November 27, 2025 • 14 mins
A crowded server board with ten thousand parts doesn’t forgive sloppy inspection—and neither do pricey GPUs and chiplets. From the floor of Productronica in Munich, we dig into how automated optical inspection keeps advanced packages honest once they hit the PCB line, where solder quality, coplanarity, and sheer component variety can make or break yield. Vidya Vijay from Nordson Test & Inspection joins us to unpack why AOI remains the fastest path to actionable insight, when X‑ray is the smarter choice, and how new sensor design changes the game for reflective, high‑mix assemblies.
We explore the real pain points engineers face today: shiny dies that confuse cameras, BGAs packed with I/O where hidden defects hide under the body, and miniature passives that crowd tight keep‑outs. Vidya explains how three‑phase profilometry creates true 3D height maps by projecting fringe patterns and reading them from multiple angles, enabling precise checks for corner fill, underfill, and coplanarity. We also get into multi‑reflection suppression, Nordson’s approach to filtering glare and ghost images so the system sees the joint, not the noise. With true RGB on side cameras and higher resolution, AOI can now pick out tiny solder balls and subtle surface issues at speed—fuel for stronger AI autoprogramming and more reliable defect classification.
If throughput is king, data is queen. We talk about closing the loop from inspection back to the line to prevent bad lots—flagging stencil drift, placement offsets, and paste issues before they explode into scrap. Then we spotlight Nordson's launched SQ5000 Pro: faster cycle times, a wider field of view, and configurable 7 µm or 10 µm sensors designed for modern PCBA demands. Whether you’re chasing yield on high‑value GPUs or balancing AOI with AXI on dense boards, this conversation offers a practical roadmap for choosing the right tool, tackling reflectivity, and using insight to drive predictable quality.
Delivering best-in-class test, inspection, and metrology solutions for semiconductor applications.
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Francoise von Trapp (00:22):
Hi there! I'm Francoise von Trapp, and
this is the 3D Insights Podcast.
Hi everyone.
This week we are recording livefrom Productronica in Munich,
Germany, and we are talkingabout the importance of optical
inspection in microelectronicsmanufacturing.
(00:44):
Now, this year we've beentalking with Nords Intestine
Inspection in a series ofepisodes about the full spectrum
of inspection and metrologytechnologies.
We had an episode on acousticmicroscopy, one on planar CT,
and most recently on X-raymetrology.
But today we're speaking withVidya VJ on the role automated
(01:06):
optical inspection plays acrossthe microelectronics
manufacturing spectrum andspecifically around printed
circuit board assembly.
Welcome to the podcast, Vidya.
Thank you.
I'm glad to be here.
Now we talked on the podcast afew years ago, I think, in
Semicon West.
For the front end sensors, forsure.
(01:28):
Right.
Yeah.
Vidya Vijay (01:29):
We talked about some vapor scent sensors that is
also part of our solution.
Francoise von Trapp (01:33):
Right.
Vidya Vijay (01:34):
So how has Product Tronica been for you this year?
Francoise von Trapp (01:36):
Here we are, it's the first day.
It's been quite good at Productronica, very busy year.
Vidya Vijay (01:42):
So any difference this year than other years that
you're noticing?
I mean, uh it's the goodquality of audience the very
first day.
I think that's a that's a bighuge difference for us.
So you're not exhibiting overat SEMICON Europa, which is
happening concurrently.
We don't have our own booth.
We are with our distributor.
We do have our products thatare in the front end, WaferSense
products uh being displayed, aswell as our acoustic systems uh
(02:06):
at the booth in Semicon Europawith our distributors.
Okay.
Francoise von Trapp (02:10):
So here today now, can you tell me a
little bit about your role atNordson and then maybe um we can
talk a little bit more aboutwhat Nordson does in the PCBA in
general?
Vidya Vijay (02:21):
Yeah, definitely.
I'm the director for growth andstrategy.
Also manage all the productsfor optical sensors and
metrology division, which is ouroptical systems and wafer sense
on the front end side, as wellas our acoustic systems.
I'm an electrical engineer byeducation and training and uh
slowly moving on to managingproducts that actually inspect
(02:44):
uh from the front-end productsto the back end electronics
assembly.
