Archive for cost reduction

Cool free stuff!

Posted in Creativity, Manufacturing Improvement, Uncategorized with tags , , , , on April 2, 2014 by manufacturingtraining

In many of our courses we teach people about the many free references and other information available on the Internet for use in reliability predictions, FMEA preparation, product design, cost estimation, and other areas in which we teach and consult.   We’re including a partial list of these free resources on the ManufacturingTraining blog for your easy reference.   There will be more of our favorites here on the blog, so check back often (or better yet, hit the RSS button to subscribe).

Electronic Equipment Reliability Data.   MIL-HDBK-217F has been the “go to” source for electrical and electronic equipment reliability data for decades (I first learned about it when preparing reliability predictions for Honeywell’s military targeting systems in the 1970s).   It’s a comprehensive failure rate source, and perhaps just as significantly, it includes environmental modifiers to tailor a prediction to your system’s operating environment.   MIL-HDBK-217 also includes directions for performing an electronic equipment reliability prediction.   You can download a free copy of MIL-HDBK-217F here.

217

Galvanic Corrosion Prevention.   Corrosion is an expensive problem, and its annual cost has been estimated at $270 billion dollars in the US alone.   That’s a whopping $1,000 for every man, woman, and child in the United States!   One of the principal contributors to corrosion is galvanic corrosion, which can occur if the wrong metals are in intimate contact.   If you’re concerned about potential reactions between metals in your designs, MIL-STD-889B is the US standard for defining what’s acceptable and what’s not.   You can download a free copy of MIL-STD-889B here.

889

Procedures for Performing an FMEA.   Failure Modes and Effects Analysis is a superior tool for alerting the design team of potential failure modes during the development process.   We teach an FMEA course that receives high marks from all who have taken it, and one of the topics we address is how FMEA was first developed by the US Department of Defense just after World War II for use in new program development.   MIL-STD-1629 has been superceded by commercial FMEA standards, but it is still the defining document for performing FMEAs, and you can still download a copy for free.   It’s available for free here.

1629

System Safety Procedures.   There are a family of system safety analyses similar in concept to Failure Modes and Effects Analysis but focused exclusively on safety issues. These include Preliminary Hazard Analyses, Subsystem Hazard Analyses, System Hazard Analyses, Common Mode Analyses, and Operating Hazard Analyses.   MIL-STD-882D addresses all of these and more.   You can download a free copy of MIL-STD-882D here.

882D

Gantt Chart Excel Software.   H.L. Gantt, an industrial engineer, developed the Gantt chart scheduling approach that bears his name during World War I to keep track of large projects.   He hit a home run with this one.   It’s the “go to” approach used throughout the world, and it makes it very easy to rapidly determine if a program is on schedule.     I don’t much care for Microsoft Project, as its Gantt charts tend to be tough to manage and nearly impossible to portray in a Word or PowerPoint file.   I’ve found Excel to be much easier to use, and to import into a Word document or PowerPoint presentation.   You can download a free Excel template for Gantt charts here.

GanttExcel

That’s it for now.   Keep an eye on this blog, as we’ll be adding more free stuff in future posts.

 

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Statistical Tolerance Analysis

Posted in Creativity, Manufacturing Improvement with tags , , , , , on June 17, 2013 by manufacturingtraining

Dimensional tolerances specify allowed variability around nominal dimensions.   We assign tolerances to assure component interchangeability while meeting performance and producibility requirements.  In general, as tolerances become smaller manufacturing costs become greater.  The challenge becomes finding ways to increase tolerances without sacrificing product performance and overall assembly conformance.  Statistical tolerance analysis provides a proven approach for relaxing tolerances and reducing cost.

Before we dive into how to use statistical tolerance analysis, let’s first consider how we usually assign tolerances.  Tolerances should be based on manufacturing process capabilities and requirements in the areas of component interchangeability, assembly dimensions, and product performance.  In many cases, though, tolerances are based on an organization’s past tolerance practices, standardized tolerance assignment tables, or misguided attempts to improve quality by specifying needlessly-stringent tolerances.  These latter approaches are not good, they often induce fit and performance issues, and organizations that use them often leave money on the table.

There are two approaches to tolerance assignment – worst case tolerance analysis and statistical tolerance analysis.

