A review of research in manufacturing prognostics

K. M. Goh, B. Tjahjono, T. Baines, S. Subramaniam

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

Abstract

With the fast changing global business landscape, manufacturing companies are facing increasing challenge to reduce cost of production, increase equipment utilization and provide innovative products in order to compete with countries with low labour cost and production cost. On of the methods is zero down time. Unfortunately, the current research and industrial solution does not provide user friendly development environment to create "Adaptive microprocessor size with supercomputer performance" solution to reduce downtime. Most of the solutions are PC based computer with off the shelf research software tools which is inadequate for the space constraint manufacturing environment in developed countries. On the other hand, to develop solution for various manufacturing domain will take too much time, there is lacking tools available for rapid or adaptive way of create the solution. Therefore, this research is to understand the needs, trends, gaps of manufacturing prognostics and defines the research potential related to rapid embedded system framework for prognostic.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Industrial Informatics, INDIN'06
Pages417-422
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event2006 IEEE International Conference on Industrial Informatics - Singapore, Singapore
Duration: 16 Aug 200618 Aug 2006

Conference

Conference2006 IEEE International Conference on Industrial Informatics
Abbreviated title INDIN'06
CountrySingapore
CitySingapore
Period16/08/0618/08/06

Keywords

  • Condition based maintenance
  • Maintenance
  • Prognostics
  • Prognostics health monitoring

ASJC Scopus subject areas

  • Control and Systems Engineering

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    Goh, K. M., Tjahjono, B., Baines, T., & Subramaniam, S. (2007). A review of research in manufacturing prognostics. In 2006 IEEE International Conference on Industrial Informatics, INDIN'06 (pp. 417-422). [4053424] https://doi.org/10.1109/INDIN.2006.275836