Okay.
Francoise von Trapp (02:49):
We at 3D Insights generally focus on the
advanced packaging, 3Dintegration side of things.
But you know, we don't oftentalk about what happens after
that device is manufacturing andand what it causes downstream
when it goes to the printedcircuit board assembly, because
we're here we are delivering youhigher density advanced
packages.
(03:09):
So, what sort of challengesdoes this bring to the PCBA
environment?
Oh, definitely.
Vidya Vijay (03:17):
With the first of all, with the advanced
packaging, each component costand the value of each component,
how critically it's placed onthe boat, is very, very high.
Right.
And uh these components nowalso have multiple IOs, meaning
it could be a BGA with multiplebumps.
Now, when you have a BGA, youneed to make sure every bump is
(03:39):
sorted in place and there is noshots between each.
All three items the X, Y, thecoplinarity, how it seats, all
of that is important.
Not just one, not just lookingat the sorter stencil, but all
of these multiple IOs on theboard.
And you also have componentsthat are shorter and also even
the passives that are much, muchsmaller, 02, 01, 08, 04.
(04:03):
I mean, you know, things aregetting a lot smaller in terms
of passives with each of theI.O.
And the number of componentsnow you can have on a server
board more than 4,000 to 10,000components.
And you have these um uh biggeruh GPUs, CPUs, a lot of
memories, a different type ofconnectors, multiple variety of
(04:24):
components very closelypackaged.
Francoise von Trapp (04:26):
Right, right.
So you're getting a lot morecomplexity in the packages
themselves than used to be.
Yes.
Vidya Vijay (04:32):
What is driving that?
For advanced packaging, right?
We have system on chip typesolution, we have uh co-wast
type packages that now it'spackaged with multiple IOs,
right?
Multiple IOs.
These types of GPUs, when theygo on the board, now these are
extremely expensive GPUs, stillneed a little bit of outside
(04:53):
I.O.
connectivity and so on.
That is definitely creating avery expensive uh end product.
Then the inspection, thesoldering, the quality of
solder, the placement of thecomponent, all of that becomes
extremely critical.
And it used to be critical witha few micron offsets now that
these are coming down, comingdown slower, uh smaller and
(05:16):
smaller.
Francoise von Trapp (05:17):
What other challenges are you finding with
today's advanced packages?
Vidya Vijay (05:21):
So with the advanced packages, the other
thing we are seeing is a lot ofshiny components.
Okay.
So this is still like a camera.
When you see something shiny,you know, you're reflecting and
it is becoming part of youroptical chain as well.
So we are seeing a lot ofrequests for shiny components,
shiny dies.
That that's becoming a biggerchallenge, actually.
(05:41):
What's making them shiny?
The substrate, the die itself.
Okay, and we are also doing alot of system on chip type
inspection.
Okay.
So now that has exposures to alot of shiny components.
Okay.
And a lot of the RF componentsare also shiny.
Okay.
And what about like chiplets?
Chiplet packages.
(06:02):
Yeah, chiplet packages can alsogo on to different types of
boards.
All types of components at theend, you know, can go on its own
substrate or can go on an FR4type assembly.
And uh those can be inspectedas well.
And sometimes if it is just uhcompletely surface mode, no
leaks, uh there we need to makesure there is corner fill and
(06:23):
underfill properly to thesecomponents so they are making
good contacts.
Okay.
Francoise von Trapp (06:28):
So are there any challenges that you're
faced with concerning differentsubstrate materials like glass
core substrates as opposed tothe traditional laminates or
even silicon?
Vidya Vijay (06:40):
So mostly on the PCBA side, we are still seeing a
lot of FR4, but also a lot ofother substrates within the IGBT
can be a ceramic type uhsubstrate for those
applications.
Francoise von Trapp (06:54):
Okay, so what I'm thinking about is the
packaging, the packages that arecoming in that have been built
on a glass core substrate or aglass carrier or a glass wafer.
Vidya Vijay (07:03):
Yeah, it still goes on an FRPCBA type substrate,
and we are okay with that.
Francoise von Trapp (07:07):
So finding any of the defects in the
package itself that has theglass is not any different than
any other kind of package?
