Materials expert Dr. Ron Lasky is a professor of engineering and senior lecturer at Dartmouth, and senior technologist at Indium Corp. He has a Ph.D. in materials science from Cornell University, and is a prolific author and lecturer, having published more than 40 papers. He received the SMTA Founders Award in 2003.
Let’s assume your
company has decided that transfer efficiency (TE) is the key metric in determining
solder paste quality. Transfer efficiency is the ratio of the volume of the
solder paste deposit divided by the volume of the stencil aperture. While you
agree that TE is an important metric, you are a little troubled with the recent
results in a solder paste evaluation. Two out of 10 pastes are fighting for the
top spot and it looks like TE will be the deciding metric. Paste A had a TE of
99.5% and Paste B had a TE of 99%. So management wants to go with paste A. You
are troubled because paste A has a poor response-to-pause. If it is left on the
stencil for 15 minutes or more the first print must be discarded. This weakness
may result in 30 minutes or so of lost production time in a 3-shift operation.
However, the TE test results showed that the TE of paste A was statistically significantly better than paste B. You think about this situation and something doesn’t make sense — 5% and 99% are quite close.
You dust off your statistics textbook and review hypothesis testing. Then it hits you, with very large sample sizes, means that are closer and closer together can be statistically significantly different.
The data show that paste A has a mean of 99.5% and a standard deviation of 10%, whereas paste B has a mean of 99% and also a standard deviation of 10%. The sample sizes were 10,000 samples each. These large sample sizes are important in the analysis. The standard error of the mean (SEM) is used to compare means in a hypothesis test. SEM is defined as the standard deviation (s) divided by the square root of the sample size (n):
So as the sample
size increases, the SEM becomes smaller or in statistics lingo “tighter.” With
very large sample sizes, this tightness enables the ability to distinguish
statistically between means that are closer and closer together. This situation
was not a concern with sample sizes of less than 100, however with the modern
solder paste volume scanning systems of today, sample sizes greater than 1000
are common.
Figure 1 shows the
expected sampling distribution of the mean for samples with a TE of 99.5% and
99.0% and a sample size of 100, both have a standard deviation of 10%. Note
that to your eye you do not see much difference. However, with the means and
standard deviations the same and sample sizes of 10,000 the sampling
distributions of the mean are clearly different in Figure 2.
The reality
though, is that there is no difference in the results in Figure 1 and 2. The
tiny difference in the means (0.5%) may be statistically significant with a
sample size of 10,000, but is it practically significant? Would this small
difference really matter in a production environment? Almost certainly not.
Figure 1. Sampling distribution of the mean for a sample size of 100. Figure 2 Sampling distribution of the mean for a sample size of 10,000.
So, with large
sample sizes, we need to ask ourselves if the difference is practical. For TE,
I think we can be confident that a difference of 0.5% is not practically
significant. But, what if the difference was 2% or 5%? Clearly,
experiments should be performed to determine at what level a difference is
significant.
With the case
discussed above, I would much prefer the paste that has a 99.0% TE and a good
response-to-pause.
Dr.
Ron, when if comes to SMT printing of solder paste, why do some people use the
five-ball rule for rectangular apertures and the eight-ball rule for circular
apertures?
Michel:
The
“Five Ball Rule” is another metric that SMT assembly industry leaders believe,
but it is difficult to find its origin. It states that when selecting a solder
paste, five of the largest solder balls should be able to fit across the width
of the smallest rectangular stencil aperture. See Figure 1a for a 0.2mm wide
rectangular aperture.
Typically,
the largest solder ball diameter is assumed at the 90th
percentile. See Figure 2. So, in this example, a type 4 solder paste would fit
the five ball rule as the largest solder ball is 0.038mm. Five times 0.038 is 0.190mm,
just a little less than the aperture width of 0.2mm. It should be remembered
that this is a “rule.” not a “law.” So let’s say you had
4.5 balls across the aperture with instead of 5, it would most likely be
OK.
Figure 1.A
comparison of the Five and Eight Ball Rules
Figure 2.Solder
Powder Sizes
A
generation ago, the advent of circular apertures to support BGA and CSP
packages necessitated a new “rule.” Figure 1b shows why the five-ball rule is
inadequate for circular apertures. Although five type 3 solder balls fit along
the 0.275 diameter, off the diameter, there is not enough room for many
solder balls. Hence, an insufficient amount of solder paste would be
printed.
