Canon lens factory tour interview: Fewer people, higher-quality, more affordable lenses – imaging resource


Shortly after the completion of this year’s installment of the annual CP+ tradeshow in Yokohama, Japan, IR founder and publisher Dave Etchells and Senior Editor William Brawley headed a couple of hours north to Utsunomiya, the capital of the Tochigi Prefecture, and home to Canon’s primary lens factory. The reason: Both gents were fortunate to be able to tour the facility for a behind-the-scenes look at how Canon lenses are designed and manufactured. But that wasn’t all — the cherry on top of the visit was an opportunity to sit down for a Q&A session with senior executives from the company to pick their brains about the nuances of lens design and manufacture, and how cutting-edge technology promises to bring us technology promises to bring us even better glass with yet more affordable pricing.

For the session, Dave and William were joined by Canon Inc.’s Masato Okada, Executive Officer and  Deputy Chief Executive of Image Communication Product Operations; Shingo Hayakawa, Deputy Group Executive, ICB Optical Business Group; and Kenichi Izuki, Plant Manager, Utsunomiya Plant. Since the interview was conducted through an interpreter, our transcriptionists were unable to ascertain precisely whom was the source of any given answer, and so we have marked all responses as coming from Canon throughout.

Without any further ado, let’s get down to the interview!

 

Dave Etchells/Imaging Resource: Thank you very much for the tour, for lunch and for this opportunity to talk with you. It’s a little hard to think of questions so quickly after seeing it!

<laughter>

Canon: Could we start with a question? What did you think of the tour?

DE: Ah, we liked it very much. We found the automated assembly and testing was interesting…

William Brawley/Imaging Resource: Very fascinating, yeah. The complexity required to go from the blanks and then through that whole automated process, and just the intricacies of that process were very interesting.

DE: I had seen normal lens normal lens polishing before, mechanical machines, but never automated like that. And it was very impressive to us that the head optical meister, Saito-san, would manually make the masters. Regular assembly was not as interesting to me personally, because I’ve been to two other lens factories in the past, but I think for people who have not seen it…

WB: Yeah, I’ve never seen it before!

 

HUGE news – test data stored in every lens!

DE: And then finally, the automated testing was very interesting to us. I was especially interested in what you told us about how the testing data is going to be stored in the lens. And the storing of the testing data is happening now for the 16-35mm Mark III?

Canon: Yes, it is.

DE: Are there other lenses that are also currently having that data stored in them?

Canon: The new lenses we’ve introduced in the last five years all have this chip data.

DE: In the last five years?!

Canon: In [these] five years. The ones before that do not, but the ones released in the last five years [do].

DE: Wow! Has the amount of data from five years ago to today changed? Is there more data stored now than when you first started doing it?

Canon: I can’t go into the details of how much, but we are saving more and more data.

DE: More and more over time, yes. So you said you are working on having cameras able to read that data and use it at some point. Do you have any idea how much longer it will be before we can do that?

Canon: <laughs> So the actual data that’s stored in the [lens] chip, that’s probably not actually something that the end users will be able to tap into, but what we are actually trying to introduce is for that data to help the users to get the last part of the image processing. So that’s the sort of the service we are looking to develop and introduce.

DE: Yes. Not that the users would take that data, but i’m thinking that the camera would be able to use it to correct the lens.

WB: Like real-time lens corrections?

Canon: So it’s not so much that the data will work to help with the lens adjustment [during manufacture], per se, but it’s about each lens [having] its own unique data. In other words, it would have its unique, quirky characteristics, which might actually have an impact on the end result. And what that data will help [us do] is to actually take this quirkiness and the characteristics of that particular lens into account to produce the optimal image at the end. So it’s about helping us with the image processing of the data.

DE: Yeah, that’s what I was thinking it would do; I was thinking that it could correct distortion…

WB: …specifically for that lens.

DE: …or even maybe like spherical aberration or something. It could apply different sharpening operators in the center of the lens versus the edges; or different amounts for different focal lengths or apertures or whatever.

Canon: At Canon, we always feel that we don’t have to rely on image processing technology or applications. We are always trying to make [it so] that our products can produce and take the photos at the highest quality at the initial stage. So obviously, if we can produce each lens to its ideal spec, to that very point, it would be perfect, but it’s not the case in an imperfect world. We do have a slight aberration breath, if you will. So what we will do is make sure that the lens will try to meet that ideal quality, but we intend to [account for] the aberration breath. We will have the data processing to make sure that it does reach the fine quality that we’re known for.

DE: So small variations, but then you can tighten that in the camera.

Canon: So, in other words, it’s about taking that production [which] always has a slight degree of variance in what it gives us in the end product. So what we will do is incorporate this image processing technology and application to allow us to achieve that end result that’s to a high quality that we always look for.

DE: And will that be done in-camera or in an application like Digital Photo Professional?

Canon: So yes, at the moment, most of our cameras would actually rely on the DPP application as you mentioned to actually do that final image processing. But eventually, in the future, we would like to have the function inside the camera. And some of the latest ones already actually do have this function.

DE: They have the processing in the camera for these lenses? And so that data’s actually being used right now by some cameras?