Vidya Vijay (07:15):
Because those type of uh substrates, right?
Yeah, that is not something wecan directly inspect on optical.
It gets packaged onto a leadframe or a something and then
goes on the PCB.
Okay.
So that we can inspect.
Okay.
Or anybody.
It's true for anything optical.
Right.
So all of that is like you'relooking at wafer level, then it
gets diced and stuff, right?
And then that goes on to sometype of molding or something,
(07:38):
and it goes on like a PCBA.
Right.
So even like uh system on chip,we have the advanced packaging
on an iPhone, right?
So it's not completely on aPCBA, but it's all made on a
different FR4 substrate.
There is no more glass on thatlevel, right?
Because you can solder on todifferent components.
Francoise von Trapp (07:54):
Okay.
In terms of inspection forthese types of packages in the
PCBA process, what are youfinding is the best method of
inspection for that?
Vidya Vijay (08:04):
So there are multiple methods of inspection,
but optical is the easiest andfastest, right?
Anything you can see with thesystem, you can automate that.
And now we have the AIalgorithm and stuff.
So to make it faster, the cycletime is also important.
Optical is way to go when youare able to see the defect, even
(08:24):
a smaller defect.
If the machine can see it, wedefinitely can automate it and
it can be an AOI typeinspection.
And when you have voids or youknow, you're looking at multiple
layers, then we have to go toeither acoustic or X-ray type uh
inspection.
Francoise von Trapp (08:40):
Okay, so we've talked about this at the
wafer level packaging level.
Are you using all of thesedifferent types of inspection
even into this PCBA?
Is it just that the aspectratios, the sizes change, get a
little bit bigger?
Vidya Vijay (08:53):
In the PCBA market, it's generally usually AOI and
X-ray.
X-ray, okay.
And you know, there is very fewacoustic, but the FR4, it's not
very good for acousticwavelength to penetrate through.
I see.
So it's mainly uh AOI and AXI.
Francoise von Trapp (09:08):
Okay.
Now let's talk specificallyabout AOI.
You talked a little bit aboutthe benefits because you of the
the speed and finding thingsquickly.
When else would you choose AOIas your method of inspection?
Vidya Vijay (09:21):
Anything you can see, cycle time, and also about
uh a lot of automated defectclassification and so on.
Francoise von Trapp (09:29):
And is this for sorting and taking the
device out of the productionline, or is it an option
opportunity for repair andreplace?
Vidya Vijay (09:39):
Yeah, it's option to repair, not just sorting good
and bad.
Okay, but it's a completecycle.
And uh you can feed theinformation back to, say, for
example, at the stencil level,if something is off and you can
do some predictive maintenanceand catch a bad lot from being
made.
You know, being fast and beingin line in the system can give
(09:59):
us that benefit.
And this is all non-destructiveas well.
It is everything isnon-destructive.
That is true with our acoustic,uh, optical as well.
Okay.
Francoise von Trapp (10:10):
So let's talk about a new product that
you introduced to the market.
Can you tell me about that?
Vidya Vijay (10:15):
What we've been going towards is like we have
our very high tiered approachfor our AOI product portfolio.
With being our five micronsolution, uh 5 micron resolution
with our SQ 7000 Plus thatwe've launched last year.
And now we are launching ourmid-tier SQ 5000 Pro that's
being launched in ProductChronica.
(10:36):
And uh this system now has asensor with four cameras and a
projector.
It's basically a three-phaseprofilometry sensor.
What is new here is we havetrue RGB on the side cameras.
We can make auto-defectanalysis a lot better.
We can see as small as solderballs on a small solder balls on
a solder pad.
Very high-resolution systemhere, completely automated with
(11:01):
uh both 7 micron and a 10 micronuh resolution, two different
types of sensors for the samesystem and a much larger field
of view.
So we can go, it's almost uhtwo times the field of view.
And when compared to our Lexiproduct, it is also 30% faster.
Okay, and so how about thethroughput?
Uh so the cycle time, becauseit is 30% faster, based on the
(11:24):
boat size, it's gonna give youyour cycle time.
