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



Published Nov 13, 2020
Patrick T. Hester Andrew J. Collins Barry Ezell John Horst


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 researchcentric 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 and demonstrates 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.

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prognostics, smart manufacturing, problem structuring methods, cognitive mapping, soft systems methodology

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