Condition-based maintenance (CBM) and prognostics and health management (PHM) are established paradigms that evidently offer a competitive advantage to a company. However, to make a business case, it must be examined where PHM and a remaining useful life (RUL) estimation can lead to substantial benefits. These benefits are strongly tied to the decision-making that succeeds prognostics. While the prognostics component of PHM is well examined, research on post-prognostics decision-making (PDM) is still in its infancy. It is generally assumed that PHM can lead to benefits for business processes beyond 'traditional' maintenance management. Unfortunately, there is no overview for which processes (such as production scheduling or route planning) PDM can be applicable and how exactly specific optimizations and their corresponding benefits can be achieved. This work provides a structured literature review on PDM and identifies studies that exploit the RUL prediction for optimizing business processes. The review synthesizes the following aspects within a PDM framework: a) which processes are improved through post-prognostics decision-making, b) what decisions must be made, and c) what novel benefits are achieved and which challenges arise. This review enables scholars to identify how current prognostics research can be extended to the decision stage of CBM and PHM and aids practitioners in pinpointing how operations can be optimized through PDM.
How to Cite
Decision-Making, Review, Post-Prognostics
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.