Eye-Popping Stunning Results
Abstract
Chris and Fred discuss the challenge of being asked by someone to show (or visualize) stunning, eye-popping results for some reliability activity. How do we do this? Is this possible?
Key Points
Join Chris and Fred as they discuss how we go about demonstrating stunning, eye-popping results for the amount of resources and organization has invested in a reliability activity. It could be a FMEA. It could be a HALT program. It could be reliability data analysis. So how do you begin?
Topics include:
- What do the ‘people’ want? If your boss is viciously focused on time to market (and not much else), then make sure your stunning, eye-popping results are not all about warranty costs. Your boss (incorrectly) doesn’t care about this. But reliability activities (for example) always make your production process faster and less problematic. So focus on this if this is what the boss wants to see. So always know what the people want.
- But we also need patience. For example, a FMEA is something whose benefit will be realized throughout the production process (even if those benefits are apparent to the participants at the start). So you can’t be halfway through your first amazing FMEA and then have wonderful results to demonstrate. At best, the people participating in the FMEA will be able to speculate or brainstorm the problems that would like be solved, along with indicative costs or delays associated with them. But a successful FMEA program will start to show that projects start to become less delay-prone and cheaper overall. The problem is that this is often not just due to a FMEA, or the other activity you are asked to show results from.
- And less is more. Or quantity is not quality. That’s right … if there is one ‘big ticket’ item, such as a $ 10 million saving, then have that be perhaps the ‘only’ thing in your presentation or visual. More words or messages dilutes your keywords or messages.
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SOR 975 Eye-Popping Stunning ResultsChristopher Jackson
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See https://fred-schenkelberg-project.prev01.rmkr.net/statistical-reliability-control/#more-522710 figure 1 for an eye-popping broom chart. The story is below the figure. It’s an example of Statistical Reliability Control. The story is an example of why people should keep track of the field reliability of electronics even if few fail during useful life.
Jerry Ackaret coined the term “broom” chart for graph of nonparametric reliability function estimates from successive cohorts.