In the worst case approach, we analyze tolerances assuming components will be at their worst case conditions.  This seemingly innocuous assumption has several deleterious effects.  It requires larger than necessary assembly tolerances if we simply stack the worst case tolerances.   On the other hand, if we start with the required assembly tolerance and use it to determine component tolerances, the worst case tolerance analysis approach forces us to make the component tolerances very small. Here’s why this happens:   The rule for assembly tolerance determination using the worst case approach is:

Tassy = ΣTi

where

Tassy = assembly tolerance

Ti = individual component tolerances

The worst case tolerance analysis and assignment approach assumes that the components will be at their worst case dimensions; i.e., each component will be at the extreme edge of its tolerance limits.  The good news is that this is not a realistic assumption.  It is overly conservative.

Here’s more good news:  Component dimensions will most likely be normally distributed between the component’s upper and lower tolerance bounds, and the probability of actually being at the tolerance limits is low.   The likelihood of all of the components in an assembly being at their upper and lower limits is even lower.  The most likely case is that individual component dimensions will hover around their nominal values.  This reasonable assumption underlies the statistical tolerance analysis approach.

We can use statistical tolerance analysis to our advantage in three ways:

  • If we start with component tolerances, we can assign a tighter assembly tolerance.
  • If we start with the assembly tolerance, we can increase component tolerances.
  • We can use combinations of the above two approaches to provide tighter assembly tolerances than we would use with the worst case tolerance analysis approach and to selectively relax component tolerances.

Statistical tolerance analysis uses a root sum square approach to develop assembly tolerances based on component tolerances.   In the worst case tolerance analysis approach discussed above, we simply added all of the component tolerances to determine the assembly tolerance.  In the statistical tolerance analysis approach, we find the assembly tolerance based on the following equation:

Tassy = (ΣTi2)(1/2)

Using the above formula is straightforward.  We simply square each component tolerance, take the sum of these squares, and then find the square root of the summed squares to determine our assembly tolerance.

Sometimes it is difficult to understand why the root sum square approach is appropriate.   We can think of this along the same lines as the Pythagorean theorem, in which the distance along the diagonal of a right triangle is equal to the square root of the sum of the squares of the triangle’s sides.  Or we can think of it as distance from an aim point.  If we have an inch of lateral dispersion and an inch of horizontal dispersion, the total dispersion is 1.414 inches as we see below:

STA-2

To continue our discussion on statistical tolerance analysis, consider this simple assembly with three parts, each with a tolerance of ±0.002 inch:

STA-1

The worst case assembly tolerance for the above design is the sum of all of the component tolerances, or ±0.006 inch.

Using the statistical tolerance analysis approach yields an assembly tolerance based on the root sum square of the component tolerances.  It is (0.0022 + 0.0022 + 0.0022)(1/2), or 0.0035 inch.  Note that the statistically-derived tolerance is 42% smaller than the worst case tolerance.   That’s a very significant decrease from the 0.006 inch worst case derived tolerance.

Based on the above, we can assign a tighter assembly tolerance while keeping the existing component tolerances.  Or, we can the stick with the worst case assembly tolerance (assuming this is an acceptable assembly tolerance) and relax the component tolerances.   In fact, this is why we usually use the statistical tolerance analysis approach – for a given assembly tolerance, it allows us to increase the component tolerances (thereby lowering manufacturing costs).

Let’s continue with the above example to see how we can do this.   Suppose we increase the tolerance of each component by 50% so that the component tolerances go from 0.002 inch to 0.003 inch.   Calculating the statistically-derived tolerances in this case results in an assembly tolerance of 0.0052 inch, which is still below the 0.006 inch worst case assembly tolerance.   This is very significant:  We increased component tolerance 50% and still came in with an assembly tolerance less that the worst case assembly tolerance.  We can even double one of the above component’s tolerances to 0.004 inch while increasing the other two by 50% and still lie within the worst case assembly tolerance.  In this case, the statistically-derived assembly tolerance would be (0.0032 + 0.0032 + 0.0042)(1/2), or 0.0058 inch. It’s this ability to use statistical tolerance analysis to increase component tolerances that is the real money maker here.

The only disadvantage to the statistical tolerance analysis approach is that there is a small chance we will violate the assembly tolerance.   An implicit assumption is that all of the components are produced using capable processes (i.e., the process capability is such that ±3σ or all parts produced lie within the tolerance limits for each part).  This really isn’t much of an assumption (whether you are using statistical tolerance analysis or worst case tolerance analysis, your processes have to be capable).  With a statistical tolerance analysis approach, we can predict that 99.73% (not 100%) of all assemblies will meet the required assembly dimension.  This relatively small predicted rejection rate (just 0.27%) is usually acceptable.  In practice, when the assembly dimension is not met we can usually address it by simply selecting different components to bring the assembly into conformance.

