Lean Six Sigma Academy

Knowledge and Thinking

May 25, 2009 By Ron Pereira 18 Comments

“Knowledge is what keeps the momentum going between dreams and reality.” -Author Unknown

I am a firm believer that the “thinking” that occurs while practicing lean manufacturing and six sigma is extremely important.

I was reminded of this by, well, myself when I re-read an answer I gave Kevin Meyer a month or so ago for a blog series he’s running.

And I won’t back away from this since I truly believe that learning how to think is far more important than any single “tool” or “technique” one can learn.

But does this mean the tools and techniques of continuous improvement aren’t important? Of course not.

In fact, I’d be willing to wager that the more tools and techniques you know the better you’ll be able to think and solve problems. Allow me to explain.

Continuous Improvement Snobs

There are some folks so in love with either lean or six sigma they snub their nose at the other.

Some ‘lean purists’ will attempt to say, for example, how six sigma is no good and that they wouldn’t be caught dead using “it” as if it (six sigma) were some type of disease.

Likewise there are ‘six sigma purists’ who think lean is a second class continuous improvement citizen due to what they feel to be a simple set of tools.

With all due respect, I find both sets of people highly ignorant… but that’s just me.

Learn it all

My approach has always been to learn as much as I can about all facets of continuous improvement. You see, I could really care less if something is labeled lean, six sigma, lean six sigma, TOC, etc.

All I want to know is how to solve problems no matter the situation. And time has taught me that sometimes a so-called six sigma toolset might be of better use than a so-called lean toolset.

For example, I am not sure I’ve ever read Dr. James Womack or Dr. Jeffrey Liker (two leading ‘lean’ experts) ever write about the benefits or importance of a repeatable and reproducible measurement system.

Likewise, I am not sure I’ve ever read George Box (a leading statistical expert) write about the greatness of an andon system. But does this mean six sigma ‘belts’ should not learn about what an andon system is? Of course not.

Morale of the story

So, the morale of my rant is this. I truly believe the more you learn the more you’ll be able to think. And the more you’re able to think the better you’ll be at solving problems. And, in the end, isn’t that what continuous improvement is really about?

Do you agree with me? Have you ever heard a ‘lean’ guru bash six sigma or perhaps a ‘six sigma’ guru bash lean? What is your response when they do?

Filed Under: Lean, Six Sigma

Gemba Academy: Improvement Learning, Improved

February 14, 2009 By Ron Pereira 2 Comments

Let me start with three words: passionate, ecstatic and enthralled.

Passionate is the perfect word to describe how I feel about continuous improvement.
While ecstatic best describes my joy at being able to share some exciting news with you.
Finally, enthralled is how I feel when collaborating in a mode of creative flow.

What am I going on about?

Allow me to explain.

You see I, along with two of my favorite people in the whole wide lean world (Jon Miller of Gemba Panta Rei and Kevin Meyer of Evolving Excellence), have been extremely busy creating what we feel will become the best continuous improvement learning system available.

We’re calling it Gemba Academy.

What is Gemba Academy?

Before explaining what Gemba Academy is, let me go out on a limb and make three assumptions about you:

You are sick and tired of training presentations full of boring text and bullet points.
You are not a fan of fuzzy PowerPoint presentations converted to Flash and thrown up on the Internet.
You are not looking forward to sitting through that next 100-slide training session.

Well, let’s just say we’re with you. As such, at Gemba Academy, were committed to the following:

Crystal clear high definition videos distributed on an advanced network of servers that span the globe. So, no matter if you live in Dallas, Texas or Mombasa, Kenya you will be able to watch, interact and learn right along with us.
Content created by active practitioners that is continuously improved and added to. We will most definitely practice what we preach.
Our pricing and business model is simply unbeatable. Let’s just say some people spend more every day on fancy coffee.

Simply put, Gemba Academy is where web 2.0 meets continuous improvement learning.

Gemba Academy officially launches in March 2009. But until then, you can get sneak peak at what we’ve been up to by visiting our main site at: http://gembaacademy.com.

Filed Under: Lean, Six Sigma

How to Create Meaningful Safety Graphs

December 2, 2008 By Ron Pereira 10 Comments

Creating meaningful charts and graphs for safety related issues can be hard, not to mention confusing. It doesn’t have to be. In this article I will share a technique that may help bring some clarity to the situation.

