Stencil Aperture Design for the Pin in Paste (PIP) Process

Peter writes,

Dear Dr. Ron,

I am trying to implement the Pin-in-Paste (PIP) process. The PWB is 63 mils thick, the component pin diameter is 47 mils, the PWB hole diameter is 87 mils, and the PWB pad diameter is 120 mils. I used the Indium StencilCoach software and the result said that I needed a stencil aperture with a 416 mil diameter for the 5 mil thick stencil I was using.

That stencil aperture diameter is way too big. What gives?

Best,

Peter

Dear Peter,

The issue is that your PWB hole diameter is too large. It is 40 mils greater than the component pin diameter. This situation results in a very large amount of solder required to fill the mostly empty PWB hole. See Figure 1. Since solder paste is about 50% by volume flux, quite a bit of paste is often needed to form a good solder joint.

Figure 1
Fig. 1. This figure is a cross-section schematic of a component mounted on a PWB. The fillet, hole, and pin volumes are shown and the resulting solder volume needed. If the component pin is much smaller than the PWB hole diameter, more solder paste will be needed than the pin-in-paste printing process can provide.

Chatting with my friends, Jim Hall and Phil Zarrow of ITM and Jim McLenaghan of Creyr Innovation, they all recommend that the PWB hole diameter be in the range of 10 to 12 mils larger than the pin diameter. In your case, this would be a hole diameter of 58 mils (I chose 11 mils greater than the pin diameter) and a PWB pad diameter of say 80 mils. The software calculates that a stencil aperture diameter of 194 mils is required (see Figure 2). It might be better to choose a square aperture of 172 mils on a side as seen in the output below. If this size stencil aperture is still too large, solder preforms can help. I will discuss using them in a future post.

Figure 2
Figure 2. The right hand column of this figure shows that a round stencil aperture diameter of 194 mils (2 x 97.184, the third cell from the bottom) is required to form a good solder joint in this application. It might be advantageous to use a square aperture of 172 mils on a side, as show in the fourth cell from the bottom in the right column.

By the way, Jim McLenaghan refined some earlier work that resulted in the formula for the fillet volume used in StencilCoach. Zarrow and Hall just released a book called Troubleshooting Electronic Assembly: Wisdom from the Board Talk Crypt. These three folks are some of the most knowledgeable people in electronics assembly today.

Cheers,

Dr. Ron

The Area Ratio for Odd-Shaped Stencil Apertures

Joey writes:

Dear Dr. Ron,

I have a stencil aperture with an unusual shape. See Figure 1. How do I calculate the area ratio? The stencil thickness is 5 mils. The dimensions of the aperture are also in mils.

Figure 1. Joey’s Stencil Aperture

Joey,

The area ratio is simply the area of the stencil aperture opening divided by the area of the sidewalls. For common aperture geometries such as circles, squares, etc. it is easy to derive formulas. See Figure 2.

Figure 2. Formulas can be developed for common aperture shapes.

For an unusual shape like yours, it is easiest to simply calculate and divide the areas. From Figure 1, we get that area of the aperture opening as: 40*24+ the area of the two triangles. A little geometry (can you do it?) shows each triangle to have an area of 89 sq mils. So, the total area is 960 + 2*89 = 1138 sq mils. The perimeter is 40+24+16+16+28+12+16+16 = 168 mils, hence the area of the sidewalls is 168*5 = 840 sq mils. Therefore, the area ratio is 1138/840 = 1.355. Experience has shown that an area ratio of > 0.66 is needed for good solder paste transfer efficiency, so this stencil aperture will do well for transfer efficiency.

Careful thought would suggest that the triangular protrusions alone do not have a good area ratio. Calculations show their area ratios to be 0.37. So, the transfer efficiency in this part of the aperture might not be good. However, the area of the rectangle is so great, more than five times that of the triangles, as to alleviate this concern.

Dr. Ron



Autonomous Vehicles Even Farther Out in Time

Folks,

Readers of this blog will remember that I have been a skeptic of self-driving cars emerging in the near term. I am even less sanguine today. A recent article supports my perspective. Humans just do so many things effortlessly that sensors and computers cannot duplicate.

As an example, suppose there are five people at a street corner. These individuals non-verbally communicate intent that other humans easily pick-up on. If they are talking to each other and not facing the road, a human rightly concludes they are not planning on crossing. If they are facing the road and looking at the traffic, a human expects they plan to cross. This intuition is well beyond any AI’s ability to interpret and will be for decades to come.

Figure 1. A human recognizes that these students aren’t planning on crossing the street.

Autonomous vehicles are typically over designed to not cause accidents. Therefore, in some cases, if a pedestrian sticks their hand out into a road to wave at a self-driving car, it will stop. Whereas a human would recognize that the person is just goofing-off or being friendly.

All of this new information makes Elon Musk’s claim that Tesla will have a car on the road in 2022 without a steering wheel hard to accept.

To be fair, self-driving cars in controlled conditions, such as low traffic, well-marked routes, in good weather, will become more common in the decade ahead. However, an autonomous vehicle that can pick me up from my poorly marked 200 foot driveway, off an unmarked country road in Vermont, and then drive me to terminal C at Boston’s Logan airport is many decades away.

So, if you know someone who wants to be a truck driver, I feel that that will continue to be a fruitful career for a long time. In addition, those of us who manufacture electronics can take comfort in the fact that autonomous vehicles will need much more electronics than originally thought.

