Tag Archives: Ron Lasky

The Professor at AJAX

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In contemplating the events that transpired in the nine months since The Professor’s last visit, Patty had to chuckle.  John, her boss, received ACME’s company-wide Manager of the Year Award. The citation accompanying the award read, “For Conspicuous Leadership, Creativity and Innovation in Tripling Assembly Line Uptime.”  John received a $25,000 cash award and a trip for two to Belize.  Right!

Well, at least John was grateful to her.  He called her into his office after he received the award and told her that the award should be hers; she thought it should really be The Professor’s.

Anyway, he put her in for a promotion and she got it.  She was five years ahead of her peers; since she had just received a promotion last year.  She was also getting along well with Pete and company morale was high, even in these tough times, as the company was doing very well financially.  Three months ago, she presented a paper at SMTAI on the work they did to triple their line uptime from 10 to 30+%.  It received the “Best Paper” award.  She had wanted the Professor to be a co-author, but he refused.  Pete, however, was pleased to accept a co-author opportunity.   She was told that, at 24, she was the youngest recipient of this award — by eight years.

Several months ago she was asked to give a presentation on this work at a local SMTA meeting.  At this meeting she met Rob, a peer at AJAX.  AJAX was a local company that performed dedicated electronics assembly for its parent company in the automobile industry.  Hence, AJAX wasn’t a competitor to ACME.  She had heard rumors that the senior managers from ACME and AJAX even played golf together and shared ideas on improving their companies.  Rob was really interested in Patty’s talk and seemed to “soak up” everything that she said.  She couldn’t help but sense that he was more than a little interested in her in other ways.  He had been one year ahead of her at Tech and they both remembered each other.  After Tech, Rob had gone to work in aerospace, but had recently been RIFFed.  He has only been at AJAX for a few months and appeared determined to make his mark at the company as soon as possible.

As Patty was daydreaming about all of these good events, she saw a new email arrive on her laptop.  It was from Rob.  Upon opening it, she read that Rob asked her to call.  Patty immediately picked up the phone.

“Hi Rob, it’s Patty. What’s up?”

“Hey, Patty, how about our Red Sox losing six in a row, after leading the league?” said Rob.

“I’m devastated,” replied Patty.  “However, I’m cautiously optimistic, because when The Professor was discussing statistics in a workshop I took, he mentioned that even if a team is winning 60% of it games, there is more than a 50% chance that the team will lose six in a row in a season … it is just the nature of statistics.”

“Well, I hope he’s right,” replied Rob.

“Patty, your talk at the local SMTA meeting was really great.  I went back to AJAX and measured our uptime, and it was only 15%.  By following the things your team at ACME has done, we are up to 32% uptime.  But, I still sense we are missing something.”

“How so?” Patty responded.

“Well,” Rob started, “I’ve read some of The Professor’s papers and books, and performed a few calculations. These calculations suggest that AJAX should be able to produce at least 20% more product than we do.”

Hmmm, Patty murmured. “It sounds like your assembly lines may not be line balanced. Have you checked to see it they are?”

“How do we do that?” Rob queried.

“Well, I did it for ACME after attending The Professor’s workshop at last year’s SMTAI,” replied Patty.

“Could you help me do it at AJAX?” pleaded Rob.

“Gee, Rob, I don’t want to goof anything up at AJAX,” Patty said thoughtfully. “Why don’t I call and see if The Professor can help? You can check with your manager and see if involving The Professor is OK on AJAX’s end.”

Patty got The Professor on her first call.  Unfortunately, he couldn’t come, but suggested he could teleconference with her and Rob and develop a plan to audit AJAX’s line balancing. At Patty’s insistence, The Professor agreed to teleconference in to the meeting that Rob and she planned to kick off the audit. Patty felt it was important to have The Professor’s credibility to legitimize the audit.

Later, Patty had received a summons to the general manager’s office.  She was very nervous, but the GM put her at ease.  He told her that he and the AJAX GM were golfing buddies and he had heard that she was asked to help Rob.  He then went on to say that it was great that she was helping Rob as he always wanted the AJAX GM to “owe him one.”  The GM then congratulated her on her recent promotion and finished by saying: “Patty, the future of ACME is in the hands of young, bright, curious and hardworking folks like you. I sleep a little better at night knowing you are on my team!”

Will AJAX’s lines be balanced?  What will the characters at AJAX be like?  Will there be a Pete there?  Will Rob make a move on Patty? Stay tuned for the latest in the adventures of The Professor and his protégés.

The Professor, Part IV: The Price of Changeovers

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So far the meeting with The Professor had proven very valuable John thought. He was anxious to hear the other suggestions The Professor had.

The Professor began to speak. “Changeovers are what really hurts ACME’s uptime and hence productivity.”