The Wrong Approach

First, let’s assume a company tracks the number of accidents per month. For the sake of an example let’s use this totally fabricated data set:

Jan-07: 0
Feb-07: 1
Mar-07 : 0
Apr-07: 0
May-07: 0
Jun-07: 1
Jul-07: 1
Aug-07: 0
Sep-07: 0
Oct-07: 0
Nov-07: 0
Dec-07: 1
Jan-08: 0
Feb-08: 0
Mar-08 : 0
May-08: 1
Jun-08: 0
Jul-08: 0
Aug-08: 0
Sep-08: 1
Oct-08: 0
Nov-08: 0
Dec-08: 1

With this data, some may attempt to create a c chart. When they do they get something that looks sort of like this.

The upper control limit is 1.959 and the measure of central tendency is 0.304. Friends, this graph is pretty much useless. There is really no way of determining if things are getting better, worse, or staying the same.

A Better Approach

A better approach would be to somehow convert this data into a yearly rate. There are a number of formulas you can use to do this… but one I quite like is to simply count the days between accidents and multiply is by 365.

For example, the first accident (in our made up data set) happened on February 8, 2007 and the second accident occurred on June 16, 2007. This means there were 128 days between accidents.

So, our annual accident rate could be calculated as follows: (1 accident/128 days) * (365 days/year) = 2.85 accidents per year.

When we work the math for the rest of the data we see something like this.

8-Feb-07, first accident
16-Jun-07, 128 days between accidents, rate = 2.85
10-Jul-07, 24 days between accidents, rate = 15.21
17-Dec-07, 160 days between accidents, rate = 2.28
1-May-08, 136 days between accidents, rate = 2.68
6-Sep-08, 128 days between accidents, rate = 2.85
11-Dec-08, 96 days between accidents, rate = 3.80

Now, by using the rate data we can create an Individuals and Moving Range Chart (I-MR) that looks something like this.

This graph is far more powerful than the c chart. From this I-MR chart we can see that we had a blip early on but have since leveled off.

In other words things are pretty much staying the same. And since we’re talking about the safety of our workers the fact things are moving sideways – averaging around 5 accidents per year – is probably cause for strong action in most companies.

Not the Only Way

As I mentioned, this is not the only way to calculate an annual accident rate. With this said, I would be very interested to hear how your company goes about this.

Filed Under: Manufacturing, Six Sigma

How to Conduct a Measurement Systems Analysis (MSA), Part One

November 9, 2008 By Ron Pereira 4 Comments

As promised a few posts ago, I’d like to explain exactly how to go about completing a measurement systems analysis (MSA).

If the sound of this makes you want to yawn… well… stop it! It’s Monday and time to get focused (and some coffee). Seriously, this one tool has greatly benefited me over the years and I know it will you too.

The two pre-cursor articles to this one explained one such example of a variation story and how a simple MSA helped save millions of dollars in 60 minutes.

Now then, tonight I want to begin by explaining what a measurement system analysis is as well as two types of MSA that will serve you very well once you’ve mastered them.

MSA Defined (Job Interview Proof)

Right, so if you’re ever on a job interview and get asked to explain what an MSA is you would probably do well to rattle off something like this:

A Measurement System Analysis, abbreviated MSA, is a specially designed experiment that seeks to identify the components of variation in the measurement.

That would be the Wikipedia definition and I guess it sounds pretty nice… and chances are the guy interviewing won’t have a clue himself… so, yeah, this would be a great answer!

MSA Defined (Ron’s Take)

But listen, I’m a simple man. So rather than getting all text book like allow me to offer my explanation of what a MSA is. You see, anytime we measure something (e.g. the weight of a part) we’re actually dealing with two types of variation.

The variation within the parts/process we’re studying (P)
The variation within the measurement system itself (M)

In other words, the total variation we’re experiencing (T) can be explained by a formula that looks something like this: T = P + M.

In a perfect world the variation due to M (measurement system) would be zero meaning all we need to do is attack and defeat the variation within the process (P) and then ride off victorious.

Sadly, many times there is so much variation with the actual measurement system we have no earthly clue how much variation is due to the actual process. Even worse, we may try and try and try to improve the process only to find out the problem wasn’t even the process… it was the dang measurement system!

And this is precisely why measurement systems analysis is so important. We must identify how much of the total variation is due to the process and how much is due to the actual measurement system.

Types of MSA

There are different types of MSA out there and the one you choose has a lot to do with the data you’re dealing with.

