Shipulski On Design

Posts Tagged ‘Engineering Capability’

Additive Manufacturing (AM) is technology/product space with ever-increasing performance and an ever-increasing collection of products. There are many different physical principles used to add material and there are a range of part sizes that can be made ranging from micrometers to tens of meters.  And there is an ever-increasing collection of materials that can be deposited from water soluble plastics to exotic metals to specialty ceramics.

But AM tools and technologies don’t deliver value on their own.  In order to deliver value, companies must deploy AM to solve problems and implement solutions.  But where to start? What to do next? And how do you know when you’ve arrived?

To help with your AM journey, below a maturity model for AM.  There are eight categories, each with descriptions of increasing levels of maturity.  To start, baseline your company in the eight categories and then, once positioned, look to the higher levels of maturity for suggestions on how to move forward.

For a more refined calibration, a formal on-site assessment is available as well as a facilitated process to create and deploy an AM build-out plan.  For information on on-site assessment and AM deployment, send me a note at mike@shipulski.com.

Execution

1. Specify AM machine – There a many types of AM machines. Learn to choose the right machine.
2. Justify AM machine – Define the problem to be solved and the benefit of solving it.
3. Budget for AM machine – Find a budget and create a line item.
4. Pay for machine –  Choose the supplier and payment method – buy it, rent to own, credit card.
5. Install machine – Choose location, provide necessary inputs and connectivity
6. Create shapes/add material – Choose the right CAD system for the job, make the parts.
7. Create support/service systems – Administer the job queue, change the consumables, maintenance.
8. Security – Create a system for CAD files and part files to move securely throughout the organization.
9. Standardize – Once the first machines are installed, converge on a small set of standard machines.
10. Teach/Train – Create training material for running AM machine and creating shapes.

Solution

1. Copy/Replace – Download a shape from the web and make a copy or replace a broken part.
2. Adapt/Improve – Add a new feature or function, change color, improve performance.
3. Create/Learn – Create something new, show your team, show your customers.
4. Sell Products/Services – Sell high volume AM-produced products for a profit. (Stretch goal.)

Volume

1. Make one part – Make one part and be done with it.
2. Make five parts – Make a small number of parts and learn support material is a challenge.
3. Make fifty parts – Make more than a handful of parts. Filament runs out, machines clog and jam.
4. Make parts with a complete manufacturing system – This topic deserves a post all its own.

Complexity

1. Make a single piece – Make one part.
2. Make a multi-part assembly – Make multiple parts and fasten them together.
3. Make a building block assembly – Make blocks that join to form an assembly larger than the build area.
4. Consolidate – Redesign an assembly to consolidate multiple parts into fewer.
5. Simplify – Redesign the consolidated assembly to eliminate features and simplify it.

Material

1. Plastic – Low temperature plastic, multicolor plastics, high performance plastics.
2. Metal – Low melting temperature with low conductivity, higher melting temps, higher conductivity
3. Ceramics – common materials with standard binders, crazy materials with crazy binders.
4. Hybrid – multiple types of plastics in a single part, multiple metals in one part, custom metal alloy.
5. Incompatible materials – Think oil and water.

Scale

1. 50 mm – Not too large and not too small. Fits the build area of medium-sized machine.
2. 500 mm – Larger than the build area of medium-sized machine.
3. 5 m – Requires a large machine or joining multiple parts in a building block way.
4. 0.5 mm – Tiny parts, tiny machines, superior motion control and material control.

Organizational Breadth

1. Individuals – Early adopters operate in isolation.
2. Teams – Teams of early adopters gang together and spread the word.
3. Functions – Functional groups band together to advance their trade.
4. Supply Chain – Suppliers and customers work together to solve joint problems.
5. Business Units – Whole business units spread AM throughout the body of their work.
6. Company – Whole company adopts AM and deploys it broadly.

Strategic Importance

1. Novelty – Early adopters think it’s cool and learn what AM can do.
2. Point Solution – AM solves an important problem.
3. Speed – AM speeds up the work.
4. Profitability – AM improves profitability.
5. Initiative – AM becomes an initiative and benefits are broadly multiplied.
6. Competitive Advantage – AM generates growth and delivers on Vital Business Objectives (VBOs).