Based on the boat size and thenumber of components you have,
is gonna uh help with thethroughput.
Quite high throughput as well.
Francoise von Trapp (11:34):
So a little more specifically, can you
explain what challenges theSQ5000 Pro targets and what the
solutions are?
Vidya Vijay (11:43):
Yeah, SQ5000 Pro is our newest product that we are
launching, and it has a sensor.
This is our first productfamily with uh true RGB on the
side uh for the site cameras.
What that's helping us isprovide higher uh quality uh
images, and that's going to helpus with a lot of AI defect
(12:04):
analysis.
So, right now we do the AIautoprogramming.
A lot of AI autoprogramming, AIfeatures are included in all of
our AI systems.
Having a better high-resolutionimage definitely helps with
defect classification as well.
Francoise von Trapp (12:18):
So explain to me a little bit.
You're doing opticalinspection, and you so you're
you're basically using cameras,and then you have AI algorithms
within that that can identifywhat the defects are.
Is that what you're saying?
Yes.
Vidya Vijay (12:32):
Okay.
So the type of sensor that weuse in our most of our uh SQ
systems right now arethree-phase profilometry
sensors.
You project a fringe patternfrom top.
So based on the type of targetand the height structure, uh
it's going to reflect the lightuh differently.
And these these lights arecaptured by the four cameras on
(12:52):
the side, and then we use theseimages now to figure out uh what
the 3D height map looks like.
Okay.
Okay, so that is how generalthree-phase profilometry in a
very quick version works.
Okay.
And uh with these images now,we are able to, because we have,
you know, we are looking at thecorners, we can do a lot of
(13:12):
corner fill inspection we talkedabout.
We also have our proprietary uhMRS, um, multi-reflection
suppression algorithm.
Uh that helps with, you know,say, for example, something is
shiny, we are able to filter outthose noise with our
algorithms.
So we do have uh we call oursensors MRS sensors, okay, very
(13:33):
specifically for that.
Francoise von Trapp (13:34):
Okay.
Okay, so um you'redemonstrating here with this
tool?
Yes, we do.
Is it all um available on themarket yet or is it still in
qualification?
Vidya Vijay (13:45):
It's fully launched and it's available for sale in
the market now.
And so where can people go tolearn more of this?
Uh please go to Lots and Testand Inspection.
Our website has a lot of videosand uh brochures about all our
AOI products and actually acrosstest and inspection, all of the
product information isavailable in our website.
Okay.
(14:05):
Well, I appreciate your timetoday.
Thank you so much, Vidya.
Thank you, Francois.
It was great talking to youtoday.
Francoise von Trapp (14:11):
Thank you.
Bye.
Next week on the 3D InsightsPodcast, we'll be celebrating 50
years of Semicon Europa,featuring conversations with
Christian Koich of ESMC and LukeVandenhoe of IMAC about global
collaborations for Europeaneconomic resilience.
(14:32):
There's lots more to come, sotune in next time to the 3D
Insights Podcast.
The 3D Insights Podcast is aproduction of 3D Insights LLC.
Hi there! I'm Francoise von Trapp, and
this is the 3D Insights Podcast.
Hi everyone.
This week we are recording livefrom Productronica in Munich,
Germany, and we are talkingabout the importance of optical
inspection in microelectronicsmanufacturing.
(00:44):
Now, this year we've beentalking with Nords Intestine
Inspection in a series ofepisodes about the full spectrum
of inspection and metrologytechnologies.
We had an episode on acousticmicroscopy, one on planar CT,
and most recently on X-raymetrology.
But today we're speaking withVidya VJ on the role automated
(01:06):
optical inspection plays acrossthe microelectronics
manufacturing spectrum andspecifically around printed
circuit board assembly.
Welcome to the podcast, Vidya.
Thank you.
I'm glad to be here.
Now we talked on the podcast afew years ago, I think, in
Semicon West.
For the front end sensors, forsure.
(01:28):
Right.
Yeah.
Vidya Vijay (01:29):
We talked about some vapor scent sensors that is
also part of our solution.
Francoise von Trapp (01:33):
Right.
Vidya Vijay (01:34):
So how has Product Tronica been for you this year?
