Risk Barriers as Swiss Cheese?

There’s a model that can help us visualize and consider the different barriers to harm: The Swiss Cheese Model of Accident Causation.

Learn what makes up this model and how ideas are represented. There are also different ways that the model is being used today.

How can we design for controls, policies, or actions that are part of the use of our product but outside of our control? We step through an example of a situation where we’re thinking about our product design in this way.

 

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Environmental Stress Testing for Robust Designs

There is a rather large family of test methods associated with Qualitative Accelerated Tests. They’re also known as RETs (or Reliability Enhancement Tests).

Today, we’re focused on the models that are used to help us with the design. Awareness about these methods will help us with future test plans and project management. We talk about environmental stress testing and remind ourselves a little about HALT.

 

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Choosing a Confidence Level for Test using FMEA

We’re developing requirements for our product, including setting reliability requirements. Or we’re setting acceptance criteria for our test plans.

What confidence levels do we choose? We don’t have to blindly set them – we can base it off the risks of failure, using our FMEA (failure mode effects analysis).

 

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Getting Started with FMEA – It All Begins with a Plan

We’re starting to populate an FMEA table with our team. We get it started, but then we get stuck in disagreements. Or we think we finish it and then we don’t know what to do with it.

We can avoid these headaches with a little planning (or maybe a lot of planning – it depends on the project). We talk about risk management planning as it relates to FMEA.

 

 

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How can 8D help Solve my Recurring Problem?

We talk about the 8D methodology, describe situations where we could benefit from it, list each of the 8 Disciplines, and compare it to PDSA and DMAIC.

 

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Mistake-Proofing – The Poka-Yoke of Usability

How do we go about mistake-proofing our product design? As we’re looking at our user process, we can use a quality method that’s well-used in manufacturing production: poka-yoke (mistake-proof).

Download the guidelines and checklist, and then follow-along with the podcast.

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Getting Comfortable with using Reliability Results

We want to engage a reliability engineer in an analysis for our product design. They can help us produce some great information from which we can make decisions. You might be feeling uncomfortable about our team making a design decision based on those results. You don’t quite understand how the reliability engineer came up with the answer. You want to know where that information comes from so you can gauge the level of project risk of our decision.

We peel-back the curtain on reliability engineering methods. We explore reliability engineering’s roots and development, from the 1950’s through today, to better understand the results of an analysis. Having a general understanding of reliability methods can help us get comfortable with using the results.

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How to Self-Advocate for More Customer Face Time (and why it’s important)

There are many stories of design successes attributed to the right level of understanding of the customer. Product designers make decisions, daily, about how a product is going to look and perform. So, we need to really understand the customer. And, to really get the customer, engineers need to spend time with them.

Sometimes, the business doesn’t want us to interact with the customer or doesn’t think it would be valuable. Objections include that we’re not prepared for the user’s environment, that we’re too blunt or honest, or that we just overgeneralize what we learn, anyway. Or, there’s a reluctance because of costs. Besides seeing these objections first hand, someone also listed them out in a published book! This shows that this is common across industries.

Is that fair to design engineers? No matter if it’s fair or not. We can prepare ourselves to address those objections. We talk about how we can prepare ourselves to self-advocate for more customer face time.

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Choosing Quality Tools (Mind Map vs. Flowchart vs. Spaghetti Diagram)

Within our quality toolbox, there are a lot of graphical organizers. Some are better at fulfilling different goals than others. If we have a goal in mind, then we may choose a certain tool. However, we don’t want analysis paralysis about which tool is best to stop us from using any tool at all.

I share my 3 general guidelines about choosing a graphical quality tool, how to draw them, and when to use them.

Plus, we talk about 3 tools in particular, prompted by a social media ask: mind map, process flowchart, and spaghetti diagram. We get into what they are, when we’re most likely to use them, and how they can be used for design.

 

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The DFE Part of DFX (Design For Environment and eXcellence)

Design for Excellence (DFX) is a concept that includes many initiatives, like design for usability, design for manufacturability and assembly, and design for environment and disassembly. It’s a focus on doing things right, exceeding customer expectations, optimizing what’s needed while minimizing costs, and continuous improvement.

Today we take a deep dive on one of those aspects: design for environment (DFE), including design for disassembly. What are reasons that a business would consider this important, and how does a design engineer fit in?

 

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Results-Driven Decisions, Faster: Accelerated Stress Testing as a Reliability Life Test

We want to ensure our designs perform reliably, as expected and intended. With today’s high-reliability products and quick release to market, we probably don’t have enough time to just test our parts at normal use rates. It would take too long, because our products ARE so reliable.  Or, we’ll miss our window of opportunity to get our product to market.

There are several ways to get reliability data to make design decisions. One of the ways is reliability life testing of our product.

This episode explores how accelerated stress testing is one subset of other reliability life testing methods, when it’s a good idea, how we can approach doing it, and what we can do with the results.

 

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When to use DOE (Design of Experiments)?

What is design of experiments, or DOE? What do we use it for and what is it all about?  We talk about when we might want to use it during the design cycle, and we do this without getting into all of the how-to and mathematical equations.

 

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Design for User Tasks using an Urgent/Important Matrix

We’ve collected all sorts of preliminary information about our users that we’re using for a new product design. We may be faced with so much data we’re not sure where to turn first, or what design feature is a priority. There’s a simple, 2-way matrix we can use to help us sort it all out: an urgent/important matrix. We may have used it to prioritize tasks for ourselves or as a management strategy for our team.  But, we can also use it to evaluate the tasks our users take when using our product.

We talk more about this matrix in the podcast, and we talk through an example of how to use it to evaluate user tasks.

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Statistical vs. Practical Significance

When we’re looking at results (like measures of a characteristic), we need to take care not to get too hung-up on what the statistics is trying to tell us.  Yes, statistical tools are a good way for us to make decisions and the results can act as proof for us. But, there’s a practical, engineering side to results, too. We need to evaluate the statistical significance along with the practical significance.

We review an example and how to document it.

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