Image credit – Cheryl

The organizational capability of a company defines its ability to get things done.  If you can’t pull it off, you have an organizational capability problem, or so the traditional thinking goes.

If you don’t have enough people to do the work, and the work is not new, that’s not a capability gap, that’s an organizational capacity gap. Capacity gaps are filled in straightforward ways. 1.) You can hire more people like the ones who do the work today and train them with the people you already have. Or for machines – buy more of the old machines you know and love.  2.) Map the work processes and design out the waste.  Find the piles of paper or long queues and the bottleneck will be right in front.  Figure out how to get more work through bottleneck.  Professional tip – ignore everything but the bottleneck because fixing a non-bottleneck will only make you tired and sweaty and won’t increase throughput.  3.) Move people and machines from the work to create a larger shortfall.  If no one complains, it wasn’t a problem and don’t fix it.  If the complaints skyrocket, use the noise to justify the first or second option.  And don’t let your ego get in the way – bigger teams aren’t better, they’re just bigger.

If your company systematically piles too work on everyone’s plate, you don’t have an organizational capability problem, you have a leadership problem.

If you’re asked to put together a future state organization and define its new capabilities, you don’t have an organizational capability gap.  A capability gap exists only when there’s a business objective that must be satisfied, and a paper exercise to create a future state organization is not a business objective.  Before starting the work, ask for the company’s growth objectives and an explanation of the new work your team will have to do to achieve those objectives.  And ask how much money has been budgeted (and approved) for the future state organization and when you can make the first hire.  This will reduce the urgency of the exercise, and may stop it altogether. And everyone will know there’s no  “organizational capability gap.”

If you’re asked to put together a project plan (with timeline and budget) to create a new technology and present the plan to the CEO next week, you have an organizational capability gap.  If there’s a shortfall in the company’s growth numbers and the VP of business development calls you at home and tells you to put together a plan to create a new market in a new country and present it to her tomorrow, you have an organizational capability gap.  If the VP of sales takes you to a fancy restaurant and asks you to make a napkin sketch of your plan to sell the new product through a new channel, you have an organizational capability gap.

Real organizational capability gaps are rare.  Unless there’s a change, there can be no organizational capability gap.  There can be no gap without a new business deliverable, new technology, new partnership, new product, new market, or new channel.  And without a timeline and an approved budget, I don’t know what you have, but you don’t have organizational capability gap.

Image credit – Jehane

Even after playing lots of tricks to reduce its energy consumption, our brains still consume a large portion of the calories we eat.  Like today’s smartphones it’s computing power is too big for it’s battery so its algorithms conserve every chance they get.  One of its go-to conservation strategies is to make mental models.  The models capture the essence of a system’s behavior without the overhead of retaining all the details of the system.

And as the brain goes about its day it tries to fit what it sees to its portfolio of mental models.  Because mental models are so efficient, to save juice the brain is pretty loose with how it decides if a model fits the situation.  In fact the brain doesn’t do a best fit, it does a first fit. Once a model is close enough, the model is applied, even if there’s a better one in the archives.

Overall, the brain does a good job.  It looks at a system and matches it with a model of a similar system it experienced in the past.  But behind it all the brain is making a dangerous assumption.  The brain assumes all systems are static.  And that makes for mental models that are static.  And because all systems change over time (the only thing we can argue about is the rate of change) the brain’s mental models are always out of date.

Over the years your brain as made a mental model of how your business works – customers do this, competitors do that, and markets do the other.  But by definition that mental model is outdated.  There needs to be a forcing function that causes us to refute our mental models so we can continually refine them. [A good mantra could be – all mental models are out of fashion until proven otherwise.]  But worse than not having a mechanism to refute them, we have a formal business process the demands we converge on our tired mental models year-on-year.  And the name of that wicked process – strategic planning.

It goes something like this. Take a little time from your regular job (though you still have to do all that regular work) and figure out how you’re going to grow your business by a large (and arbitrary) percentage. The plan must be achievable (no pie in the sky stuff), it should be tightly defined (even though everyone knows things are dynamic and the plan will change throughout the year), you must do everything you did last year and more and you have fewer resources than last year.  Any brain in it’s right will fit the old models to the new normal and put the plan together in the (insufficient) time allotted. The planning process reinforces the re-use of old models.

