Shipulski On Design

Archive for the ‘How To’ Category

Though we can’t describe it in words, or tell someone how to do it, we all know innovation is good. Why is it good? Look at the causal chain of actions that create a good economy, and you’ll find innovation is the first link.

When innovation happens, a new product is created that does something that no other product has done before. It provides a new function, it has a new attribute that is pleasing to the eye, it makes a customer more money, or it simply makes a customer happy. It does not matter which itch it scratches, the important part is the customer finds it valuable, and is willing to pay hard currency for it. Innovation does something amazing, it results in a product that creates value; it creates something that’s worth more than the sum of its parts. Starting with things dug from the ground or picked from it – dirt (steel, aluminum, titanium), rocks (minerals/cement/ceramics), and sticks (wood, cotton, wool), and adding new thinking, a product is created, a product that customers pay money for, money that is greater than the cost of the dirt, rocks, sticks, and new thinking. This, my friends, is value creation, and this is what makes national economies grow sustainably. Here’s how it goes.

Customers value the new product highly, so much so that they buy boatloads of them. The company makes money, so much so stock price quadruples. With its newly-stuffed war chest, the company invests with confidence, doing more innovation, selling more products, and making more money. An important magazine writes about the company’s success, which causes more companies to innovate, sell, and invest. Before you know it, the economy is flooded with money, and we’re off to the races in a sustainable way – a way based on creating value. I know this sounds too simplistic.  We’ve listened too long to the economists and their theories – spur demand, markets are efficient, and the world economy thing. This crap is worse than it sounds. Things don’t have to be so complicated. I wish economists weren’t so able to confuse themselves. Innovate, sell, and invest, that’s the ticket for me.

Innovation – straightforward, no, easy, no. Innovation is scary as hell because it’s risky as hell. The risk? A company tries to develop a highly innovative product, nothing comes out the innovation tailpipe, and the company has nothing for its investment. (I can never keep the finance stuff straight. Does zero return on a huge investment increase or decrease stock price?) It’s the tricky risk thing that gets in the way of innovation. If innovation was risk free, we’d all be doing it like voting in Chicago – early and often. But it’s not. Although there is a way to shift the risk/reward ratio in our favor.

After doing innovation wrong, learning, and doing it less wrong, I have found one thing that significantly and universally reduces the risk/reward ratio. What is it?

Know you’re working on the right problem.

Work on the right problem? Are you kidding? This is the magic advice? This is the best you’ve got? Yes.

If you think it’s easy to know you’re working on the right problem, you’ve never truly known you were working on the right problem, because this type of knowing is big medicine. Innovation is all about solving a special type of problem, problems caused by fundamental conflicts and contradictions, things that others don’t know exist, don’t know how to describe, or define, let alone know how to eliminate. I’m talking about conflicts and contradictions in the physics sense – where something must be hot and cold at the same time, something must be big while being small, black while white, hard one instant, and soft the next. Solve one of those babies, and you’ve innovated yourself a blockbuster product.

In order to know you’re working on the right problem (conflict or contradiction), the product is analyzed in the physics sense. What’s happening, why, where, when, how? It’s the rule (not the exception) that no one knows what’s really going on, they only think they do. Since the physics are unknown, a hypothesis of the physics behind the conflict/contradiction must be conjured and tested. The hypothesis must be tests analytically or in the lab. All this is done to define the problem, not solve it. To conjure correctly, a radical and seemingly inefficient activity must be undertaken. Engineers must sit at their desk and think about physics. This type of thinking is difficult enough on its own and almost impossible when project managers are screaming at them to get off their butts and fix the problem. As we know, thinking is not considered progress, only activity is.

After conjuring the hypothesis, it’s tested to prove or disprove. If dis-proven, back to the desk for more thinking. If proven, the conflict/contradiction behind the problem is defined, and you know you’re working on the right problem. You have not solved it, you’ve only convinced yourself you’re working on the right one. Now the problem can be solved.

Believe it or not, solving is the easy part. It’s easy because the physics of the problem are now known and have been verified in the lab. We engineers can solve physics problems once they’re defined because we know the rules. If we don’t know the physics rules off the top of our heads, our friends do. And for those tricky times, we can go to the internet and ask Google.

I know all this sounds strange. That’s okay, it is. But it’s also true. Give your engineers the tools, time and training to identify the problems, conflicts, and contradictions and innovation will follow. Remember the engineering paradox, sometimes slower is faster. And what about those tools for innovation? I’ll save them for another time.