Francoise von Trapp (01:36):
Here we are, it's the first day.
It's been quite good at Productronica, very busy year.
Vidya Vijay (01:42):
So any difference this year than other years that
you're noticing?
I mean, uh it's the goodquality of audience the very
first day.
I think that's a that's a bighuge difference for us.
So you're not exhibiting overat SEMICON Europa, which is
happening concurrently.
We don't have our own booth.
We are with our distributor.
We do have our products thatare in the front end, WaferSense
products uh being displayed, aswell as our acoustic systems uh
(02:06):
at the booth in Semicon Europawith our distributors.
Okay.
Francoise von Trapp (02:10):
So here today now, can you tell me a
little bit about your role atNordson and then maybe um we can
talk a little bit more aboutwhat Nordson does in the PCBA in
general?
Vidya Vijay (02:21):
Yeah, definitely.
I'm the director for growth andstrategy.
Also manage all the productsfor optical sensors and
metrology division, which is ouroptical systems and wafer sense
on the front end side, as wellas our acoustic systems.
I'm an electrical engineer byeducation and training and uh
slowly moving on to managingproducts that actually inspect
(02:44):
uh from the front-end productsto the back end electronics
assembly.
Okay.
Francoise von Trapp (02:49):
We at 3D Insights generally focus on the
advanced packaging, 3Dintegration side of things.
But you know, we don't oftentalk about what happens after
that device is manufacturing andand what it causes downstream
when it goes to the printedcircuit board assembly, because
we're here we are delivering youhigher density advanced
packages.
(03:09):
So, what sort of challengesdoes this bring to the PCBA
environment?
Oh, definitely.
Vidya Vijay (03:17):
With the first of all, with the advanced
packaging, each component costand the value of each component,
how critically it's placed onthe boat, is very, very high.
Right.
And uh these components nowalso have multiple IOs, meaning
it could be a BGA with multiplebumps.
Now, when you have a BGA, youneed to make sure every bump is
(03:39):
sorted in place and there is noshots between each.
All three items the X, Y, thecoplinarity, how it seats, all
of that is important.
Not just one, not just lookingat the sorter stencil, but all
of these multiple IOs on theboard.
And you also have componentsthat are shorter and also even
the passives that are much, muchsmaller, 02, 01, 08, 04.
(04:03):
I mean, you know, things aregetting a lot smaller in terms
of passives with each of theI.O.
And the number of componentsnow you can have on a server
board more than 4,000 to 10,000components.
And you have these um uh biggeruh GPUs, CPUs, a lot of
memories, a different type ofconnectors, multiple variety of
(04:24):
components very closelypackaged.
Francoise von Trapp (04:26):
Right, right.
So you're getting a lot morecomplexity in the packages
themselves than used to be.
Yes.
Vidya Vijay (04:32):
What is driving that?
For advanced packaging, right?
We have system on chip typesolution, we have uh co-wast
type packages that now it'spackaged with multiple IOs,
right?
Multiple IOs.
These types of GPUs, when theygo on the board, now these are
extremely expensive GPUs, stillneed a little bit of outside
(04:53):
I.O.
connectivity and so on.
That is definitely creating avery expensive uh end product.
Then the inspection, thesoldering, the quality of
solder, the placement of thecomponent, all of that becomes
extremely critical.
And it used to be critical witha few micron offsets now that
these are coming down, comingdown slower, uh smaller and
(05:16):
smaller.
Francoise von Trapp (05:17):
What other challenges are you finding with
today's advanced packages?
Vidya Vijay (05:21):
So with the advanced packages, the other
thing we are seeing is a lot ofshiny components.
Okay.
So this is still like a camera.
When you see something shiny,you know, you're reflecting and
it is becoming part of youroptical chain as well.
So we are seeing a lot ofrequests for shiny components,
shiny dies.
That that's becoming a biggerchallenge, actually.
(05:41):
What's making them shiny?
The substrate, the die itself.
Okay, and we are also doing alot of system on chip type
inspection.
Okay.
So now that has exposures to alot of shiny components.
Okay.
And a lot of the RF componentsare also shiny.
Okay.
And what about like chiplets?
Chiplet packages.