Because the brain believes everything is static, it’s thinking goes like this – a plan based on anything other than the tried-and-true mental models cannot have certainty or predictability in time or resources.  And it’s thinking is right, in part.  But because all mental models are out of date, even plans based on existing models don’t have certainty and predictability.  And that’s where the wheels fall off.

To inject a bit more reality into strategic planning, ignore the tired old information streams that reinforce existing thinking and find new ones that provide information that contradicts existing mental models.  Dig deeply into the mismatch between the new information and the old mental models.  What is behind the difference?  Is the difference limited to a specific region or product line? Is the mismatch new or has it always been there?  The intent of this knee-deep dissection is not to invalidate the old models but to test and refine.

There is infinite detail in the world.  Take a look at a tree and there’s a trunk and canopy. Look at the canopy and see the leaves. Look deeper to see a leaf and its veins.  In order to effectively handle all this detail our brains create patterns and abstractions to reduce the amount of information needed to make it through the day.

In the case of the tree, the word “tree” is used to capture the whole thing – roots and all.  And at a higher level, “tree” can represent almost any type of tree at almost any stage in its life.  The abstraction is powerful because it reduces the complexity, as long as everyone’s clear which tree is which.

The message is this. Our brain takes shortcuts with its chunking of the world into mental models that go out style. And our brain uses different levels of abstraction for the same word to mean different things. Care must be taken to overtly question our mental models and overtly question the level of abstraction used when statements of facts are made.

Knowing what isn’t said is almost important as what is said. To maintain this level of clarity requires calm, centered awareness which today’s pace makes difficult.

There’s no pure cure for the syndrome. The best we can do is to be well-rested and aware. And to do that requires professional confidence and personal disciple.

Slowing down just a bit can be faster, and testing the assumptions behind our business models can be even faster.  Last year’s mental models and business models should be thought of as guilty until proven relevant.  And for that you need to make the time to think.

In today’s world we confuse activity with progress. But really, in today’s dynamic world thinking is progress.

Image credit – eyeliam.

How long will it take? The short answer – same as last time. How long do we want it to take? That’s a different question altogether.

If the last project took a year, so will the next one. Even if you want it to take six months, it will take a year. Unless, there’s a good reason it will be different. (And no, the simple fact you want it to take six months is not a good enough reason in itself.)

Some good reasons it will take longer than last time: more work, more newness, less reuse, more risk, and fewer resources. Some good reasons why it will go faster: less work, less newness, more reuse, less risk, more resources. Seems pretty tight and buttoned-up, but things aren’t that straight forward.

With resources, the core resources are usually under control.  It’s the shared resources that are the problem. With resources under their control (core resources) project teams typically do a good job – assign dedicated resources and get out of the way. Shared resources are named that way because they support multiple projects, and this is the problem. Shared resources create coupling among projects, and when one project runs long, resource backlogs ripple through the other projects. And it gets worse. The projects backlogged by the initial ripple splash back and reflect ripples back at each other. Understand the shared resources, and you understand a fundamental dynamic of all your projects.

Plain and simple – work content governs project timelines. And going forward I propose we never again ask “How long will it take?” and instead ask “How is the work content different than last time?” To estimate how long it will take, set up a short face-to-face meeting with the person who did it last time, and ask them how long it will take. Write it down, because that’s the best estimate of how long it will take.

It may be the best estimate, but it may not be a good one. The problem is uncertainty around newness. Two important questions to calibrate uncertainty: 1) How big of a stretch are you asking for? and 2) How much do you know about how you’ll get there? The first question drives focus, but it’s not always a good predictor of uncertainty.  Even seemingly small stretches can create huge problems. (A project that requires a 0.01% increase in the speed of light will be a long one.) What matters is if you can get there.

To start, use your best judgment to estimate the uncertainty, but as quickly as you can, put together a rude and crude experimental plan to reduce it. As fast as you can execute the experimental plan, and let the test results tell you if you can get there. If you can’t get there on the bench, you can’t get there, and you should work on a different project until you can.