Drawing Tolerances and the Manufacturing Impact

Posted in Manufacturing Improvement with tags , , , , , on May 29, 2013 by manufacturingtraining

Emergency Egress SearDimensional tolerances specify allowed variability around nominal dimensions.  In general, as tolerances become smaller manufacturing costs become greater.   This isn’t always the case, but it is generally true (we’ll cover exceptions in a future blog entry).

The approach used by most organizations for assigning tolerances often offers improvement opportunities in the areas of fit, performance improvement, and cost reduction.   It makes sense to consider tolerance modifications (and in particular, tolerance relaxations) where we can do so for all of the above reasons and more.  The photo on the right, for example, shows a product that was poorly toleranced and ultimately resulted in the failure of an aircraft emergency egress system.   We’ll tell you more about it in a subsequent blog entry.

If you’re wondering if any of the above might be applicable to your design and manufacturing organization, we’d like to suggest the following questions:

  • How do we assign tolerances?
  • Do we or our suppliers have any recurring rejections we suspect are induced by needlessly-stringent tolerances?
  • Are there any areas where we or our suppliers are taking extreme measures to hold tight tolerances?
  • Have we ever experienced failures with otherwise conforming equipment?
  • Do we require drawing changes to relax the tolerance whenever we disposition nonconforming parts “use as is?”

Future Blog Entries

We’ll have a series of articles in the next several weeks addressing the pitfalls in how most organizations assign tolerances, how we can approach relaxing tolerances, how tighter tolerances can sometimes actually lower cost, the need for appropriately-targeted tolerance analysis, and how statistical process control implementation can allow increasing tolerances.

Keep an eye on the ManufacturingTraining blog for important and informative updates in each of these areas!

A Couple of Great Books

Posted in Manufacturing Improvement with tags , , , on August 25, 2012 by manufacturingtraining

I’ve recently read a couple of great books that I think should be required reading for anyone working in the manufacturing or engineering world.   One of these is Car Guys versus Bean Counters by Bob Lutz, a book I featured a few weeks ago in the California Scooter blog (it’s a blog I write for CSC Motorcycles, one of my clients).  With your permission, I’ll repeat part of that blog entry here.  The other book is The Gun, by C.J. Chivers.   I’ll get to that one a few paragraphs down.

I bought the Lutz book a few months ago when I saw it in an airport while I was on my way to Thailand to present a Manufacturing Leadership course.  Bob Lutz is a certifiable gearhead with the credentials and experience to back it up…he’s held very senior positions with Ford, BMW, Chrysler, and General Motors.  The book is mostly about GM, a company that rehired Lutz to help the company find its way again…which is another way of saying that Lutz’s new job was to conceive, develop, and make GM cars people would want.

A bit of history on this first…in the 1950s and 1960s, GM was ahead of the world in producing exciting cars.  Think 1955 Chevys, the Pontiac GTO, the Corvette, the Olds Toronado and Cadillac El Dorado, the 1959 Coupe de Ville, the SS 396 Chevelle, the El Camino, the Camaro, the Buick Riviera, and, well, you get the idea. It was the golden age for American automobiles and GM was at the top of the heap. Then the company lost its way, and the cars GM cranked out in the mid-70s and beyond were just awful.

Lutz explains that the reason GM fell from glory was not just the financial folks (the “bean counters” of the book’s title), but its pre-occupation with committee-based design efforts that bred a culture of mediocrity.  He makes a strong case for strong-willed leaders who design cars based on their instincts and a connection with the product, not what cost reduction, producibility, and all of the other “ilities” committees will approve.

The good news is that GM is on the way back, and I think you can see that in their new cars. I especially like what’s being offered by Cadillac and Chevy.   I drive a Z-06 and in my opinion there’s nothing more exciting.  It’s American made and it has the right style and sound.

The next book that I have even stronger feelings about is The Gun, by C.J. Chivers.  I was surprised that I hadn’t heard of this book before when I read a review in the New York Times.   The New York Times is about as left-leaning a rag as ever existed and it had high praise for The Gun.   I reasoned that if the leftist Bloomberg lackies liked it, there had to be something there, so I went to Amazon and bought a copy.