For
the same aperture, if a type 4 paste is used, 7 or 8 solder balls span the
diameter and the amount of paste printed would be much closer to the volume of
the aperture.
This coming February will be my third SMTA Pan Pac. Pan Pac is a very enjoyable and rewarding conference. It is small enough that you can get to know all of the speakers, yet large enough that there is a full venue. For those of us in the northern part of the US, it is also a nice break from the winter weather. The first time I went I was surprised that it wasn’t very expensive. For this coming conference, air tickets from Boston are as low as $600 and the hotel is about $200 per night.
The conference will be held on the “Big island” of Hawaii. If you come early or stay late there are many interesting attractions, including the active volcanoes and the Mauna Kea Observatories. So for sure come to the conference, but why not submit an abstract to be a speaker? If interested in submitting an abstract go to this site.
Patty had just finished an
all day workshop on “Common Defects in SMT Assembly and How to Minimize
Them.” The workshop seemed to go really well, and many of the 35 or so
attendees thanked her for a great learning experience.
After most of the people
filed out of the room, two approached her as she was disconnecting and packing
her laptop.
“Dr. Coleman, that was a great workshop. But, I do have one question. You used a term all day that I wasn’t familiar with, ‘SAC’,” a 35-year-old process engineer commented to her.
While saying this, he
presented his business card that referred to him as a “Senior Process
Engineer.”
Patty was trying to
recover from this shock, when the second similar looking fellow asked,
“And what are ‘OSP’ and ‘eutectic’.”
After explaining these
three terms and exchanging a few pleasantries, the two senior process engineers
walked out of the room and bade Patty farewell. As the room became empty, Patty
settled into a chair.
“How can this be?” she
thought. She was stunned that people with enough experience to be called
“senior process engineers” would not know these terms.
Today 6 AM …
Patty was jogging back to her house in Woodstock, VT, when she spied a beautiful red fox. Neighbors had reported seeing the fox numerous times. People believed that the fox was nesting. In addition, a black bear had been sighted by everyone in her family over the past few weeks. Add all of this to the family of deer and the rafter of turkeys in her neighborhood and it was quite an experience for Patty, Rob, and their sons.
The fox, however, created
a new problem. Patty and Rob had bought their twin sons a Yorkshire puppy,
Ellie, about a year ago. At 6 pounds she could be dinner for the fox, so,
unfortunately, they could no longer let Ellie out by herself.
Figure 1. Ellie the Yorkie after a big day. Sadly she has to be
watched when she goes outside of Patty’s house, due to the local predators.
By 7:30AM Patty was
in her office. She was giving a workshop in two weeks at a local chapter
meeting in Boston and decided to create a pre-test to give to the attendees so
that she could assess their current knowledge. Patty planned on having the
students grade each other’s exams and on working the exam in as a leaning
experience at the start of the workshop. By assessing the results of the
pre-test, she wanted to make sure she didn’t use acronyms they don’t
understand, and to also explain topics that the students might not be familiar
with. As she was working on the questions for the pre-test, Pete walked in.
“Hey, Professor C, how
goes it?” Pete asked.
“I’m preparing a pre-test
for the workshop I’m giving in a few weeks,” Patty replied nonchalantly.
“I remember you talking
about doing it a month or so ago. Seems like a good idea to me,” Pete
responded.
“I’m ,glad you approve,”
Patty said wryly. “I just finished it. Do you want to take a look at it?”
she continued.
Patty printed out a few
copies and handed one to Pete. They both looked at it for a few minutes, in
silence.
Finally, Pete commented
sheepishly, “Aaa, Patty your joking, right?”
“Why do you say that?”
Patty asked, a little annoyed.
“It’s just too easy.
Everyone will get 100% and you won’t get any information,” Pete opined.
Patty then reminded Pete
of her experience 6 months ago.
“OK. Maybe you have a
point. But, I still think it’s too easy,” Pete concluded.