The best way to understand how long a project will take is to understand the work content. And the most important work content to understand is the new work content. Choose several of your best people and ask them to run fast and focused experiments around the newness. Then, instead of asking them how long it will take, look at the test results and decide for yourself.

When engineers see a big opportunity, we want desperately to move the company in the direction of our thinking, but find it difficult to change the behavior of others. Our method of choice is usually a full frontal assault, explaining to anyone that will listen the opportunity as we understand it. Our approach is straightforward and ineffective. Our descriptions are long, convoluted, complicated, we use confusing technical language all our own, and omit much needed context that we expect others should know. The result – no one understands what we’re talking about and we don’t get the behavior we’re looking for (immediate company realignment with what we know to be true).  Then, we get frustrated and shut down – opportunity lost.

To change the behavior of others, we must first change our own. As engineers we see problems which, when solved, result in opportunity. And if we’re to be successful, we must go back to the problem domain and set things straight. Here’s a sequence of new behaviors we as engineers can take to improve our chances of changing the behavior of others:

Step 1. Create a block diagram of the physical system using simple nouns (blocks) and verbs (arrows). Blue arrows are good (useful actions) and red arrows are bad (harmful actions). Here’s a link to a PowerPoint file with a live template to create your own.

Step 2. Reduce the system block diagram down to its essence to create a distilled block diagram of the problem, showing only the system elements (blocks) with the problem (red arrow).For a live template, see the second page of the linked file. [Note – if there are two red arrows in the system block diagram, there are two problems which must be solved separately. Break them into two and solve the first one first. For an example, see page three of the linked file.]

Step 3. Create a hand sketch, or cartoon, showing the two system elements (blocks) of the distilled block diagram from step 2. Zoom in so only the two elements are visible, and denote where they touch (where the problem is), in red. For an example, see page four of the linked file.

Step 4. Now that you understand the real problem, use Google to learn how others have solved it.

Step 5. Choose one of Google’s most promising solutions and prototype it. (Don’t ask anyone, just build it.)

Step 6. Show the results to your engineering friends. If the problem is solved, it’s now clear how the opportunity can be realized. (There’s a big difference between a crazy engineer with a radically new market opportunity and a crazy engineer with test results demonstrating a new technology that will create a whole new market.)

Step 7. If the problem is not solved, or you solved the wrong problem, go back to step 1 and refine the problem

With step 1 you’ll find you really don’t understand the physical system, you don’t know which elements of the system have the problem, and you can’t figure out what the problem is. (I’ve created complicated system block diagrams only to realize there was no problem.)

With step 2, you’ll continue to struggle to zoom in on the problem. And, likely, as you try to define the problem, you’ll go back to step 1 and refine the system block diagram. Then, you’ll struggle to distill the problem down to two blocks (system elements). You’ll want to retain the complexity (many blocks) because you still don’t understand the real problem.

If you’ve done step 2 correctly, step 3 is easy, though you’ll still want to complicate the cartoon (too many system elements) and you won’t zoom in close enough.

Step 4 is powerful. Google can quickly and inexpensively help you see how the world has already solved your problem.

Step 5 is more powerful still.

Step 6 shows Marketing what the future product will do so they can figure out how to create the new market.

Step 7 is how problems are really solved and opportunities actually realized.

When you solve the real problem, you create real opportunities.

You might be a superhero if…

• Using just dirt, rocks, and sticks, you can bring to life a product that makes life better for society.

• Using just your mind, you can radically simplify the factory by changing the product itself.

• Using your analytical skills, you can increase product function in ways that reinvent your industry.

• Using your knowledge of physics, you can solve a longstanding manufacturing problem by making a product insensitive to variation.

• Using your knowledge of Design for Manufacturing and Assembly, you can reduce product cost by 50%.

• Using your knowledge of materials, you can eliminate a fundamental factory bottleneck by changing what the product is made from.

• Using your curiosity and creativity, you can invent and commercialize a product that creates a new industry.

• Using your superpowers, you think you can fix a country’s economy one company at a time.

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 »