Shipulski On Design

Archive for the ‘A/B Data’ Category

Improving product robustness is straightforward and difficult. Here’s how to do it.

Identify specific failure modes, prioritize them, and go after the biggest ones first. Failure modes can be identified through multiple sources. Warranty data is sometimes coded by failure mode (more precisely, symptom type), so start there. The number one failure mode in this type of data is typically “no problem found”, so be ready for it. Analysis of the actual products that come back is another good way. Returned product is routed to the appropriate engineer who analyzes it and enters the failure mode into a database. A formal design FMEA generates a list of prioritized failure modes through the risk priority number (RPN), where larger is more important. To do this, engineers are hauled into a room and a facilitator helps them come up with potential failure modes. One caution – the process can generate many failure modes, more than you can fix, so make the top five or ten go away and don’t argue the bottom fifty. It makes no sense to even talk about number eleven if you haven’t fixed the top ten. But the best way I have found to identify failure modes (problems) that are meaningful to the customer is to ask the technical services group for their top five things to fix. They will give you the right answer because they interact daily with customers who have broken product. They won’t expect you to listen to them (you never listened before), so surprise them by fixing one or two on their list. They will be grateful you listened (they’ll likely want to buy you coffee for the rest of your career) and your customers will notice.

Once failure modes are identified, define the physics of failure – why the product breaks. This is tough work and requires focused thought and analysis. If, when you break the product, it “looks like” the ones coming back from the field, you have defined the physics of failure. This is the same thing as replicating the problem in the lab. Once that’s defined, create an automated test rig or experimental setup that breaks the product in a way that captures the physics of failure. I call this test rig a robustness surrogate because it stands in for the actual failure mode seen in the field. The robustness surrogate should break the product as fast as possible while retaining the physics of failure so you can break it and fix it many times before product launch. The robustness surrogate should be designed to break the product within minutes, not hours or days – the faster the better.

To know if product robustness is improved, the baseline (or existing) design is broken on the robustness surrogate. The new design must survive longer on the robustness surrogate than the baseline design. The result is A/B data (baseline design/ new design) that is presented at the design review using a simple bar graph format which I call big-bar-little-bar. Keep improving robustness of the new design even if it outperforms the baseline design by a factor of ten – that’s not good enough for your customers.

Don’t stop improving robustness until you run out of time, and don’t stop if you meet the arbitrary MTBF specification. Customers like improved robustness, and in this case too much of a good thing is wonderful.

Using this method, I reduced warranty cost per unit by 75% over a five year period. It worked.

2009 is a tough year, especially for CEOs.

CEOs have a strong desire to do what it takes to deliver shareholder value, but that’s coupled with a deep concern that tough decisions may dismantle the company in the process.

Here is the state-of-affairs:

Sales are down and money is tight.  There is severe pressure to cut costs including those that are linked to sales – marketing budgets, sales budgets, travel – and things that directly impact customers – technical service, product manuals, translations, and warranty.

Pricing pressure is staggering.  Customers are exerting their buying power – since so few are buying they want to name their price (and can).  Suppliers, especially the big ones, are using their muscle to raise prices.

Capacity utilization is ultra-low, so the bounce-back of new equipment sales is a long way off.

Everyone wants to expand into new markets to increase sales, but this is a particularly daunting task with competitors hunkering down to retain market share, cuts in sales and marketing budgets, and hobbled product development engines.

There is a desire to improve factory efficiency to cut costs (rather than to increase throughput like in 2008), but no one wants to spend money to make money – payback must be measured in milliseconds.

So what’s a CEO to do?  Read the rest of this entry »

Six Lessons Learned DFA paper for May 2006 DFMA Forum.pdf  (8 pages)

Each company works with Design for Assembly (DFA) methods for different reasons.  Some companies want to take cost out of their products, some want to make more products in their factories, and some want to simplify the product to increase quality and reliability.  In a growing market a company wants to reduce labor content to get more products through the factory to meet demand without adding assembly workers.  And, in a growing market a company wants to reduce the required floor space required to meet demand without building another factory.  Remarkably, the goals are similar for Read the rest of this entry »