on Product Reliability

Yesterday had the chance to review the long list of Design for X topics. Assembly, environment, maintainability, and of course reliability, plus about a dozen other areas of focus. How is a design team to navigate all these different sets of constraints and objectives along with crafting a solution that works?

With a little creativity, you could relate every Design for X topic to reliability. Easier to assembly, fewer assembly errors leading to field failures, for example.

Another way to think about the Design for X space is to consider a superset instead. What are all these design considerations really about? What is common, including the design for reliability topic? With a little thought, it seems clear to me that we all are really considering how to identify and manage risk. [Read more…]

“Speak with Data!” commanded my former general manager. “Let the Data Sing” is an article I wrote long ago. We all have data, often too much data. We like to present based on what the data says. Yet, sometimes the speaking with data is not clear.

If you’ve done the data gathering, the analysis, the summary, all based on the data, how can you best reveal what the data says to enhance your results and recommendations?

Just because you can add a 3D pie chart doesn’t mean you should. Crafting meaningful charts is only one part of the puzzle. You also have to present the data in a clear and meaningful manner. Here is a set of suggestions to consider the next time you are preparing and presenting when data is involved. [Read more…]

As reliability professionals, we have a lot to do. Risks to identify, failures to analyze. Plans to draft, numbers to crunch. Meetings, writing, research, and leading fill the day.

The list of tasks that you have before you each day is impressive and daunting. So, how do you focus on what actually requires your attention and not just the tasks that get your attention?

[Read more…]

If we set a product reliability goal of 99% reliable over two years in the requirements document, what are we supposed to do tomorrow? On the other hand, if our goal is to write 1,000 pages for the next great novel by the end of the year and we have no pages written so far, well, we should write a page or two tomorrow.

A good goal provides a vision, a measurable milestone, a target. What it lacks is what we do from now till achieving that goal. If the goal is 1,000 pages in 365 days, we may want to set up a process to write at least 3 pages per day.

So, given a reliability goal, what do we do tomorrow, next week, and each week between now and when the goal is due?

A Good Reliability Goal

In previous work, I’ve written about setting reliability goals, connecting the goal to customer expectations, technical capability, and business needs. Plus, have written about the four (five) parts of a complete goal, including Function(s), Environment, Duration, and Probability (and all four continue to get more difficult as customers expect more).

A well-stated reliability goal provides direction and a measurable target for the entire team. It provides a basis to compare progress and to help frame “is the design reliable enough yet” discussions.

This is all well and good, yet is it enough? [Read more…]

I often joke that being a reliability engineer makes it difficult to get on an airplane. Yet air travel is by far the safest method of transportation. Maybe I just think about failure too much.

When a project manager views the day’s tasks, she sees timelines, connections, dependencies. When a marketing manager views a product idea, she sees benefits, sales channels, and profits. When a reliability engineer views a prototype, she sees the many ways it can fail.

Underlying how we view the world includes our assumptions, reasoning, and experience. We understand the world around us via the set of filters we use. We form conclusions and make decisions much the same way. Quickly and mostly automatically. [Read more…]

One of my standing searches revealed an article that has shows a nice example of reliability data analysis. The author analyzed the time-to-violent-death of Roman emperors. The article is interesting in a historical sense plus illustrates a few key points for any life data analysis.

The article, “Statistical reliability analysis for the most dangerous occupation: Roman Emperor” by Joseph Homer Saleh takes a look at the 69 Roman emperors and 62% of them that suffered a violent death. The idea of the study was to determine if there is some pattern to the deaths and if the analysis would reveal any insights for those studying the era of the Roman emperors. [Read more…]

Some may argue that just enough reliability data is just the right amount. Too much may lead to confusion, too little doesn’t inform well. The reliability work we do helps others make decisions, and recent work in how humans make decisions may help us prepare and present our results effectively.

If preparing reliability data-based recommendations, consider using less information. Ed O’Brien and Nadav Klein have found decision-makers tend to use much less data or information to make a decision than they think they will need.

If using data and the derived information to make a decision consider the situation carefully to know when to use a structured decision-making approach or to simply go with your gut. Daniel Kahneman and Gary Klein provide some insights and basic guidelines for decision making. [Read more…]