Only a very modest percentage of maintenance of capital goods is done condition-based, as opposed to plan-based or corrective. Doing much more would be very beneficial from a safety and operations perspective. Moreover, the basic methods have been known for some time. This paper addresses the question that, if condition-based maintenance (CBM) or Prognostic Health Management (PHM), as the terms commonly used to denote the same maintenance policy, is so logical and beneficial, why is it currently not more often applied in practice?
This paper suggests that the answer lies in a complex interplay of technical and organizational issues. This interplay is best conceptualized as a data enrichment chain, which starts and ends at the physical asset to be maintained and ends at the actual prognostic maintenance being executed and evaluated. This chain is described in more detail, and illustrated with examples from an open innovation project in the process industry in the Netherlands, the CAMPIONE fieldlab. From this description, it becomes evident that this chain is currently broken in many places. If CBM/PHM is to become more established as a business practice, these breaks will need to be fixed. The paper discusses several of the options of how to fix this data enrichment chain in practice.
How to Cite
data enrichment, organizational aspects, condtion-based maintanance, process industry, action research
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.