When dealing with variable data (data we can measure like weight, distance, etc.) a Gage R&R study will serve you well. This stands for Gage Repeatability & Reproducibility.
When dealing with attribute data (pass/fail, good/bad, etc.) an Attribute Gage study will do the trick nicely.

Up Next

Now that we know what a MSA is as well as two popular types of analysis it’s time to learn how to conduct the actual studies… and that’s precisely what we’ll discuss in the very near future!

If you have any experience, good or bad, with measurement systems analysis please share in the comments section below. Also, if you have a specific question on the topic please share that as well.

Filed Under: Six Sigma

How Do You Measure Success?

November 5, 2008 By Ron Pereira 18 Comments

I recently received the following question from Petri, a reader of LSS Academy.

The issue I wanted to contact you about was if LSSA has ever done work on measuring lean success? I am not sure if there are any tools which are used in this area, or if “Lean companies” have i.e. key KPI’s which are used to track this?

I know that there are auditing systems which measure the level of how far 5S is implemented etc, but I am interested in broader measures.

I find the topic of KPI’s with most successful companies fascinating, and was wondering if there is reference material one could learn from?

Your thoughts on this would be appreciated.

Best regards,
Petri
Finland

This is a great question and one I wanted to put some thought into. I am a believer that you must measure it to improve it. With this said, here are some of my personal thoughts on the matter.

The Wrong Measurements

First of all, I believe many companies get caught measuring the wrong things.

For example, some feel like they can measure the success of their continuous improvement initiative by tracking the number of people trained or certified.

Please don’t get me wrong, I think it’s good to measure these things. But to think that the number of people trained or certified equates to guaranteed success is a gigantic fallacy.

In fact, this type of behavior is the definition of an activity based program.

It’s about one thing: Results

The opposite of activity based programs are results driven programs whereby things like quick wins and bottom line impact rule the day.

But how can one go about measuring this? Is there a magic scorecard we can all download? Unfortunately, at least as far as I know, the answer is no.

With this said, here are some ideas I have for excellent indicators of the health and vitality of a lean or six sigma initiative.

1. Number of improvement initiatives complete (higher is better)

I’d track this monthly and count any documented (even a one page summary) improvement as an initiative.

2. Average time to complete improvement initiatives (lower is better)

I’d also track this monthly. I despise long, drawn out projects that take ages to complete. If an improvement initiative cannot be done is less than 4 months I say it’s over scoped.

Further, the reason I am such an advocate of kaizen events is the speed at which they are done. When done properly, these quick events become contagious and begin to spread throughout an organization like wild fire.

3. Number of improvement suggestions submitted (higher is better)

Tracked monthly, this metric simply allows an organization to measure how motivated the work force is to make improvements.

4. Number of improvement suggestions implemented (higher is better)

The reason most suggestion box initiatives fail is simple. The employees submit ideas and never hear back from management so they stop suggesting things! So, in order to combat this, management should make it clear how many suggestions – as well as what the suggestion was – were implemented. And for the suggestions that were not implemented a clear and honest explanation with the employee should occur.

5. Sales per Employee (higher is better)

In the end, finishing projects and offering suggestions are great… but if you are in a for profit business one thing is clear – cash is king.

We lean and six sigma bloggers can wax poetic about respecting people and all the rest of it… but if an organization is not profitable the doors will be shut… simple as that.

With this said, my favorite productivity metric is sales per employee. Of course some will think I’m advocating cutting heads in order to drive this metric up. I’m not. I am, however, interested in making sure all employees understand whether the business is making money and whether things are trending up or down.

What metrics do you use?

These are just a few ideas I have for how to measure the success of a lean of six sigma initiative. I’m sure I’ve missed a plethora of metrics so if you know of any I missed please share in the comments section below.

Filed Under: Lean, Six Sigma

Millions of Dollars Saved in 60 Minutes

October 28, 2008 By Ron Pereira 1 Comment

Last night I told you the story of a measurement system analysis gone bad. Tonight, as promised, I’ll explain exactly what the issue was and how we solved it in around 60 minutes.

The Part in Question

The plastic component in question measured approximately 4” by 2”. I’ve made a rough sketch of what it looked like (see picture).

The component was actually completely black in color but I’ve made it gray in order to point out some key characteristics.

Towards the corners of the part were two key features.

First, points “A” were a rounded black protrusion-like piece of plastic that stood up about 1/16 of an inch in three corners of the piece.

This is what the camera looked at when taking the actual measurements. The camera would first “zero itself” and then it would measure the distance of the three black protrusions from one other. From this the machine would calculate the X and Y dimensions of the part.

