Shipulski On Design

Posts Tagged ‘Downstream Savings’

I hear it’s a good idea to move manufacturing work back to the US.

Before getting into what it would take to move manufacturing work back to the US, I think it’s important to understand why manufacturing companies moved their work out of the US.  Simply put, companies moved their work out of the US because their accounting systems told them they would make more money if they made their products in countries with lower labor costs. And now that labor costs have increased in these no longer “low-cost countries”, those same accounting systems think there’s more money to be made by bringing manufacturing back to the US.

At a low level of abstraction, manufacturing, as a word, is about making discrete parts like gears, fenders, and tires using machines like gear shapers, stamping machines, and injection molding machines.  The cost of manufacturing the parts is defined by the cost of the raw material, the cost of the machines, the cost of energy to power the machines, the cost of the factory, and the cost of the people to run the machines. And then there’s assembly, which, as a word, is about putting those discrete parts together to make a higher-level product.  Where manufacturing makes the gears, fenders, and tires, assembly puts them together to make a car.  And the cost of assembly is defined by the cost of the factory, the cost of fixtures, and the cost of the people to assemble the parts into the product.  And the cost of the finished product is the sum of the cost of making the parts (manufacturing) and the cost of putting them together (assembly).

It seems pretty straightforward to make more money by moving the manufacturing of discrete parts back to the US.  All that has to happen is to find some empty factory space, buy new machines, land them in the factory, hire the people to run the machines, train them, source the raw material, hire the manufacturing experts to reinvent/automate the manufacturing process to reduce cycle time and reduce labor time and then give them six months to a year to do that deep manufacturing work.  That’s quite a list because there’s little factory space available that’s ready to receive machines, the machines cost money, there are few people available to do manufacturing work, the cost to train them is high (and it takes time and there are no trained trainers).  But the real hurdles are the deep work required to reinvent/automate the process and the lack of manufacturing experts to do that work.  The question you should ask is – Why does the manufacturing process have to be reinvented/automated?

There’s a dirty little secret baked into the accounting systems’ calculations.  The cost accounting says there can be no increased profit without reducing the time to make the parts and reducing the labor needed to make them.  If the work is moved from country A to country B and the costs (cycle time, labor hours, labor rate) remain constant, the profit remains constant.  Simply moving from country A to country B does nothing.  Without the deep manufacturing work, profits don’t increase.  And if your country doesn’t have the people with the right expertise, that deep manufacturing work cannot happen.

And the picture is similar for moving assembly work back to the US.  All that has to happen is to find empty factory space, hire and train people to do the assembly work, reroute the supply chains to the new factory, redesign the product so it can be assembled with an automated assembly line, hire/train the people to redesign the product so it can be assembled in an automated way, design the new automated assembly process, build it, test it, hire/train the automated assembly experts to do that work, hire the people to support and run the automated assembly line, and pay for the multi-million-dollar automated assembly line.  And the problems are similar.  There’s not a lot of world-class factory space, there are few people available to run the automated assembly line, and the cost of the automated assembly line is significant.  But the real problems are the lack of experts to redesign the product for automated assembly and the lack of expertise to design, build, and validate the assembly line.  And here are the questions you should ask – Why do we need to automate the assembly process and why does the product have to be redesigned to do that?

It’s that dirty little secret rearing its ugly head again.  The cost accounting says there can be no increased profit without reducing the labor to assemble the parts.  make them.  If the work is moved from country A to country B and the assembly costs (labor hours, labor rate) remain constant, the profit remains constant.  Simply moving from country A to country B does nothing.  Without deep design work (design for automated assembly) and ultra-deep automated assembly work, profits don’t increase.  And if your country doesn’t have the people with the right expertise, that deep design and automated assembly work cannot happen.

If your company doesn’t have the time, money, and capability to reinvent/automate manufacturing processes, it’s a bad idea to move manufacturing work back to the US.  It simply won’t work.  Instead, find experts who can help you develop/secure the capability to reinvent/automate manufacturing processes to reduce the cost of manufacturing.

If your company doesn’t have the time, money, and capability to design products for automated assembly and to design, build, and validated automated assembly systems, it’s a bad idea to move assembly work back to the US. It, too, simply won’t work.  Instead, partner with experts who know how to do that work so you can reduce the cost of assembly.

With inflation on the rise and sales on the decline, the time to reduce costs is now.