Pete was surprised. “Even you were impressed with our system of having a white board to document logistics status for each future job.”

“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.”

“We have a high product mix business; it’s what we do,” said John.

“The good news is, you can cut your changeover time to 30 minutes,” shared The Professor.

“How?” asked John.

“By using feeder racks,” explained The Professor. “These racks allow you to set up 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 feeders onto component placement machines. With the feeder racks, you just roll them and lock them in place.”

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 headed for an ‘A,’ “ he thought. “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, Olives 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 its market share. Patty’s dinner and ballgame 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 admirers.

Dr. Ron’s note: I know that a story like this seems too comical to be true. However, every point and the associated uptime numbers, lost time, etc., is based on a real situation with no exaggeration. The names have been changed to protect the innocent (guilty?) What is your uptime?

The Professor’s 2d Visit, Continued

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“Well, what should we do Professor?” John said weakly.

“Clearly, not shut the line down over the lunch hour,” 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 hour,” The Professor opined.

“Fifteen dollars per hour for the lunch time or the 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 eight-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, and 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, and it is really easy with a 30-minute lunch hour. If five people normally run the line, you have just one stay back over lunch hour; that way, each person only misses the lunch hour 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. Yes, John will keep his job. What is The Professor’s plan to get uptime to 30% or more? 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. A company that can acheive 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 the urgency to improve it.

Line Balancing: The Professor’s Tale

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Folks,

Business was good at ACME.  Even in these challenging times, the company’s three assembly lines could not keep up with demand.  John, the manger of the assembly lines, decided to request the funds for an additional assembly line.  A member of his team, Patty, suggested he might want to consult “The Professor,”*before getting a new line.

The Professor taught a course on line balancing that Patty took at the SMTAI conference last summer.  Line balancing is an important part of optimizing productivity in electronics assembly. A balanced line ensures that the component placement process, usually the “constraint,” is the fastest possible by ensuring that each placement machine spends the same amount of time placing components.  If any machine is waiting for the others, assembly time is being wasted.  In a sense line balancing is an application of Goldratt’s Theory of Constraints. John remembered that when Patty applied what she learned from The Professor, throughput increased 25%.  Unfortunately, Patty did not attend The Professor’s other class on “Increasing Line Uptime.”

John decided to have a chat with Patty about The Professor.

“Patty, why do you think I should consult with The Professor, about getting a new line?”

“Well John, perhaps with some effort to improve our uptime , we wouldn’t have to buy another line,” said Patty.

“That’s a good point,” replied John.

Patty contacted The Professor and he agreed to fit ACME into his busy schedule. Upon his arrival, The Professor was given a tour. As part of the tour he was shown the process that ACME used to minimize changeover time between jobs. The Professor appeared impressed. After the tour, The Professor asked if a brief meeting could be held with the engineers and managers to discuss the situation.

“What is the average line uptime?” The Professor asked the assemblage.

There was some hemming and hawing, finally Pete, the senior process engineer replied, “I’d say at least 95%, we work our fannies off out there.” There was a murmur of agreement from the 9 or 10 people in the room.

Finally John spoke up, “Professor, what is your definition of uptime?”

The Professor responded, “Simply the percent of time an assembly line is running.” Pete again responded that 95% was the right number.

The Professor asked for some production metrics and performed some calculations on his laptop. In a few moments he commented, “From the data you gave me, I estimate that your average line uptime is about 10%.”

Upon hearing this, Pete became red in the face, especially after Patty whispered in his ear, “I told you so.” The noise in the room became so loud that John was concerned he might have a riot on his hands. The Professor asked to speak and John, in a booming voice, asked for calm.

“Let’s not become angry, perhaps my calculations are off. Why don’t we measure the uptime for a few weeks to be certain.”

“How do we do that?” asked Pete, his face still crimson.

“Each day one process engineer will go out to the lines every 30 minutes. If the line is running, he will put a 1 in an Excel spreadsheet cell. If the line is not running, a 0 will be entered,” responded the professor.”

It was agreed that this will be done and The Professor would come back in two weeks.

Will Pete’s red face return to normal? Will the line uptime be 95%? Will Patty and Pete ever be on speaking terms again?  Stay tuned for the next episode.

Cheers,

Dr. Ron

*The Professor, as he is affectionately called by his many students, is a kindly older man who works at a famous university. Few know his real name. The Professor is an expert in process optimization.

Tin Pest: A Forgotten Issue in Pb-Free Assembly?

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Tin is a metal that is allotropic, meaning that it has different crystal structures under varying conditions of temperature and pressure. Tin has two allotropic forms. “Normal” or white beta tin has a stable tetragonal crystal structure with a density of 7.31g/cm3. Upon cooling below about 13.2°C, beta tin turns extremely slowly into alpha tin. “Gray” or alpha tin has a cubic structure and a density of only 5.77g/cm3. Alpha tin is also a semiconductor, not a metal. The expansion of tin from white to gray causes most tin objects to crumble.