Cheers,

Dr. Ron

Thixotropy: An Important Solder Paste Property

Folks,

To the SMT process engineer, the second most important thixotropic material in their lives is solder paste. If solder paste was not thixotropic, it would be difficult to print and would likely slump after printing the paste. What is a thixotropic material? It is a material that has a low viscosity when it is shear stressed and a high viscosity when it is not shear stressed. So, when the solder paste is forced through the stencil aperture by a squeegee, its viscosity plummets and allows it to fill the aperture. See Figure 1.

Figure 1. The viscosity of solder paste dramatically decreases as it is forced through the stencil aperatures.

When the stencil is removed, the resulting solder paste deposit experiences no shear stress so the deposit maintains the shape of a “brick.” See Figure 2. So thixotropy is a very helpful property of solder pastes.

Figure 2. After printing, the solder paste viscosity is high, enabling the depost to maintain the brick shape. Figure courtesy of Ron Lasky, Jim Hall, and Phil Zarrow.

If solder paste was dilatant, it would be a disaster. These materials are the opposite of thixotropic materials. They have a low viscosity when not shear stressed and a high viscosity when shear stressed. So they could not be forced through the stencil aperture and, if they could, they would flow all over the board. Cornstarch and water is an example of a dilatant material.

Oh, yes, what is the most important thixotropic material to the SMT process engineer? Their blood. When getting up from lying down, our heart automatically makes a strong “pump” to rush the flow of blood to our head. Since blood is thixotropic, it shear thins and makes it easier for our heart to get the needed blood up to our head. If blood was not thixotropic, we might faint every time we rise from reclining!

Cheers,

Dr. Ron

Statistically Significant vs. Practically Significant in SMT Data Collection

Folks,

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.

Cheers,

Dr. Ron

Dispelling The ‘Five Ball Rule’

Michel writes:

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.

For a little more on this topic, see a past post.

Cheers,

Dr. Ron

Selecting Reflow Oven Length

Folks,

You are putting in a new assembly line to assemble some large boards for which your company just received a three-year contract. The boards are 45cm long and you expect the cycle time from the component placement machines to be 40 seconds per board. Your boss is pressuring you to get another 5-zone oven, as they are cheaper and take up much less space than a 7- or 10-zone oven. But, you are concerned that a 5-zone oven may not have the capacity that is needed to keep up with the component placement machines. Let’s make some calculations and see if your concerns are justified.

Table 1 shows some typical reflow oven metrics:

Let’s assume that you will be using a typical modern SAC solder paste. By studying the reflow profile above, we see that the amount of time needed in the heated zone is about 4.5 min. or 270 sec.

So if we choose the 5-zone oven the belt speed will be:

Belt Speed = BS= Heat Tunnel Length/Time in Heated Tunnel = HTL/Time = 180 cm/270 sec. or 0.66 cm/sec

The component placers will be presenting a 45cm board every 40 sec., so the belt speed needs to be:

BS = Board Length/Cycle Time = BL/CT = 45cm/40 sec = 1.125cm/sec

So clearly a 5-zone oven won’t work. What about a 7-zone oven? Let’s calculate the belt speed for this oven.

BS = HTL/Time = 250cm/270 sec. or 0.926cm/sec

Now we can see that the 7-zone oven won’t do the job either.

How about the 10-zone oven? Let’s see if the belt speed is greater than the 1.125 cm/sec needed.

BS = HTL/Time = 360cm/270 sec. or 1.33cm/sec

Success! Since 1.33cm/sec is greater than 1.1125cm/sec, this 10-zone oven will work. The extra belt speed will permit a small amount of spacing between the boards. Let’s calculate what it will be:

BS = (BL + Spacing)/CT = 1.33cm/sec => BL+ Spacing = BS x CT => Spacing = BS x CT – BL

Spacing = 1.33cm/sec. x 40 sec – 45cm = 53.2cm – 45cm = 8.2cm

To summarize: For our 45cm board that has a cycle time of 40 sec., we need a 10-zone oven with a heated tunnel length of 360cm. There will be an 8.32cm spacing between the boards in the oven.

If you would like an Excel spreadsheet to make these calculations send me an email at rlasky@indium.com.

Cheers,

Dr. Ron

SMT Workshop Pre-Test

Folks,

Six months ago …

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:

  1. What does the letter “S” in SAC stand for?
  2. How much silver is in SAC305?
  3. What is the approximate melting point for SAC305 solder (+/- 4oC)?
  4. Solder paste is approximately how much (by weight) metal (+/- 5%)?
  5. What is not a current common defect in SMT?
    1. Head-in-pillow
    1. Pad cratering
    1. BGA Ball Matting
    1. Graping
  6. Which is a closest to typical stencil thickness?
    1. 5 microns
    1. 20 mils
    1. 5 mils
    1. 20 microns
  7. Which is closest to a typical lead spacing for a plastic quad flat pack (PQFP)?
    1. 0.1mm
    1. 0.1mil
    1. 0.4mm
    1. 0.4mils
  8. Which has finer solder particles, a Type 3 or 4 solder paste?
  9. What does OSP stand for?
  10. 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?


Self-Driving Cars Decades Away Means More Electronics Will Be Needed

Folks,

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.

Cheers,

Dr. Ron

The Return of Patty and the Professor: Uptime Part 2

Folks,

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.

Cheers,

Dr. Ron