The Times was right, but for the wrong reasons.

My impression is that the Times guys did little more than read the press release for The Gun, as all they really mentioned in their review was that the book told the story of the AK-47’s proliferation after the Soviet empire disintegrated.  The AK-47, of course, is the Kalashnikov-designed assault rifle that has become an iconic communist/terrorist/insurgency weapon.  The Gun makes the point that after the Soviet empire fell all eyes were on securing the Soviet nuclear arsenal, yet no Soviet nuclear weapon had ever killed anyone.  AK-47 rifles, however, were all over the world, and they had killed many people.   The production quantities were such that the Soviets could have issued 700 AK-47s to each of their soldiers.  They didn’t do that for obvious reasons…instead, the rifles proliferated and wound up in the hands of terrorists and other low-lifes all over the world.

While the above is interesting, it’s not what The Gun is all about.   The book should perhaps have been titled The Guns, because what it focuses on are the differences between the AK-47 and the US weapon designed in response to it…the M-16.   That, folks, is a fascinating story, and Chivers’ telling of it is masterful.   The producibility, reliability, and engineering tradeoffs made by Colt and Kalashnikov for each of these weapons are fascinating.  Colt focused on accuracy and precision, which made the early M-16s unreliable and less battle-worthy.   The AK-47 focused on reliability, low cost, easy producibility, and just enough accuracy to make the weapon deadly.   In the early Vietnam War days, there’s no question that the AK-47 was a superior rifle.   Chivers’ explanations and comparisons of these two rifles make for great reading, and we use The Gun in our failure analysis, cost reductionmanufacturing leadership, and engineering creativity courses for just that reason.

Leaving money on the table…

Posted in Manufacturing Improvement with tags , , , on April 10, 2012 by manufacturingtraining

On the subject of drawing tolerances, many organizations leave a lot of money on the table.   This is an important area from both cost reduction and quality perspectives.  Here’s a question for  you:  How does your organization assign tolerances?

Common approaches for tolerance selection include the following:

  • In some organizations, tolerances are based on the nominal dimension.  Dimensions up to 1 inch might get a tolerance of ± 0.001 inch, dimensions up to 5 inches might get a tolerance of ± 0.01 inch, and everything above 5 inches might get a tolerance of ± 0.05 inch.  This makes the designer’s work easy, but it is a poor practice.
  • In some organizations, tolerances are based on decimal places.  If the designer specifies a nominal dimension of, say, 1.000 inch (3 decimal places), the tolerance for might be ± .001 inch (all 3-decimal-place dimensions are assigned a ± .001 inch tolerance).  If the designer specifies a nominal dimension of 1.00 inch (2 decimal places), the tolerance is ± .01 inch.  The tolerances are restricted to fixed steps, and it’s not likely the steps correspond to fit, function, or process capabilities.
  • In some cases, designers assign tight tolerances to parts in an effort to improve quality.  This practice is misguided and builds unnecessary cost into the product.
  • In some cases, the designers assess how the parts fit together, what the parts have to do, and how the parts will be manufactured, and base the tolerances on these factors.

That last approach is the best approach.  Based on our observations of many organizations, though, it’s not what usually happens.

Cost Reduction Opportunities

The best point for reducing cost is during the design process.   A good approach is to include the manufacturing folks in the design process, assess the production approach as designs emerge, and identify processes and process capabilities for each part.  It’s the engineering organization’s responsibility to select dimensions and assign tolerances that will assure fit and function; it’s the manufacturing organization’s responsibility to raise a red flag where tight tolerances mandate expensive processes or a high likelihood of nonconformances.

If you didn’t do the above during the design process any you have tightly-toleranced parts in production, you can still reduce cost by targeting unnecessarily-tight tolerances.  Here’s a recommended approach:

  • Talk to your QA and manufacturing people.   They’ll be able to identify parts and dimensions that cause frequent rejections.   Where this situation exists, evaluate relaxing the tolerances.
  • Look for “use as is” dispositions on nonconforming parts (trust me on this…your manufacturing people will know where this is occurring).  If a “use as is” disposition is the acceptable, it’s likely the tolerance on the nonconforming dimension can be relaxed.
  • Talk to your purchasing folks.   They can reach out to the supplier community and ask the same kinds of questions.   This is a particularly important area to explore, because in most manufacturing organizations approximately 70% of the cost of goods sold flows through the purchasing organization.  You may not know without asking how many parts your suppliers are rejecting; all you’ll see are the costs buried in what you have to pay for the parts.   The best way to ask the question is the most direct:   What are we doing that’s driving your costs?  The suppliers know, and they’re usually eager to answer the question.

