Before repairing anything, a technician searches. The right electrical drawing, the machine's fault history, the person who has already seen this failure. That search time appears in no indicator, yet it is real, and it adds up on every job. It is often the most accessible productivity gain, well before optimising the repair itself.
Mimorian models industrial equipment and supports technicians in their diagnostic reasoning, so that every intervention enriches the plant's collective memory. Part of that value rests on something simple: putting the right information back in front of the technician at the moment they need it.
Search time, the cost nobody measures
Maintenance indicators track repair time, availability and the number of interventions. None of them tracks the time spent searching before any action is possible. Yet on many jobs, that time weighs as much as the repair.
The drawing for a twenty-year-old machine sits in a binder, or in a PDF lost on a server. Fault history is split between the CMMS, paper notebooks and the memory of the old hands. When the technician reaches the stopped machine, they start by piecing together what should have been immediately available.
Three searches that stack up on every failure
In practice the technician looks for three things, and each one takes time.
First the drawing: the right electrical, pneumatic or hydraulic schematic, in the right revision. Then the history: has this failure happened before, what was done last time, does it have a known cause. Finally the person: who, in the team or elsewhere, knows this machine and can unblock the situation. And that person is getting scarce, since 89% of manufacturing executives acknowledge a talent shortage [Deloitte/Manufacturing Institute, 2018], which stretches the search for the right expert further still.
Each of these searches can take a few minutes or several hours, depending on the state of the documentation and the availability of those who know. Multiplied by the number of interventions in a year, they add up to a considerable volume of time, entirely invisible on the dashboards.
Why more documents does not cut that time
The common reflex is to add documentation: scan the binders, fill in the CMMS, create shared folders. But piling up files is not enough. Large organisations lose an average of $47 million a year to inefficient knowledge sharing [Panopto, 2018]. The sticking point is the ability to retrieve information at the right moment, not the volume available.
A hard drive full of PDFs saves nothing if the technician cannot find the right document under pressure. Useful knowledge is information that is structured, tied to the machine, and one gesture away. Not one more folder to dig through.
Making information available at the moment of the failure
The real answer lies in access rather than storage. When drawings, documentation and history are tied to a model of the machine, the technician asks and the information comes back in the right place, with the right tag or component reference.
The technician can question the machine in their own words, even with both hands busy, and get the exact drawing, the procedure or the history of the failure in progress. Time spent searching turns into time spent diagnosing and repairing. And since every intervention enriches the base, the next search is faster still.
Conclusion
Search time is the hidden cost of maintenance: invisible in the indicators, but real at every failure. It is also the easiest to win back, because it calls for no instrumentation on the machines, only for information to be available at the right moment. Before optimising the repair, remove the time lost looking for what it takes to start it.
To understand how this information is structured for the long term, read our guide to capitalising maintenance know-how.
Sources
- Panopto, 2018 : Workplace Knowledge and Productivity Report
- Deloitte/Manufacturing Institute, 2018 : Skills Gap and Future of Work Study