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An Investigation On The Effectiveness Of A Problem Structuring Method In A Group Decision-Making Process, Ying Thaviphoke
An Investigation On The Effectiveness Of A Problem Structuring Method In A Group Decision-Making Process, Ying Thaviphoke
Engineering Management & Systems Engineering Theses & Dissertations
There is no shortage of methods to address messy problems. A messy problem is a system of problems with multiple stakeholders who may hold different views of what is feasible or desirable. Decision-makers in a messy problem are prone to committing an error – especially the Type III error. One of the ways to mitigate the chance of committing the error in a messy problem is to reach a group consensus. Problem Structuring Methods (PSM) are the collections of participatory modeling methods that aim to tackle a messy problem. Despite the positive reports, literature indicates some challenges and criticisms of …
A Review Of Problem Structuring Methods For Consideration In Prognostics And Smart Manufacturing, Patrick T. Hester, Andrew J. Collins, Barry Ezell, John Horst
A Review Of Problem Structuring Methods For Consideration In Prognostics And Smart Manufacturing, Patrick T. Hester, Andrew J. Collins, Barry Ezell, John Horst
Engineering Management & Systems Engineering Faculty Publications
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 …