“I’ll tell you what. How
about a bet? If the average pre-test grade is above 70%, Rob and I will take
you and your new crush, Mary, out to Simon Pearce. If
it is 70% or less, you treat us,” Patty teased.
“It’s a bet,” replied Pete
quickly.
The Pretest:
What does the letter “S” in SAC stand for?
How much silver is in SAC305?
What is the approximate melting point for SAC305 solder (+/- 4oC)?
Solder paste is approximately how much (by weight) metal (+/- 5%)?
What is not a current common defect in SMT?
Head-in-pillow
Pad cratering
BGA Ball Matting
Graping
Which is a closest to typical stencil thickness?
5 microns
20 mils
5 mils
20 microns
Which is closest to a typical lead spacing for a plastic quad flat
pack (PQFP)?
0.1mm
0.1mil
0.4mm
0.4mils
Which has finer solder particles, a Type 3 or 4 solder paste?
What does OSP stand for?
Place an arrow at the eutectic point of the tin-lead phase diagram
below.
Epilogue (two days after the workshop)
Patty arrived at Ivy U and
couldn’t wait to see Pete. She went to his office but he wasn’t there. Finally,
she found him in the machine shop helping four students with a project that
required some additive manufacturing.
“Hey, Pete! When are you
and Mary going to treat us to our dinner?” Patty teased.
“Don’t tell me the average
was less than 70%,” Pete grumbled.
“Forty-three point zero
eight to be exact,” Patty punctuated.
Figure 2. The Pretest
Scores
“Yikes!” Pete exclaimed,
rubbing the back of his neck. “I guess you were right.”
“It really helped me to
take things slowly and explain all the terms. I think I helped the students
much more than usual,” Patty explained.
“Rob and I both agreed, we
are ordering the most expensive meal that Simon Pearce has,” Patty joked.
At that Pete let out
a deep groan.
Dr. Ron note: All of the events in this post are true. How would you do on the pretest?
I have enjoyed writing the Patty
and the Professor blog for about 10 years now. I’ve written about numerous
real-life electronics assembly examples that I have encountered in my career,
all disguised, of course.
To continue keeping things real, and to keep my readers
involved, I am inviting you to submit an authentic story from your career.
That’s right! You’re being invited to submit an idea, story, or experience that
can be built into the Patty & The Professor series.
Your experience will help many other electronics assembly
practitioners resolve their issues and avoid problems.
So, get your thoughts together, then shoot me an email at [email protected]. Share the details of your experience or observation. I may
ask a few questions to help me comprehend the full story. Then, I will write up
the segment and let you read it before posting. You will be credited, of
course.
Bonus: You will also receive either a Dartmouth hat or coffee mug (similar to, not exactly like, those pictured below)!
Contact me if you are interested in submitting a story. I
look forward to hearing from you!
It’s been way too long, let’s look in on Patty and the boys…..
It was 5:30AM and Patty’s alarm went off. She was unusually tired
today because of a PTA meeting last night. She had become much more interested
in the school her twin sons went to when she found out that the school was no
longer teaching cursive writing. She was too late for that battle, but had
heard that the school was not going to teach long division. Another mother told
her that the reason was that long division was too hard and it could be done
with a calculator. When Patty heard this she “went through the roof.”
Fortunately, when Patty attended the PTA meeting, she and the other
parents were assured that long division was still being taught.
Patty’s sons would learn cursive, however, as both her mother
and her husband’s mother would teach the boys during baby-sitting sessions –
and once a week the boys would read one of the 100+ letters to home that their
great grandfather wrote to their great grandmother during World War II. All
written in cursive of course!
After her morning jog and workout Patty was in her office at Ivy
U by 7:30AM. She turned on her laptop and saw an email from Mike Madigan, her
former employer’s CEO. It read:
Dear Professor Coleman,
One of my golfing buddies owns a small jewelry firm, Galahad Jewelry in Providence, RI. One of the units in the company produces silver charms for charm bracelets. This unit is not performing well financially. After chatting with him I sensed that productivity is low, inventory is out of control, and the processes are not lean.
Could you visit his factory and perform an audit? Maybe Pete can go with you – just make sure he behaves.
The note finished with contact information for the company.
Not only was Pete willing to go, but Rob also had a colleague in
nearby Brown University that he wanted to visit. A few days later our trio
was heading south to Providence in Rob’s Buick.
