![]() ![]() ![]() And when several shipments are made at different dates and their corresponding returns noted, the recorded data are in the form of a triangular matrix. It’s common to keep track of reliability field data in the form of number of items shipped and number of items returned from a particular shipment over time. Naturally, someone doing warranty analysis in Minitab should want to compute this value too! But looking at raw reliability field data, which are recorded in the form of a triangular matrix, it’s not obvious how to compute B10 life! So a manufacturer might set a warranty period after a product’s B10 life, for instance, with the goal of minimizing the number of customers who will take advantage of the warranty should the product they purchase fail within the warranty period. Why? Because it indicates the time at which X% of items in a population will fail. But before I round out my BX life blog series with rationale for why BX life is one of the best measures for reliability, I thought I’d take this opportunity to address the LinkedIn question-as you might wonder the same thing.īX Life can be a useful metric for establishing warranty periods for products. My second post, How to Calculate BX Life, Part 2, shows how to compute any BX life in Minitab. In case you missed it, my first post, How to Calculate B10 Life with Statistical Software, explains what B10 life is and how Minitab calculates this value. That is, until this question appeared on the Minitab LinkedIn group: I thought 3 posts would capture all the thoughts I had about B10 Life. ![]()
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