The macro conversion of white to gray tin takes on the order of 18 months. The photo, likely the most famous modern photograph of tin pest, shows the phenomenon quite clearly.
39-40.

This phenomenon has been known for centuries and there are many interesting, probably apocryphal, stories about tin pest. Perhaps the most famous is of the tin buttons on Napoleon’s soldiers’ coats disintegrating while on their retreat from Moscow. Since tin pest looks like the tin has become diseased, many in the middle-ages attributed it to Satan as many tin organ pipes in Northern European churches fell victim to the effect.

Initially, tin pest was called “tin disease” or “tin plague”. I believe that the name “tin pest” came from the German translation for the word “plague” (i.e., in German plague is “pest”).

To most people with a little knowledge of materials, the conversion of beta to alpha tin at colder temperatures seems counter intuitive. Usually materials shrink at colder temperatures, not expand. Although it appears that the mechanism is not completely understood, it is likely due to gray alpha tin having lower entropy than white beta tin. With the removal of heat at the lower temperatures a lower entropy state would likely be more stable.

Since the conversion to grey tin requires expansion, the tin pest will usually nucleate at an edge, corner, or surface. The nucleation can take 10s of months, but once it starts, the conversion can be rapid, causing structural failure within months.

Although tin pest can form at <13.2°C, most researchers believe that the kinetics are very sluggish at this temperature. There seems to be general agreement in the literature that the maximum rate of tin pest formation occurs at -30° to -40°C. How much of a worry is tin pest in practice? Probably not too much. Small amounts (0.01 to 0.1%) of some metals, most notably antimony and bismuth, inhibit the formation of tin pest, probably by solid solution strengthening. Because most tin will have such impurities, researchers have actually found it hard to produce tin pest in the lab. A concern, of course, is that these impurities are uncontrolled, leaving open the chance of tin pest showing up in some cold temperature applications. I have written a paper that discusses tin pest in more detail. If you are interested, send me a note and I will send it to you.

Let the Data Be Your Driver

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I was recently asked to give a presentation and audit an assembly line regarding minimizing “tombstoning” of passives at a major electronics assembler. As my presentation brought out, tombstoning can be caused by many factors: the reflow profile, the solder metal composition (for lead-free applications, SAC 387 tends to tombstone more than SAC 305), off-center placement, nitrogen reflow atmosphere, buried vias, etc. After two hours of talking, I walked the line that “had a problem with tombstoning.”

As I started asking, it became clear that no one knew the magnitude of the problem.

“How many passives are on each board?” I asked. No one knew.

“How many DPMO (defects per million opportunities) for tombstones have you had recently?” Also unknown.

As people scurried to get the data, it dawned on us that tombstoning might not be as big an issue as was thought. It was more of a local legend.

Finally, we got some data. Each board had about 1000 passives, and the company had produced 100 boards with a total of two tombstones in the past two hours. Tombstones were the only defect. Hmmmmm, two bad boards out of 100 = 98% first-pass yield, not bad! From a DPMO perspective, they had two defects per 200,000 (two defect opportunities per passive) opportunities or 10 DPMO, which is beyond world-class. This level of DPMO would be very difficult to improve on without massive engineering investment. It is “in the noise” and it is likely caused by “common cause” variation.

I then asked how much money it costs to repair a tombstone; as expected, no one knew. My guess was less than $2. This situation is the rare case where yields are so good, it may not pay to make engineering investment to improve them.

This isn’t the point of the story, however. In a case like this, the response — whatever it is — must be data driven. Only with the proper failure rate data, plotted in a Pareto chart, and a complete understanding of all costs, can the appropriate action plan be developed.

Always be data driven!

When Six Is Really 4.5

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Folks,

In teaching Six Sigma workshops at Dartmouth, we ensure that everyone understands that “Six Sigma,” as presented in the industry, is in fact mathematically 4.5 sigma. So when folks say Six Sigma is 3.4 defects per million (dpm), they are in fact not referring to plus-and-minus six standard deviations from the mean (even though they may not know it), as 3.4 dpm is only 4.5 sigma.

The true six sigma defect rate is 2 defects per billion. The figure shows this error.

Where does this confusion come from? When Six Sigma was developed, it was defined as a Cp of 2 and a Cpk of 1.5. These process capability indices are where the confusion lies. A Cpk of 1.5 permits a shifting of the process mean of 1.5 sigma, hence the true statistical measure of Cpk = 1.5 is 4.5 sigma (or 3.4 ppm). True statistical six sigma (Cpk = 2) is elusive indeed at 2 dpb!

Cheers,
Dr. Ron