“You guys don’t know squat about making charms for charm
bracelets. Do you really think you can help them?” Rob teased.
“Hey, we’ve got the great Professor Coleman here. She can solve
any problem! — Seriously, we’ve discuss this before, most manufacturing
processes are similar. I won’t be surprised if we can help them a lot,” Pete
answered.
They stayed in a hotel near the Galahad facility the night
before the audit. They arrived at the facility the next morning and met
with the site superintendent, Don Smithson. After exchanging pleasantries,
Patty and Rob toured the manufacturing, inventory storage, shipping, and
administrative areas. By then it was lunchtime. Pete had stayed behind to watch
the manufacturing line and collect productivity data. During a late lunch, they
requested some additional production and cost data from Smithson. They then
requested that Smithson give them two hours to develop a summary of their
findings.
After preforming all of the necessary calculations, Patty and
her team prepared a Powerpoint presentation. Smithson had gathered a few of the
process engineers and the manager of production Ervin “Bud” Clark. Clark was an
intimidating man with sharp features and, it appeared, a quick temper.
Patty started the meeting by reviewing the strengths of the
operation. The facility was so clean it could only be described as spotless.
The production workers appeared to have very good attitudes and the quality of
the resulting charms they produced was excellent. Bud Clark beamed as Patty was
sharing this information. Then she reviewed the “Opportunities for Improvement”
(OFI’s).
‘The greatest OFI is the line uptime. From the data you gave us,
and from what we gathered today, we calculated that your uptime is 30%,” Patty
began.
At this, Clark turned red in the face and demanded,” What do you
mean by uptime Dr. Coleman?”
“Simply the amount of time the line is running during an 8-hour
shift,” Patty responded.
Clark was now shaking with fury, “This is the greatest insult I
have ever experienced, my lines are running almost 100% of the time. Smithson,
let’s kick these Ivy Tower intellects out of here, they’re wasting our time!”
he grumbled.
Smithson calmed Clark down and then said to Patty, “Thirty
percent seems very low, how did you calculate it?” he asked.
“We did it two ways. Rob and I took the production metrics you
gave us and calculated uptime, Pete also monitored the line and took readings,
both methods yielded about 30%,” Patty responded.
At this Bud Clark exploded, “My lines run nearly 100% of
the time. I can’t be convinced otherwise,” he fumed.
“Dr. Coleman, can you share some of the details relating to how
you calculated 30%?” Smithson asked reasonably.
“Of course. Pete monitored the lines from the start of the shift
through lunch. The time was from 8AM to 1PM.” Patty stated.
“Well, it shows right off the bat that you don’t know our
schedule,” Clark fumed, “lunch is over at 12:30.” He was so riled that his face
was red and he was shaking.
“That’s true Patty” said, “I’ll let Pete explain.”
“Technically the lunch period starts at 12 noon, but the workers
shut their machines down at 11:48AM today. The lunch period is supposed to end
at 12:30PM, but the workers did not get back to their stations until almost
12:45PM. It then took them until 12:55PM to get the machines running. So the 30
minute lunch period was actually 1 hour and 5 minutes,” Pete explained.
“Boy, what an eye opener,” Smithson said.
Bud Clark seemed numb, but then he chimed in, “There’s no
way that extra lunch time gives us only 30% uptime,” he snarled.
“True,” said Pete, “but the 15 minute break at 10:00AM was
really 35 minutes.”
Now Smithson was getting agitated at Clark.
“Bud, what is going on?” Smithson said.
Patty felt it was time to interject some calming comments.
“To be honest, this type of situation is what we see in most
audits,” Patty said sympathetically.
“Let’s let Pete finish,” Clark said glumly.
“Works starts at 8AM, but the team really didn’t begin making
parts until almost 8:30AM,” Pete went on. In addition, set-ups for new jobs are
performed on most machines two to four times per day. In theory they take 15
minutes, in practice more like 45 minutes,” Pete went on.
“So with all of this downtime our uptime is only about 30%?”
Smithson groaned.
“Yes,” Pete responded.
Patty then showed how the production data for the last 3 months
support the 30% uptime number.