Next, points “B” were drilled out circles that were used the hold the part into the final product during assembly. These circles were ignored during the measurement process.

30 Minutes of Brainstorming

After we failed the MSA we all sat around a table and talked about what the issue could be. We felt sure that the actual measurement system was probably OK and that the problem had more to do with the measuring process itself.

So we started throwing out ideas… everything from the fixtures we used to the way the operator loaded the parts was discussed.

Then someone wondered if looking at the black protrusions was the best approach. This person’s theory was that the camera may be struggling to distinguish the difference between the black protrusion and the black frame.

After a few more minutes of pondering the idea of using the circles right next to the black protrusions was tossed out there.

The supplier’s engineer was skeptical. He didn’t think it would work. But after some old fashioned Texas hog wrestling (a figure of speech, no actual wrestling occurred) everyone agreed to give it a shot.

30 Minutes of Trystorming

Using the same 15 pieces and the same operators and a modified computer program we re-did the MSA in about 30 minutes. The difference this time was we used the drilled out circles instead of the black protrusions.

Once we had the data we re-did the analysis in our statistical software package. The result? We passed the MSA with flying colors.

Problem Solved

And that was that. Some simple experimentation coupled with both brainstorming and then trystorming solved a problem that had been plaguing this company for the better part of a year. The best thing was we started in the morning and were done by lunch time.

We were also able to proceed with our DOE and optimize the injection molding process. Soon, the quality problems we were experiencing from this supplier completely vanished. It was truly a win/win situation.

The key learning for me was that continuous improvement doesn’t have to take a long time. Problems can, and in my opinion should, be attacked and solved quickly.

It’s Time to Learn How to Conduct an MSA

Now then, in light of this story I thought it may be beneficial for me to explain exactly how to go about doing a measurement systems analysis. And that’s precisely what we’ll do over the next few posts.

So stay tuned and please forward this post to anyone who may benefit from this type of information by clicking the “Share This” button below. From there you can email the article.

Filed Under: Six Sigma

A Variation Story

October 27, 2008 By Ron Pereira 4 Comments

If you test or inspect (visual or automatic) a product of any kind I’m very confident I can show you how to save your company thousands, if not millions, of dollars (or Euros, Pounds, etc.).

How you ask? Three words. Measurement Systems Analysis, or MSA for short. But first a true story.

Back in the Day

In a past life I was working with a supplier that provided my former company with some critical plastic components for the product we produced. I’m purposely being vague to protect the innocent!

Anyhow, we were having some problems with the aforementioned critical components so I went to the supplier to see if I could help.

After some investigation and discussion we decided to run a design of experiment (DOE) on the injection molding process that produced these parts.

A Simple Question

Being the good six sigma guy I try to be, the first thing I asked the engineer I was working with was if they had ever done a measurement systems analysis of the optical inspection machine used to measure the actual dimensions of the parts.

He went on to explain how this very expensive inspection machine had just recently been calibrated to the “gold standard.” I wasn’t quite sure what the gold standard was… nor did I care how calibrated it was.

I asked him again, “Have you ever done an MSA.” He was growing frustrated with me and finally admitted… no, they had never done an MSA.

Let’s do it!

Happy to finally hear this I asked him to collect 15 of the parts we were planning to measure.

About 8 minutes later he had the 15 parts.

We grabbed a couple of operators and proceeded to conduct a variable data measurement systems analysis. It took us about 30 minutes to complete the entire study.

I threw the data into some statistical software and did the analysis.

Houston, we have a problem

Guess what? We failed the test. And I don’t mean fail like we did sort of bad. I mean fail like this fancy optical inspection machine that had recently been calibrated to the gold standard couldn’t tell the difference between a good part and bad part if its life depended on it. Good thing it wasn’t alive!

In other words, this supplier had no earthly clue what the *true* dimensions of these components were. Not good.

The Rest of the Story

Tomorrow night I’ll explain exactly how we solved the problem in less than 60 minutes. By the way, the cost of poor quality of this particular problem was resulting in millions of dollars of damage each year.

Filed Under: Six Sigma

Planting Seeds

July 13, 2008 By Ron Pereira 2 Comments

What can we learn about continuous improvement from the person Christian’s call the King of King’s, Lord of Lord’s, and The Great I AM? Lots. Let’s start in the book of Matthew.

And he spoke to them at length in parables, saying:
“A sower went out to sow.
And as he sowed, some seed fell on the path,
and birds came and ate it up.

