When something breaks down, we investigate. We take things apart, clean and lubricate them in line with our procedures. We believe that we have done everything to prevent wear and tear. But lubrication does not simply mean applying oil or grease in the right places. It also means ensuring the right amount and the right grade.
If we apply too much grease to a bearing that spins at high rpm, it can overheat and fail as a result. The type of grease may well be correct, but the amount is wrong. The same applies when replacing grease. Some types cannot be mixed, as they can solidify and lead to overheating.
In solving problems and analyzing root causes, historical data is often a valuable tool. To make analysis easier, it’s important to create a structure for your way of reporting and to ensure that everyone is aware of why and how you report. We naturally want a maintenance system to have the ability to track faults so that we can identify the root causes. MaintMaster uses completion code groups and completion codes for this.
However, we do not recommend generating completion codes to identify the exact cause for each individual job. In many instances, a few general codes are sufficient to understand a lot from your analysis. The equipment and the frequency of the work you perform, together with good completion codes are enough to identify root causes or at least provide help along the way.
Let’s continue to use wear and tear as an example.
The root cause of wear and tear could be:
These three – substandard cleaning, substandard/incorrect lubrication and normal wear and tear are the three root causes that work very well as completion codes in MaintMaster maintenance system. It doesn’t have to be more complicated than this. Our experience is that many people believe that having more completion codes means more accurate statistics.
But this is rarely true; instead we have seen that the statistics are confusing and more difficult to decipher. Many codes are misinterpreted and overlap each other, presenting the user with a difficult choice, and as a result users opt for their favorites and almost exclusively pick these when reporting. Your statistics will therefore not be better.
For statistics, monitoring, and the ability to improve, it is important that everyone understand completion codes.
Good luck with your analyses.