“The good news is that if you can increase productivity
by only 10%, your profits will more than double,” Patty added cheerfully.
“I find that hard to believe,” Clark said with an agitated voice
and a red face.
“Me too”, said Smithson, “ if I increase productivity by 10%, I
only have 10% more parts to sell, so profits will go up only 10%.”
“That would be true if you had no fixed costs, your fixed costs
are high. Every additional part you sell brings in more revenue, but costs less
to make because your fixed cost per part is lower,” Patty explained.
“I developed an equation the shows this,” she went on.
“In this equation nimproved is
the number of charms produced in a day after process improvement – let’s say
that is 10% more than the current amount. We’ll use nold as the current
amount per day. Pu is
the price you sell the charm for and Cu is
the material cost. CostFixed represent
the fixed costs,” she explained.
“I plotted a graph of profit versus productivity increase from the cost and production metrics you gave us. Note that current profits are at about $160,000/yr. With just a 10% increase in productivity the profits go to about $360,000/yr,” Patty continued.
Figure. Patty’s Graph of Profit Increase
vs Productivity Increase.
Both Smithson and Clark sat in their chairs dumbfounded. “If we
can’t improve productivity by 10% we should be fired,” Clark humbly replied.
Discussion then ensued on how to improve productivity, much of
it focused on how to minimize or eliminate turning the machines off. Both
Smithson and Clark became energized by this discussion and also expressed their
gratitude to Patty, Rob, and Pete.
“Did you notice anything else beyond production that could help
us reduce costs?” Smithson
asked.
“You could save quite a bit by better inventory control,” Rob
responded.
“I’m off the hook on this one Smithson,” Clark teased.
“I own inventory control,” Smithson agreed, “what did
you find?”
“Well you have way more inventory than you need. We especially
noted a block of silver as big as a microwave oven in your store room. We
calculated its value at about $500K. I asked some people who have been with the
company for over 15 years and they say it was there when they started,” Rob
explained.
“The block is so big and heavy, we could never figure out how to
work with it so we just put off dealing with it. Weeks became months and months
stretched into years,” Smithson sadly replied.
“In addition, the shipping department, although neat, had
multiple shipping cartons of the same box size that were partially used. People
also commented that they sometimes had to hunt for items for production or
shipping,” Rob went on.
Smithson sat in his chair looking glum.
“Dell estimated that the cost of one week’s inventory is about
1% of the value of the inventory, you have about 30 weeks of inventory. We
estimate that your inventory carrying charges are greater than your profits,”
Rob explained.
“I always wanted to assure we never ran out of material,”
Smithson added a bit defensively.
“A worthy goal, but you can almost certainly accomplish that with five, or at most 10 weeks of inventory,” Rob replied.
The group then began discussing to how to reduce inventory and outlined a plan. Our trio agreed to come back in six weeks and access progress in both productivity and inventory control.
On the car ride back to Ivy University, Rob sensed that Patty
and Pete were a little pensive.
“Hey you two, what’s up?” Rob asked.
“It seems like déjà vu all over again,” Pete chuckled.
Patty agreed, “The first productivity problem the Professor
helped us with at ACME was so similar to this it’s so surprising.”
“That was the first of our many adventures together with the
Professor, too many years ago now,” Pete added.
Patty agreed and Rob noted a little catch in her voice ….
Recent
articles have added to the confusion regarding when fully autonomous vehicles
will become common. One
suggests that they around the corner with this quote:
“Alphabet plans to launch a self-driving service later this year,
while GM Cruise has targeted the introduction of a similar service in 2019.
Ford has that it expects to put self-driving vehicles into commercial service
by 2021.”
So
it sounds like autonomous vehicles will be here this year or next. But wait,
here is a counter
article. This article points out the many issues to be resolved before
fully self-driving cars are launched. Consider this one quote from the article:
“There’s still a lot to be worked out. There are scenarios where
the car will have to break the law in order to proceed. One common scenario is,
you’re driving down a two-lane highway—one lane each way—and there’s a Fed Ex
truck in front of you, parked on the curb. You can’t go around it without
crossing the double-yellow line. Are you going to allow the car to break the
law? Now, you’re getting into a whole different set of rules, regulations, and
even morality decisions.”