(06:02):
Yeah, chiplet packages can alsogo on to different types of
boards.
All types of components at theend, you know, can go on its own
substrate or can go on an FR4type assembly.
And uh those can be inspectedas well.
And sometimes if it is just uhcompletely surface mode, no
leaks, uh there we need to makesure there is corner fill and
(06:23):
underfill properly to thesecomponents so they are making
good contacts.
Okay.
Francoise von Trapp (06:28):
So are there any challenges that you're
faced with concerning differentsubstrate materials like glass
core substrates as opposed tothe traditional laminates or
even silicon?
Vidya Vijay (06:40):
So mostly on the PCBA side, we are still seeing a
lot of FR4, but also a lot ofother substrates within the IGBT
can be a ceramic type uhsubstrate for those
applications.
Francoise von Trapp (06:54):
Okay, so what I'm thinking about is the
packaging, the packages that arecoming in that have been built
on a glass core substrate or aglass carrier or a glass wafer.
Vidya Vijay (07:03):
Yeah, it still goes on an FRPCBA type substrate,
and we are okay with that.
Francoise von Trapp (07:07):
So finding any of the defects in the
package itself that has theglass is not any different than
any other kind of package?
Vidya Vijay (07:15):
Because those type of uh substrates, right?
Yeah, that is not something wecan directly inspect on optical.
It gets packaged onto a leadframe or a something and then
goes on the PCB.
Okay.
So that we can inspect.
Okay.
Or anybody.
It's true for anything optical.
Right.
So all of that is like you'relooking at wafer level, then it
gets diced and stuff, right?
And then that goes on to sometype of molding or something,
(07:38):
and it goes on like a PCBA.
Right.
So even like uh system on chip,we have the advanced packaging
on an iPhone, right?
So it's not completely on aPCBA, but it's all made on a
different FR4 substrate.
There is no more glass on thatlevel, right?
Because you can solder on todifferent components.
Francoise von Trapp (07:54):
Okay.
In terms of inspection forthese types of packages in the
PCBA process, what are youfinding is the best method of
inspection for that?
Vidya Vijay (08:04):
So there are multiple methods of inspection,
but optical is the easiest andfastest, right?
Anything you can see with thesystem, you can automate that.
And now we have the AIalgorithm and stuff.
So to make it faster, the cycletime is also important.
Optical is way to go when youare able to see the defect, even
(08:24):
a smaller defect.
If the machine can see it, wedefinitely can automate it and
it can be an AOI typeinspection.
And when you have voids or youknow, you're looking at multiple
layers, then we have to go toeither acoustic or X-ray type uh
inspection.
Francoise von Trapp (08:40):
Okay, so we've talked about this at the
wafer level packaging level.
Are you using all of thesedifferent types of inspection
even into this PCBA?
Is it just that the aspectratios, the sizes change, get a
little bit bigger?
Vidya Vijay (08:53):
In the PCBA market, it's generally usually AOI and
X-ray.
X-ray, okay.
And you know, there is very fewacoustic, but the FR4, it's not
very good for acousticwavelength to penetrate through.
I see.
So it's mainly uh AOI and AXI.
Francoise von Trapp (09:08):
Okay.
Now let's talk specificallyabout AOI.
You talked a little bit aboutthe benefits because you of the
the speed and finding thingsquickly.
When else would you choose AOIas your method of inspection?
Vidya Vijay (09:21):
Anything you can see, cycle time, and also about
uh a lot of automated defectclassification and so on.
Francoise von Trapp (09:29):
And is this for sorting and taking the
device out of the productionline, or is it an option
opportunity for repair andreplace?
Vidya Vijay (09:39):
Yeah, it's option to repair, not just sorting good
and bad.
Okay, but it's a completecycle.
And uh you can feed theinformation back to, say, for
example, at the stencil level,if something is off and you can
do some predictive maintenanceand catch a bad lot from being
made.
You know, being fast and beingin line in the system can give
(09:59):
us that benefit.
And this is all non-destructiveas well.
It is everything isnon-destructive.
That is true with our acoustic,uh, optical as well.
Okay.
Francoise von Trapp (10:10):
So let's talk about a new product that
you introduced to the market.
