3",

doi = "10.1109/ICMIT.2008.4654564",

language = "English",

isbn = "9781424423309",

pages = "1331--1336",

booktitle = "Proceedings of the 4th IEEE International Conference on Management of Innovation and Technology, ICMIT",

note = "4th IEEE International Conference on Management of Innovation and Technology, ICMIT ; Conference date: 21-09-2008 Through 24-09-2008",

}

Chan, TS & Tiwari, MK 2008, Anticipating performance of work stations in MMPs at sensor breakdowns. in Proceedings of the 4th IEEE International Conference on Management of Innovation and Technology, ICMIT., 4654564, pp. 1331-1336, 4th IEEE International Conference on Management of Innovation and Technology, ICMIT, Bangkok, Thailand, 21/09/08. https://doi.org/10.1109/ICMIT.2008.4654564

Anticipating performance of work stations in MMPs at sensor breakdowns. / Chan, Tung Sun; Tiwari, M. K.

Proceedings of the 4th IEEE International Conference on Management of Innovation and Technology, ICMIT. 2008. p. 1331-1336 4654564.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Anticipating performance of work stations in MMPs at sensor breakdowns

AU - Chan, Tung Sun

AU - Tiwari, M. K.

PY - 2008/12/3

Y1 - 2008/12/3

N2 - 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.

AB - 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.

KW - Bayesian networks

KW - Multi-station manufacturing Process

KW - Particle swarm optimization

KW - Sensor breakdown

UR - http://www.scopus.com/inward/record.url?scp=56849116861&partnerID=8YFLogxK

U2 - 10.1109/ICMIT.2008.4654564

DO - 10.1109/ICMIT.2008.4654564

M3 - Conference article published in proceeding or book

SN - 9781424423309

SP - 1331

EP - 1336

BT - Proceedings of the 4th IEEE International Conference on Management of Innovation and Technology, ICMIT

T2 - 4th IEEE International Conference on Management of Innovation and Technology, ICMIT

Y2 - 21 September 2008 through 24 September 2008

ER -

Anticipating performance of work stations in MMPs at sensor breakdowns

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this