These
two perspectives were brought home to me recently when I was on a review board
for a student projects course, Technology
Assessment, taught by friend and colleague, Eric Bish.
One of the projects was to assess the viability of bringing fully autonomous
vehicles to market by 2021. Reviewing this project helped to clarify the
dichotomy between the two perspectives discussed above.
It
ends up that the efforts of Alphabet, Ford, and GM are to be launched in very
controlled environments. They will only be used in well mapped out routes, with
good lane markers, no construction, on days with good weather etc. Note also
that the first quote refers to a self driving service, not private autos.
Having
an autonomous vehicle that can completely replace a human is still (many?)
decades away. There are just too many issues such as the FedEx scenario
envisioned above that need to be resolved. I believe that over time, more and
more such issues will be discovered and push the date of such vehicles even
farther in the future.
Even
if, on the whole, early autonomous vehicles are safer, accidents like the one
in Phoenix
earlier this year, will put a spotlight on autonomous vehicles that will
further delay their full advent.
What
does all of this portend for the electronics industry? I think these issues
will require more electronics and sensors than many believe, so in a sense it
is good news for the electronics industry.
So far the meeting with The Professor had proven very valuable, John thought. He was anxious to hear the other suggestions that The Professor had. The Professor began to speak.
“Changeovers are what really hurts ACME’s uptime and, hence, productivity,” The Professor commented.
Pete was surprised. “Even you were impressed with our system of having a white board to document the logistics’ status for each future job,” said Pete.
“You are correct,” responded The Professor. “However, a changeover takes you about 2-3 hours and you have one or two changeovers per line per day,” The Professor added.
“We have a high product mix business. It’s what we do,” said John.
“The good news is that you can cut your changeover time to 30 minutes,” shared The Professor.
“How?” asked John increduously.
“By using feeder racks,” explained The Professor. “These racks allow you to set up the component reels for the next job while the current job is running. Admittedly they cost about $30,000, but they will pay for themselves in weeks. Right now you lose more than two hours per changeover loading the feeders onto the component placement machines. With the feeder racks, you just roll them and lock them in place,” said The Professor.
Pete moaned, “We already have feeder racks. We only used
them once, because they stick on the carpet when we move them.”
This comment caused The Professor to groan internally, but he hid
it well. He had noticed the frayed carpet near the component placement
machines.
John was beside himself. “It’s a good thing we are not
The Professor’s students……I don’t think we would be heading for an A,” he
thought. John responded to Pete’s comment, “Pete, let’s get
facilities to remove that rug and start using the feeder racks
ASAP.”
Patty listened to all of this with comical fascination. She had harassed Pete about using the feeder racks several times. While the meeting was going on she drew a sketch of The Professor, who is notoriously camera shy. Oh, and she decided on the restaurant, Aujourd’hui in nearby Boston. Maybe they can pick up a Red Sox game while they’re there.
Epilogue: Six months later ACME’s uptime was a respectable 30.4%. John never had to buy another line. The improved productivity enabled ACME to increase their market share. Patty’s dinner and ball game were a complete success. She handled her victory modestly and she and Pete became best friends. Pete also joined the ranks of The Professor’s many admirers.
Dr. Ron’s note: I know that a story like this must seems too comical to be true. Every point and the associated uptime numbers, lost time etc, are all based on a real situation with no exaggeration. The Epilogue, however, is ficticious, as is the Patty/Pete friendly (?) conflict. The names have been changed to protect the innocent (guilty?).
“Well what should we do Professor?”
John said weakly.
“Clearly,
not shut the line down over the lunch break,” The Professor responded
quickly.
“We
can’t!” said John, “The operators are all friends and they
count on having lunch together.”
“How
much are they paid per hour?” asked The Professor.
“Ten
dollars,” replied John.
“You
can pay them $15 per hour and still make more profit if they keep the line
running over the lunch break,” The Professor opined.
“Fifteen
dollars per hour for the lunch time or the entire 40 hour week?” John
asked nervously.
“For
the whole week,” was The Professor’s reply.
“I
find that hard to believe,” John shot back.
“Consider
this,” said The Professor. “Your line is up only 9.7% of an 8 hour
shift, that’s only 47 minutes. Today you lost 95 minutes over the lunch hour.
