Knowledge in Maintenance
Hance, Knowledge is regarded as a critical resource within a Maintenance Organisation. It resides partially in the minds of employees who are still working in the organization, and partially in texts written in the past by current and previous employees. Knowledge is the result of human experience. In literature the distinction is made between explicit knowledge (written down in texts) and tacit knowledge (embedded in the minds of employees). One of the challenges of Knowledge Management is to incite employees to make tacit knowledge explicit. This is the only way of making sure that knowledge becomes accessible to others, in the absence of the original knowledge owner.
Knowledge Management in Maintenance
“Knowledge management is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise’s information assets. These assets may include databases, documents, policies, procedures, and previously un-captured expertise and experience in individual workers.” (Duhon, Gartner Group, 1998).
Or a more recent and shorter definition: “Knowledge management is the practice, process and culture of creating, sharing and improving an organization’s knowledge.” (Devin Fowler, Simplicable, 2013)
Knowledge Management initiatives in Maintenance start with defining a structure for the Maintenance Knowledge. In most cases this is done by applying folder structures or by defining tags for the documents. This quickly becomes a huge mountain to climb, and many projects are abandoned prematurely: it is hard to get a consensus on the right ‘structure’ and even when you reached a consensus, the structure is not respected by the users in their daily work, resulting in documents that are mislabeled or stored in the wrong shared folder. And then there are other challenges like: how do you label mails, drawings, etc.? And what with the texts that are stored in your Work Order System?
What many maintenance organizations overlook is that during their maintenance processes, a lot of knowledge is already made explicit. Organizations who have implemented a Computerized Maintenance Management System (CMMS) often work with a work order process that is fully supported by that CMMS. What many are not ware of is that the maintenance requests and the maintenance reports in their CMMS contain valuable information for future maintenance jobs. Therefore a first challenge is to ask maintenance employees to write down a bit more extensively the problem that occurred, the findings of the problem analysis, the preparation of the maintenance job and finally the maintenance report with details of the actual work done. But why would they do that? They have it in their head. They will remember the next time. Or at least that’s what they think.
Maintenance Engineers will be more willing to write down their knowledge when they experience themselves the benefits of finding back information on previous experiences.
Knowledge Discovery in Maintenance
Therefore the true challenge is not really the structuring and capturing of knowledge, but rather making sure that the information one is looking for can be found in the existing documentation. This is what is called the Knowledge Discovery. “Knowledge discovery is the process of discovering useful knowledge from a collection of data.” (Techopedia).
CMMSs offer a variety of reports to analyze the Work Orders from a financial or logistic perspective based on structured data (like equipment type, spare parts, quantities, cost, etc.). None of them however allow the users to get insights from the unstructured data (texts and documents) in their CMMS.
This challenge of getting insights from the textual information in a CMMS is all the more challenging when the company has used various IT systems over the years. When this is the case, the user has no other option than to search through every IT system separately (at least when the IT system offer a search function for textual information). Not many employees go through that pain. As a consequence choices are made and decisions are taken based on incomplete information.
Where is all the Knowledge?
Enters the Insights Engine. An Insights Engine is an intelligent type of Enterprise Search Engine. An insights engine
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