Can you tell me about that?
Vidya Vijay (10:15):
What we've been going towards is like we have
our very high tiered approachfor our AOI product portfolio.
With being our five micronsolution, uh 5 micron resolution
with our SQ 7000 Plus thatwe've launched last year.
And now we are launching ourmid-tier SQ 5000 Pro that's
being launched in ProductChronica.
(10:36):
And uh this system now has asensor with four cameras and a
projector.
It's basically a three-phaseprofilometry sensor.
What is new here is we havetrue RGB on the side cameras.
We can make auto-defectanalysis a lot better.
We can see as small as solderballs on a small solder balls on
a solder pad.
Very high-resolution systemhere, completely automated with
(11:01):
uh both 7 micron and a 10 micronuh resolution, two different
types of sensors for the samesystem and a much larger field
of view.
So we can go, it's almost uhtwo times the field of view.
And when compared to our Lexiproduct, it is also 30% faster.
Okay, and so how about thethroughput?
Uh so the cycle time, becauseit is 30% faster, based on the
(11:24):
boat size, it's gonna give youyour cycle time.
Based on the boat size and thenumber of components you have,
is gonna uh help with thethroughput.
Quite high throughput as well.
Francoise von Trapp (11:34):
So a little more specifically, can you
explain what challenges theSQ5000 Pro targets and what the
solutions are?
Vidya Vijay (11:43):
Yeah, SQ5000 Pro is our newest product that we are
launching, and it has a sensor.
This is our first productfamily with uh true RGB on the
side uh for the site cameras.
What that's helping us isprovide higher uh quality uh
images, and that's going to helpus with a lot of AI defect
(12:04):
analysis.
So, right now we do the AIautoprogramming.
A lot of AI autoprogramming, AIfeatures are included in all of
our AI systems.
Having a better high-resolutionimage definitely helps with
defect classification as well.
Francoise von Trapp (12:18):
So explain to me a little bit.
You're doing opticalinspection, and you so you're
you're basically using cameras,and then you have AI algorithms
within that that can identifywhat the defects are.
Is that what you're saying?
Yes.
Vidya Vijay (12:32):
Okay.
So the type of sensor that weuse in our most of our uh SQ
systems right now arethree-phase profilometry
sensors.
You project a fringe patternfrom top.
So based on the type of targetand the height structure, uh
it's going to reflect the lightuh differently.
And these these lights arecaptured by the four cameras on
(12:52):
the side, and then we use theseimages now to figure out uh what
the 3D height map looks like.
Okay.
Okay, so that is how generalthree-phase profilometry in a
very quick version works.
Okay.
And uh with these images now,we are able to, because we have,
you know, we are looking at thecorners, we can do a lot of
(13:12):
corner fill inspection we talkedabout.
We also have our proprietary uhMRS, um, multi-reflection
suppression algorithm.
Uh that helps with, you know,say, for example, something is
shiny, we are able to filter outthose noise with our
algorithms.
So we do have uh we call oursensors MRS sensors, okay, very
(13:33):
specifically for that.
Francoise von Trapp (13:34):
Okay.
Okay, so um you'redemonstrating here with this
tool?
Yes, we do.
Is it all um available on themarket yet or is it still in
qualification?
Vidya Vijay (13:45):
It's fully launched and it's available for sale in
the market now.
And so where can people go tolearn more of this?
Uh please go to Lots and Testand Inspection.
Our website has a lot of videosand uh brochures about all our
AOI products and actually acrosstest and inspection, all of the
product information isavailable in our website.
Okay.
(14:05):
Well, I appreciate your timetoday.
Thank you so much, Vidya.
Thank you, Francois.
It was great talking to youtoday.
Francoise von Trapp (14:11):
Thank you.
Bye.
Next week on the 3D InsightsPodcast, we'll be celebrating 50
years of Semicon Europa,featuring conversations with
Christian Koich of ESMC and LukeVandenhoe of IMAC about global
collaborations for Europeaneconomic resilience.
(14:32):
There's lots more to come, sotune in next time to the 3D
Insights Podcast.
The 3D Insights Podcast is aproduction of 3D Insights LLC.
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