You may be able to increase your uptime to greater than 15% by keeping the line
running over lunch. I modeled your business with ProfitPro3.0 cost estimating software. Your
company will make millions more per year if you keep the lines running over
lunch. I have worked with other companies to make this change; it is really
easy with a 30 minute lunch period. If 5 people normally run the line, you
have just one stay back during lunch. That way each person only misses the
regular lunch break once a week.”
John
thought optimistically, “There is such a thing as a free lunch.”
“Now,
let’s talk about what we can do to double the uptime from the 15% we will get
by running the lines over lunch,” said the Professor.
Patty
listened to all of this in amazement. The Professor was helping ACME more than
she thought possible.
Next
steps? Yes, John will keep his job. But, what is The Professor’s plan to get
uptime to 30% or more? And, we still haven’t learned where Patty will go to
dinner. Stay tuned for the latest.
Cheers,
Dr.
Ron
Dr.
Ron note: As surprising as this may seem, this story is based on real
events. The uptime numbers and improvements are from real examples. Any company
that can achieve 35% or more uptime can compete with anyone in the world, even
in low labor rate countries. Sadly, few companies know their uptime or have an urgency
to improve it.
For the next few weeks I plan to repost some of the first Patty and the Professor episodes. As I visited several facilities, some of them in other industries, I found that uptime is as vital a topic as ever. Although these facilities were tracking a few metrics, uptime was not one of them. I estimated they were little better than ACME in the following vignette. Let’s all be committed to measuring and improving our processes uptimes. Now on to Patty and the Professor.
Two weeks passed quickly and The Professor returned to ACME. Patty met him at the door. “Professor, it’s great to see you,” Patty said with enthusiasm. “We collected the uptime data in real time on a laptop, no one has seen that results yet. We wanted it to be a surprise,” said Patty. The Professor suggested that he go out on the shop floor to observe the manufacturing activities until shortly after lunch. He pointed out that his observations may help to understand the uptime results.
The morning seemed to drag for Patty, she was very anxious to see the resets of the uptime data. She bet Pete a dinner for two that the uptime would not be more than 50%. If she wins, Pete and his wife will treat her and her boyfriend Jason to dinner at the restaurant of her choice.
Around 1:30 p.m. The Professor suggested that he was ready for the meeting. Patty had written a simple Excel macro to perform the calculations for the uptime. She only had to push a button and he whole room would see the result in a moment, as Patty connected her laptop to a projector. There was tension in the air, friendly wagers had been made, but the entire process team realized that their reputation was on the line.
When the number emerged on the screen, John, the manager’s face became ashen. Pete’s visage was redder than two weeks ago. John thought, “I should be fired. How could I manage this team for five years and not know that our uptime was only 9.7%.” Patty was thinking about her choice of restaurants.
“How can we be so bad?” John asked The Professor. The Professor responded, “The good news is that there are tremendous opportunities for improvement. After observing the operations out on the floor this morning, I think we can get the uptime to greater than 40%.” Pete shot back, “You’re kidding, only 40%?”
“I’ve only seen two operations that have greater than 45% uptime, and I’ve been to over 150 facilities worldwide,” answered The Professor.
“Where do we start?,” asked John.
“How about lunch?” beamed The Professor.
“We just had lunch!” Pete groaned.
“No, no Pete,” The Professor chuckled, “I mean how lunch is handled out on the line. Lunch costs the company more than 1½ hours of production in an eight hour shift. That’s nearly 20% of the entire shift.”
Now John was a little agitated. “Professor, lunch is only 30 minutes. We purposely have a short lunch period to avoid the line being down for a long time,” John said with a note of annoyance.
“John, this is true, but I watched what the operators did. Lunch is supposed to start at 12 noon, but the operators turn the line off at 11:40 a.m. They don’t get back to the line until 12:40 p.m. and it takes them more than 30 minutes to get the line running again. Today, the line was not running until 1:15 p.m. It was down for 1 hour and 35 minutes,” stated The Professor.
John thought again, “Yes, I should really be fired.”
Will John keep his job? What restaurant will Patty choose for dinner? What should be done about lunch? Where are all of the other hours lost? Stay tuned for the answers to these and other questions.
