Project risk management in global manufacturing environment

Youn Sook Kim, Tomohiro Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Injection mold industry is a fundamental industry which decides competitiveness of manufacturing industries. Due to the OEM operation nature of injection mold industry, product standardization is difficult and market demands request short production lead time. Today, SMEs(Small and Medium-sized Enterprises) in injection mold industry seeks more efficient production process which can decrease lead time and cost by improving utilization of automated production equipment. However, compared to the other industries, injection mold industry become to be more specialized internationally and those manufacturing process needs tight data sharing and correlation between each process. Then project risk management becomes more important because multiple processes progress simultaneously with globally distributed manner with more uncertain conditions. In this paper, a project risk management method based on Bayesian Network model is proposed for accurate prediction of job completion time and preventing delay of delivery. Bayesian Network model is used as a probabilistic prediction tool to find risk of project delay and its root cause with means of measuring and monitoring performance of project progress.

Original languageEnglish
Title of host publicationProceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1016-1021
Number of pages6
ISBN (Electronic)9781467389853
DOIs
Publication statusPublished - 2016 Aug 31
Event5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 - Kumamoto, Japan
Duration: 2016 Jul 102016 Jul 14

Other

Other5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
CountryJapan
CityKumamoto
Period16/7/1016/7/14

Keywords

  • Bayesian Theory
  • Global Manufacturing Environment
  • Mold Manufacturing
  • Project Risk Management

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Kim, Y. S., & Murata, T. (2016). Project risk management in global manufacturing environment. In Proceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 (pp. 1016-1021). [7557762] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IIAI-AAI.2016.160