But before you can design out the cost you’ve got to know where it is.  And the best way to do that is to create a Pareto chart that defines product cost for each subassembly, with the highest cost subassemblies on the left and the lowest cost on the right.  Here’s a pro tip – Ignore the subassemblies on the right.

Use your costed Bill of Materials (BOMs) to create the Paretos.  You’ll be told that the BOMs are wrong (and they are), but they are right enough to learn where the cost is.

For each of the highest-cost subassemblies, create a lower-level Pareto chat that sorts the cost of each piece-part from highest to lowest.  The pro tip applies here, too – Ignore the parts on the right.

Because the design community designed in the cost, they are the ones who must design it out.  And to help them prioritize the work, they should be the ones who create the Pareto charts from the BOMs.  They won’t like this idea, but tell them they are the only ones who can secure the company’s future profits and buy them lots of pizza.

And when someone demands you reduce labor costs, don’t fall for it.  Labor cost is about 5% of the product cost, so reducing it by half doesn’t get you much.  Instead, make a Pareto chart of part count by subassembly.  Focus the design effort on reducing the part count of subassemblies on the left.  Pro tip – Ignore the subassemblies on the right.  The labor time to assemble parts that you design out is zero, so when demand returns, you’ll be able to pump out more products without growing the footprint of the factory.  But, more importantly, the cost of the parts you design out is also zero.  Designing out the parts is the best way to reduce product costs.

Pro tip – Set a cost reduction goal of 35%.  And when they complain, increase it to 40%.

In parallel to the design work to reduce part count and costs, design the test fixtures and test protocols you’ll use to make sure the new, lower-cost design outperforms the existing design.  Certainly, with fewer parts, the new one will be more reliable.  Pro tip – As soon as you can, test the existing design using the new protocols because the only way to know if the new one is better is to measure it against the test results of the old one.

And here’s the last pro tip – Start now.

Image credit — aisletwentytwo

For systems with high levels of complexity, such as organizations, business models, and cross-domain business processes, it’s characterize the current state, identify the future state, and figure out how to close the gap. That’s how I was trained. Simple, elegant, and no longer fits me.

The block diagram of the current state is neat and clean. Sure, there are interactions and feedback loops but, known inputs generate known outputs. But for me there are problems with the implicit assumptions. Implicit is the notion that the block diagram correctly represents current state; that uncontrollable environmental elements won’t change the block diagram; that a new box or two and new inputs (the changes to achieve the idealized future state) won’t cause the blocks to change their transfer functions or disconnect themselves from blocks or rewire themselves to others.

But what really tipped me over was the realization that the blocks aren’t blocks at all. The blocks are people (or people with a thin wrapper of process around), and it’s the same for the inputs. When blocks turn to people, the complexity of the current state becomes clear, and it becomes clear it’s impossible to predict how the system will response when it’s prodded and cajoled toward the idealized future state. People don’t respond the same way to the same input, never mind respond predictably and repeatably to new input. When new people move to the neighborhood, the neighborhood behaves differently. People break relationships and form others at will. For me, the implicit assumptions no longer hold water.

For me the only way to know how a complex system will respond to rewiring and new input is to make small changes and watch it respond. If the changes are desirable, do more of that. If the changes are undesirable, do less.

With this approach the work moves from postulation to experimentation and causation – many small changes running parallel with the ability to discern the implications. And the investigations are done in a way to capture causality and maintain system integrity. Generate learning but don’t break the system.

It’s a low risk way to go because before wide-scale implementation the changes have already been validated. Scaling will be beneficial, safe, and somewhat quantifiable. And the stuff that didn’t work will never see the light of day.

If someone has an idea, and it’s coherent, it should be tested. And instead of arguing over whose idea will be tested, it becomes a quest to reduce the cost of the experiments and test the most ideas.

Results from a new survey show that upfront design using DFMA methods creates significant savings in operational cost — downstream savings.

An exerpt from the survey:

Sixty-eight percent of a survey group, including Fortune 400 companies, measured an increase in production throughput, and 47 percent an increase in profit per unit of factory floor space, after applying Design for Manufacture and Assembly (DFMA®) techniques to their organizations’ supply chains. A roundtable discussion of these and other results from the questionnaire, conducted by Boothroyd Dewhurst, Inc., is now available.

Respondents included Dell, Motorola, TRW Automotive, Raytheon, MDS Analytical Technologies, Magna Intier Automotive Seating and other leading North American manufacturers. Some participants also contributed to a candid roundtable discussion about applying design simplification and early costing to Lean and Six Sigma programs, along with the opportunities missed by industry in measuring financial best practices.