A Review of Problem Structuring Methods for Consideration in Prognostics and Smart Manufacturing

Patrick Hester, Andrew Collins, Barry Ezell, and John Horst
Publication Target: 
IJPHM
Publication Issue: 
Special Issue on Smart Manufacturing PHM
Submission Type: 
Full Paper
Supporting Agencies (optional): 
NIST
AttachmentSizeTimestamp
ijphm_16_016.pdf791.79 KBAugust 29, 2016 - 10:52am

Successful use of prognostics involves the prediction of future system behaviors in an effort to maintain system availability and reduce the cost of maintenance and repairs. Recent work by the National Institute of Standards and Technology indicates that the field of prognostics and health management is vital for remaining competitive in today’s manufacturing environment. While prognostics-based maintenance involves many traditional operations research-centric challenges for successful deployment such as limited availability of information and concerns regarding computational efficiency, the authors argue in this paper that the field of prognostics and health management, still in its embryonic development stage, could benefit greatly from considering soft operations research techniques as well. Specifically, the authors propose the use of qualitative problem structuring techniques that aid in problem understanding and scoping. This paper provides an overview of these soft methods and discusses how manufacturers might use them. An approach combining problem structuring methods with traditional operations research techniques would help accelerate the development of the prognostics field.

Publication Year: 
2016
Publication Volume: 
7
Publication Control Number: 
016
Page Count: 
12
Submission Keywords: 
problem structuring methods
prognostics
smart manufacturing
cognitive mapping
soft systems methodology
Submission Topic Areas: 
Standards and methodologies
Submitted by: 
  
 
 
 

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