How does your equipment fail? How do you plan for spares? Do you use your existing failure data to help refine your maintenance planning?
Given the title of the article, these questions are reasonable. As either a plant reliability or maintenance engineer do you also rely on gut feel to refine your estimates? If you rely on MTBF or similar metrics, you most likely do not trust the data to provide useful answers. Continue reading “Maintenance and Statistics Without MTBF”
In most circumstances we know as do our customers that failures will happen. It is finding the right balance between reliable performance and expectation that is difficult. In some cases it is the language we use to talk about reliability with our customers that leads to the confusion.
How do your customers talk about reliability
And, what can you do about it?
As engineers laying out a factory or designing a new product we have to meet the reliability expectations of our customers. It would be great if the system would not fail or need repair, yet that is often not the case. Continue reading “Customer Reliability Talk”
In an earlier article, we looked at how MTBF alone can be misleading when selecting an item for use in a design. In this article, we’ll take a look at how the MTBF metric falls short as an input to maintenance planning. There were three items in the referenced article, Item D, Item E, and Item F that we’ll consider. We already know each of their failure times are Weibull distributed with the following parameters and MTBF.
A guest article by Andrew Roland. In an earlier article, we looked at how MTBF alone can be misleading when selecting an item for use in a design. In this article, we’ll take a look at how the MTBF metric falls short as an input to maintenance planning.
Management of aging electronic systems is a problem faced by many industries. Management of these systems requires some understanding of their reliability performance. In the United States commercial nuclear industry several approaches are being taken in an attempt to understand the reliability performance of plant systems. This article describes one approach being used. The method is non- parametric and requires no specialized data analysis software.
Nuclear Power Plant Electronic System Reliability Study
by Andrew Rowland, CRE – a contributed paper.
Andrew is back with a paper describing using non-parametric approach to maintenance data. While not mentioning MTBF (which is good) the paper does provide alternatives to using a overly simply (i.e. MTBF) analysis of maintenance data.
I find the world of maintenance a very odd place to find MTBF. While it is possible, that a set of equipment or a machine may actually have a constant failure rate it is the exception rather than all that common. Assuming a constant failure rate doesn’t make it so. Continue reading “MTBF and preventative maintenance”
With the kind permission of Wayne Nelson and Robert Abernathy we are posting an article on the analysis of repair data. As you may know, the assumptions made when using simple time to failure analysis of repairable systems may provide misleading results. Using the analysis method outlined by Wayne is one way to avoid those costly mistakes. Continue reading “Graphical Analysis of Repair Data”