Design for Manufacturability Metrics

In this final section of our DFM basics series, we cover Design for Manufacturability metrics. Here we take a deep dive into how we measure and quantify DFM efforts so that we know we're making improvements in our design. Before we jump in, let's do a quick recap of what was covered in this series.

DFM Basics Recap

1. Design for Minimalism Our first step was to reduce as many components as possible in our designs.
2. Design for Standardization Next, we look where we can design existing components to be reusable, to further reduce unique parts.
3. Design for Assembly Then, we look at how components come together to see what features we can design into the parts, to aid in assembly.
4. Design for Component Manufacturability We then take a deep look into how components are designed in ways that lend to how they are manufactured.
5. Design for Mistake Proofing Next, we review the quality aspects of our design to design for a zero defect product.
6. Design Robustly We furthermore review how robust we can design our product to ensure our designs can be manufactured well within specification.

We've covered a lot thus far and the possibilities to improve any new design are endless. So how do we strategize from here, and how do we know we are indeed improving the design for manufacturability? We can do so by measuring each design iteration with some very simple and high level manufacturing metrics.

Universal Design for Manufacturability Metrics

Design and manufacturability is a deep and complex subject matter that spans many industries and hence takes on many different forms. The good news is that all manufacturability metrics, regardless of industry or design, typically boil down to the same high level metrics.

The three key simple mantras are:

1. Improve Quality
2. Improve Productivity
3. Reduce Cost

With every new iteration, one should seek to simultaneously improve a design in these three areas. Please note, simultaneous is key! It is not enough to improve in one area while sacrificing in another. Great DFM efforts focus on improving all three.

Let's break down each of these three mantras into their best measurable corresponding DFM metrics:

Quality Metrics

Yield

A simple yield calculation of actual completed units divided by start quantities can paint a great picture of how a design stacks up. This metric is presented as a percentage of how many units you can expect when starting a work order. A lower yield percentage means more material and labor costs thrown away in scrap units, and often points to something that can be fixed in the design.

When measuring yield in a products early stages, try not to get too hung up on formalities. Even tracking yield on an early small quantity build in a lab is fine. Record it in a simple notebook if needed. If specifications don't fully exist, use best engineering judgement. Also, be sure to take advantage of any predicate data that may exist from prior comparable designs in production, which have relevant failure modes.

Top Defect Pareto

All scrap should be categorized by a defect type. The top 3 to 5 defects should be analyzed. Pareto charts are great for this assessment. DFM Challenge: What can we do in the design to ensure these defects can no longer occur? Defect counts are more a sub-metric of overall yield, and are important to emphasize what aspects of our device requires the most attention.

This metric is best depicted 2 ways. First as a percentage of the number of scrap units from particular defect category divided by the overall scrap (a.k.a percentage of fallout). This helps prioritize what category to target. Next, as a percentage of the number of scrap units from particular defect category divided by the work order quantity (a.k.a percentage of scrap). This helps us understand the impact of the defect.  If we we're to resolve this defect, how much it would improve overall yield.

Manufacturing companies often have pre-categorized scrap types. Use these if applicable, but feel free to create new and more meaningful categorizes that make best of common sense. Sometimes pre-existing categories fall short of telling the full story, especially for new designs. If the quality system won't allow for this (which happens all too often), keep your own separate unofficial categorization that works best for you and the design. After all, this is intended to be an actual tool to help improve the design and not just a paperwork exercise.

Productivity Metrics

Touch Time

This metric is a simple time measurement of how many hours it takes a human to build a product. Since we pay our workforce, labor hours directly impacts the overall cost of the device. A design with relatively high labor hours will guide us to look for areas of the design that we can better simplify and lend to assembly.

Note that touch time is not an exact science as people vary with respect to each other, and over time. At the start of a new design it may take 5 hours for an operator to build a product. One year later, after building thousands of units, the same operator can complete the job in 3 hours. Don't over think this. Simply time a build for a best approximation using a stopwatch, or by recording start and end times on a paper.

What's more meaningful for DFM, is to break down the assembly into relevant steps for comparison. Ask, which steps take the longest to complete and is there anything that can be changed in the design to reduce touch time.

Training Time

This metric is even less of an exact science than touch time, but very important none the less. First break down the assembly into relevant assembly steps. Next, simply ask technicians, operators, or whoever first learns how to build your product, approximately how long it might take for others to learn and become proficient at that step. This can be measured in days, weeks, months as applicable.