Yep. Been there, got the t-shirt. There are lots of people who seem to take great joy in seeing others struggle. As soon as you have an idea, they have 5 reasons it won’t work hoping you will just go away.

The answer? Don’t go away. Give it a try. If you fail, so what. Try again and fail better.

Some fell on rocky ground, where it had little soil.
It sprang up at once because the soil was not deep,
and when the sun rose it was scorched,
and it withered for lack of roots.

Ah, yes. A manager reads the book Lean Thinking and decides James Womack is his ticket to stardom. So the manager sends a few of his guys (he is too busy of course) to a workshop and expects inventory turns to double the following week. It doesn’t quite work out. He’s frustrated.

He then reads The Goal and realizes that, of course, lean manufacturing stinks and that the old wily fox, Eli Goldratt, has all the answers.

The problem isn’t the “methodology” of choice. Lean works. TOC works. Six Sigma works. They all work when you work them. But don’t expect to read a book and think you’re ready to conquer Goliath. It doesn’t work that way. Toyota has been at it for 50+ years and is still fighting muda (waste) like never before.

Some seed fell among thorns, and the thorns grew up and choked it.
But some seed fell on rich soil, and produced fruit,
a hundred or sixty or thirtyfold.

The thorns will always be there. Try to avoid them is the best advice I can offer. It’s not always possible, but many times it is.

Finally, as with all aspect of life… when the right foundation is in place mighty and powerful things can result.

And as it relates to continuous improvement… laying this foundation is not easy, but it’s also well within reach. I’ll share some of my thoughts as to how we might go about this foundation development throughout this week. Stay tuned.

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Filed Under: Leadership, Lean, Six Sigma

Strategies to Sustain Operations Excellence

June 9, 2008 By Ron Pereira 12 Comments

This is an abridged version of a presentation I recently gave at a manufacturing excellence conference.

If you’d like to download the video follow this link to Google Video and click on download video.

Filed Under: Leadership, Lean, Six Sigma, Video

Entropy, Salmon, and Swimming

June 4, 2008 By Ron Pereira 9 Comments

Entropy A can of soup falls if you drop it, your car tire blows out when a nail punctures it, and eventually my barbeque grill cools down after grilling steaks, even in the hot Texas air. Why is this? Allow me to explain.

While these things are all different, they do share a common denominator. They’re all explained by the second law of thermodynamics – entropy.

Defined, entropy is a measure of the disorder or randomness in a system. Put another way, entropy helps us measure the energy that disperses or spreads out in a process, any process.

Entropy, our foe

Here is where we begin to understand how this second law of thermodynamics describes a fierce foe to those of us trying to improve processes in our factories, hospitals, and office buildings.

It would seem that entropy never seizes. It never grows tired, frustrated, or bewildered. It’s never sick or complains about a sore back. It just relentlessly presses on.

And while I realize entropy is a measure and not really a thing… I’m pretending, if you’ll allow me, that it is a thing… a relentless thing in fact.

This thing explains why my garage looks great for a week or two after our annual spring cleaning and then falls to pieces a few months later. It’s why the fifth S (sustain) is so darn hard. It’s why control charts were invented (to determine when the disorder is getting out of hand).

And its why, as I’ve stated many times before, I personally believe “controlling” or even “sustaining” gains is next to an impossible task, long-term. Why? Because entropy works harder than you and me and all our friends combined. It’s just a fact of life.

What to do?

Right, so entropy is relentless and never tires and controlling gains are next to impossible. That’s just great. Let’s all just pack our bags and quit, right? Wrong.

Have you ever watched salmon swim upstream? It’s really one of the most amazing things you’ll ever watch.

I can only imagine how hard it is for these fish to battle the current. I wonder how tired they get? I wonder what motivates them? I wonder if they realize many of them will die on the journey?

I can’t answer these questions. But I do know these salmon may be the perfect role models for how we should approach our battle with entropy.

Swim Like Hell

You see these salmon aren’t satisfied with maintaining their present position (i.e. controlling gains). Chinook salmon, for example, swim more than 900 miles and climb 7,000 feet from the Pacific Ocean as they return to spawn each year. So with massive odds facing them they set off against a mighty foe and swim.

And so it is with us, we too must swim (i.e. continuously improve). In fact, we must swim like hell with full knowledge that entropy is waiting for us to relax… so it can do what it does best… bring disorder back to the system.

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Filed Under: Featured, Leadership, Lean, Six Sigma

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