I can’t believe everyone isn’t doing Design for Assembly (DFA), especially in these tough economic times. It’s almost like CEOs really don’t want to grow stock price. DFA, where the product design is changed to reduce the cost of putting things together, routinely achieves savings of 20-50% in material cost, and the same for labor cost. And the beauty of the material savings is that it falls right to the bottom line. For a product that costs $1000 with 60% material cost ($600) and 10% profit margin ($100), a 10% reduction in material cost increases bottom line contribution by 60% (from $100 to $160). That sounds pretty good to me. But, remember, DFA can reduce material cost by 50%. Do that math and, when you get up off the floor, read on.

Unfortunately for DFA, the savings are a problem – they’re too big to be believed. That’s right, I said too big. Here’s how it goes. An engineer (usually an older one who doesn’t mind getting fired, or a young one who doesn’t know any better) brings up DFA in a meeting and says something like, “There’s this crazy guy on the web writing about DFA who says we can design out 20-50% of our material cost. That’s just what we need.” A pained silence floods the room. One of the leaders says something like, “Listen, kid, the only part you got right is calling that guy crazy. We’re the world leaders in our field. Don’t you think we would have done that already if it was possible? We struggle to take out 2-3% material cost per year. Don’t talk about 20-50% because is not possible.” DFA is down for the count.

Also unfortunate is the name – DFA. You’ve got to admit DFA doesn’t roll off the tongue like six sigma which also happens to sound like sex sigma, where DFA does not. I think we should follow the lean sigma trend and glom some letters onto DFA so it can ride the coat tails of the better known methodologies. Here are some letters that could help:

Lean DFA; DFA Lean; Six Sigma DFA; Six DFA Sigma (this one doesn’t work for me); Lean DFA Sigma

Its pedigree is also a problem – it’s not from Toyota, so it can’t be worth a damn. Maybe we should make up a story that Deming brought it to Japan because no one in the west would listen to him, and it’s the real secret behind Toyota’s success. Or, we can call it Toyota DFA. That may work.

Though there is some truth to the previous paragraphs, the main reason no one is doing DFA is simple:

No one is asking the design community to do DFA.

Here is the rationalization: The design community is busy and behind schedule (late product launches). If we bother them with DFA, they may rebel and the product will never launch. If we leave them alone and cross our fingers, maybe things will be all right. That is a decision made in fear, which, by definition, is a mistake.

The design community needs greatness thrust upon them. It’s the only way.

Just as the manufacturing community was given no choice about doing six sigma and lean, so should the design community be given no choice about doing DFA.

No way around it, the first DFA effort is a leap of faith. The only way to get it off the ground is for a leader in the organization to stand up and say “I want to do DFA.” and then rally the troops to make it happen.

I urge you to think about DFA in the same light as six sigma or lean: If your company had a lean or six sigma project that would save you 20-50% on your product cost, would you do it? I think so.

Who in your organization is going to stand up and make it happen?

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.

In a previous post I defined the term brand-damaging threshold and said I’d talk about how to improve product robustness. So, here goes.

Every company is at a different stage in their formalized product robustness efforts, so it’s challenging to talk meaningfully to everyone. But there are two especially meaningful principles that have served me well through the years.

I had the privilege of working with Don Clausing – Total Quality Design, The House of Quality, Enhanced QFD, and Robust Quality. I vividly remember the conversation where Don shared one of his secrets. As we watched a robustness test run, Don, in his terse way, barked out a guiding principle of improving product robustness. He said:

“Improve robustness at the expense of predicting it.”

I asked Don what the hell he meant (he liked to make his students work for it), and after some prodding, he went on to explain why it’s so important. He said people spend far too much time running tests to predict robustness and then spend even more time calculating mean time between failures (MTBF). If that’s not enough, then they spend time arguing about MTBFs and the confidence intervals. He said companies should dedicate all their time and energy improving robustness. “That’s what matters to the customer,” he said. And then he continued with something like: “Predicting robustness is worse than a simple waste of time.” (He wasn’t that polite.) But I still didn’t get it. What’s the big deal about predicting robustness? Read the rest of this entry »

Successful Design For Assembly

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 and to meet demand without adding assembly workers. In a growing market, a company also wants to reduce the floor space required to meet demand without building another factory. 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 »