All of the above is associated with cost reduction, but that’s not the only place where inappropriately-toleranced parts create problems.  In many cases, dimensioning and tolerancing practices can induce system-level failures.    That’s another fascinating area, and we’ll address it in a future blog entry.

Would you like to know more about cost reduction opportunities you act on right now?  Consider our cost reduction training programs, or take a look at our most recent book, Cost Reduction and Optimization for Manufacturing and Industrial Companies!

Posted in Manufacturing Improvement with tags , , on April 1, 2012 by manufacturingtraining

If you work in manufacturing, I know you have been inundated with cute titles for quality and productivity improvement programs for decades:

  • Zero defects (that one made a few guys in Winter Haven wealthy)
  • TQM (does anyone use that term any more?)
  • 6σ (we are fascinated by Greek letters and martial arts belts)
  • 5 Whys (hey, why not?)
  • 5S (in both English and Japanese, no less!)
  • Lean (perhaps picking up on our anti-obesity predilection?)

And many, many more. You get the idea.

Over the last three or four decades I’ve watched all of the above with some detachment and great amusement.  Much of what’s included in these programs is the same; the titles are simply new wrappings around old ideas.  But the old ideas still make sense.  Process improvement.  Scrap reduction. Clean workplaces.  Reduced setup times.  Straight-line manufacturing.  The list goes on.  My challenge to you is this: Find something in any of the above programs that didn’t originate in basic manufacturing/industrial management concepts…concepts that go all the way back to the Industrial Revolution and Frederick Taylor.  I’d be interested in hearing your comments.

The above notwithstanding, I’d like to weigh in with a program of my own.  I’ve thought about this a lot. It’s got to be simple.  It needs a Greek letter to lend an air of the esoteric and perhaps make it sound needlessly scientific (although I promise you, it won’t be either).  It needs to offer a catchy way to package Mr. Taylor’s key concepts.  It needs to be marketable.  And it needs to be focused on improving manufacturing, quality, and profitability.

Here we go:  7 Pi.

Yep. I originally started out with 6P, but then I realized I was leaving out an important P, and P didn’t sound as cool as Pi, or ππ, as you know, is the Greek letter for P.

About now, as you’re reading this, you’re probably wondering what this is all about.  The focus here is delivery performance improvement, or getting and staying on schedule as a manufacturer.  If you’ve ever run a plant that was behind schedule, you know how tough life can be.  And if your plant is on schedule, you know that quality and profitability are going to be okay (trust me on this, I’ve seen it happen in the plants I’ve run and in the ones I’ve advised).  Staying on schedule is critical.  If you can do that, everything else falls into place.  And if you do everything you need to do to be on schedule, everything is in place.

So, here we go…the 7 Pi’s for delivery performance improvement:

  • People
  • Product
  • Process
  • Procurement
  • Productivity
  • Production Control
  • caPacity

I know, I fudged it a little on that last one, but that’s the only bit of artistic license I’ll take here.  Watch the ManufacturingTraining blog, folks, because we’re going to explore each of our 7π’s in the coming weeks!

KU Online Courses Scheduled for 2012-2013

Posted in Manufacturing Improvement with tags , , , , , on March 21, 2012 by manufacturingtraining

ManufacturingTraining and the University of Kansas have finalized the course schedule for our next series of six online Manufacturing Optimization courses:

  • Delivery Performance Improvement:  21 August 2012
  • Cost Estimation:  16 October 2012
  • Industrial Statistics:  8 January 2013
  • Quality Management:  5 March 2013
  • Root Cause Failure Analysis:  30 April 2013
  • Cost Reduction and Optimization:  25 June 2013

Each course is 3 weeks long and the University of Kansas will grant Continuing Education credit.  We’ll meet for online lectures twice each week, with interactive assignments and discussion board activities following the lectures.  We’ll be posting more information here and on the ManufacturingTraining.com website in the near future, so stay tuned for more information on this exciting new professional education opportunity!  In the meantime, if you want advance information on pre-enrolling, you can do by shooting an email to info@ManufacturingTraining.com.