Though training time may not directly impact a product's cost, this metric still tells a very important story. First, it gives a sense of how complicated an assembly step is to perform. If all but one step takes about a day to learn, and that one step takes 3 months to learn, we know where to focus our attention in simplifying the design. Next, it gives context for how long it would take to scale a product into production volumes, which is crucial for new products.

Cost Metrics

Material Cost Pareto

Total material cost is a basic and crucial metric that should be tracked and compared with iterative concepts. Material cost directly impacts overall product cost. To break this down further, each part in the assembly should be sorted from most to least expensive on a cost pareto chart. DFM teams should review at least the top 3 - 5 most expensive parts to see where design improvements can be made.

Part Count Assessment

Total part count and unique part count is another simple yet powerful metric that should be captured and compared for each design iteration. Total part count is the number of all parts in an assembly, which includes multiple quantities of the same part (such as quantity 5 of the same screw). Unique part count tracks only unique numbers (so a unique screw would count as 1 regardless of quantity). The lower part count, the better! DFM teams should seek to utilize Design for Minimalization tools to reduce part count as much as possible.

Creative Design for Manufacturability Metrics

Aside from the universal and high level manufacturing metrics above, any number of additional metrics can be created to portray DFM. Teams should create the metrics that tell the most about their product. When doing so, keep in mind the following three criteria that make for a good DFM metric:

1. Metrics must be quantifiable
2. Metrics should lead to prioritization
3. Metrics should lead to key takeaways

Additional metrics may not always be necessary. When considering additional metrics, one should ask what keeps you up at night about this new design. Almost any issue can be captured in a creative manufacturability metric. Examples may include: Number of glue bonds, number of screws, number of lubricant applications, number of suppliers a part is sent to before final assembly. We recommend not adding more metrics than necessary, but add the ones that are most important for the product you are building.

How to prioritize and improve DFM metrics?

So now that we've captured all of these metrics, what do we do with them? Moreover, how do we prevent drowning in them? All of these metrics paint a picture for your design as it relates to manufacturability. Each of these can be portrayed visually, in bar charts and pareto graphs. All of these metrics should lead to some key takeaways, that point to what areas are major pain points verses other areas that are doing well.

The goal should not be to solve everything. In fact it is far better to prioritize only 3 to 5 big impact DFM efforts in the next design iteration, rather than trying to solve everything. Identify and write down each high impact DFM improvement effort in order of priority. When in doubt which given metric to prioritize, keep in mind that almost all metrics (yield, touch time, part count, etc.) can be converted to a dollar value. Cost is a universal metric that can help put each criteria into perspective by a standard unit, thus to better know where to prioritize.

Next, brainstorm innovative redesigns that can improve these metrics, and ensure each of these top priority DFM efforts has an owner. Ownership is best assigned to the individual who cooks up the awesome new design idea. These passionate people are often the most excited and driven to test out their new idea.

Finally, create the next prototype as soon as possibly and test how this measures up compared the metrics of the latest prototype. Did the design indeed improve? Did the change cause any negative unintended consequences to other manufacturability metrics? Great DFM is about accepting the challenge of how fast and frequently we can review, brainstorm, redesign and iterate before the design is frozen. With each iteration loop we seek to make the design better and better.

The core mission of DFM and DFM metrics

The core mission of DFM is to constantly iterate, and with each iteration, to beat the last design in terms of manufacturing metrics.

DFM is not about setting some arbitrary manufacturing metric goals. There is really only one live or die manufacturing metric for any new product, which is that the production cost must be low enough to make the needed margin for the business to survive. This cost target is not an end goal for DFM, but more so a necessary business metric. In truth, DFM efforts themselves have no end goal. Instead, DFM is a continuous challenge of making the design better than it was yesterday.

All to often, teams try to set arbitrary target metrics with DFM. Don't fall into this pitfall. These goals are often not rooted in reality or the laws of physics. They often derail attention, placing blinders on other obvious DFM opportunities that might have been improved but did not get any attention because it did not serve the arbitrary target. Another big problem with arbitrary target metrics occurs whenever teams actually reach their goal. Then what? All forward progress and innovation stops!

Instead, our drive with DFM metrics is simply to accept the challenge of always being better than where we were. DFM culture means continually improving, iteration after iteration, as quickly and innovatively as possible, with no actual end goal. When teams fully embrace this culture of continuous improvement, the potential for DFM greatness becomes limitless. This type of culture fosters an environment where DFM innovation exceeds all expectation, pushing the boundaries of what was thought possible. By nurturing this culture, teams fully unlock the potential of their design development process and go on to achieve incredible results.