Canon: In terms of having that quirkiness to be incorporated, [no] that is not actually incorporated at the moment. We aren’t able to actually use that exact unique data for each lens for the [image quality] adjustments that we were just talking about. But we do have a sort of similar system in place where we do take into account certain unique characteristics of that particular [model of lens] to do that adjustment. So we’re on the way to actually making it to uniquely adjusting future lenses.

DE: And you say some of the characteristics of that line, so it would be data that’s characteristic for instance of all 16-35mm [lenses], or all 400mm f/2.8’s, or whatever?

Canon: There is data that’s actually saved, for example for the 16-35mm, that is saved onto that. The last inspection that we saw at the end of the tour, that data actually is set for something that’s already being stored for the moment. But that particular unique data for that lens is actually not being used for that adjustment process, per se. But we are using the stock data for particular [products], for example the 16-35mm, to do the [image quality] adjustment. So it’s like a gradual step of getting to that point of being able to adjust for that [individual lens].

DE: So there’s sort of generic or average data that’s an average of all the 16-35’s, and that data is being used to correct?

Canon: So [the] production site [has] a [potential range of inaccuracy]. So we’re doing adjustments at that level [to correct for generic defects] and then we will move into the future of where we do the adjustments for each unique lens. This is where they are now.

DE: Very interesting. You said so some cameras do that — which cameras in the line now use that data?

Canon: So Digital Photo Professional supported the Digital Lens Optimizer [data] in software in the past, and still we support that. The 1DX Mark II achieved in-camera RAW conversion to JPEG [using Digital Lens Optimizer corrections/adjustments], but not real-time JPEG shooting. But the 5D Mark IV enables the real-time JPEG [compression] applied to the [results of the] Digital Lens Optimizer [algorithm]. That’s the first one. But as we explained, it’s not [using the] unique, [individual] lens data.

DE: It’s just “This is what a 16-35mm does”, or “This is what the theoretical 16-35mm does” and so it’ll adjust based on that, just not on the individual [lens]. Yeah, that’s extremely interesting. It seems to me like this is a good argument for people to buy Canon lenses to use with Canon cameras!

So we were very interested in the automated testing process that we saw at the end. How long ago did that start? Was that also about five years ago; did that coincide with when you started being able to save the data?

Canon: A little [earlier] than that.

DE: So you were automating, and then it was “Aha, we can save the data!”?

Canon: Yes.

This is a big, BIG deal…

(An extended editorial note, by Dave Etchells)
This is potentially HUGE news; the end of sample variation? Every lens will have minor quirks and variations, even within a tightly-controlled production process. As we’re all aware, some samples of any given lens are better out of the box than others. With the highest-quality lenses from the best manufacturers, this “sample variation” will be small, bit it’s always there; even the best-controlled production process has to have at last some tolerance built into it, or the yield would be zero.

As Canon points out, they don’t intend to rely on software to correct problems after the fact, but there’ll always be some “quirks” (as they call them) in each lens, relative to the theoretical ideal of the lens design itself.

Related to this, some lens designs can be extremely difficult to manufacture, because they push production tolerances to the limits of what’s attainable, so yields on them are low. (I’m aware of at least one advanced lens by another manufacturer where this is the case; it’s a difficult design to manufacture, so theyr’e having a hard time keeping up with demand.) 

It turns out that Canon has been storing testing data in each lens’s internal memory for years now, adding more and more detail over time, as the capabilities of their automated testing have evolved. While this “quirks” data isn’t being used yet, the potential is there to correct for the minor quirks and manufacturing variation from lens to lens, either in host software like DPP (Digital Photo Professional, Canon’s RAW-processing software) or even the camera itself. Fully implemented, this could let Canon Lenses on Canon bodies approach perfection relative to the lens designs themselves. (That is, when used on a Canon body or with DPP RAW conversion, every lens off the line could perfectly match the theoretical ideal of its optical design.)

While they were very clear that they don’t intend to rely on image processing to correct for basic lens performance, it does seem that this kind of per-lens processing might make it easier for Canon to push the boundaries of what’s possible in the fabrication and assembly process itself, allowing for even more advanced lens designs that aren’t possible today.

It’s important to note that this goes far beyond current “lens corrections”, as provided for by generic profiles for sharpness, distortion or CA. As we’ve seen in our own lens testing, things like CA and sharpness can vary unevenly across the frame, with some lenses being off in one direction, and others off in the opposite. (That is, one lens might show decentered sharpness favoring the right side, another of the same type might favor the left.) While generic lens profiles can improve average performance, with a decentered lens, they could make one side a bit better, but the other side actually worse.

While I can’t talk in detail about how Canon tests lenses, let alone what their test targets look like, it doesn’t require any special knowledge to realize that the test software will be looking at and recording data for the entire frame, so it can tell if one corner is a bit softer than the others, if the CA variation across the frame is different from what’s theoretically predicted by the optical design, etc, etc. 

While Canon’s lens-manufacturing prowess is literally second to none, the ability to compensate for these minor variations between lenses and within the frame could bring another whole level of optical performance.

Canon gave no indication of when this kind of per-lens image processing might make its way into DPP, let alone the cameras themselves, but I bet we’ll see it sooner than later, given that they actively disclosed it in this tour and interview.

Fully implemented, this will be a powerful argument for Canon camera owners to stay loyal to the Canon brand for lenses as well.

 

Testing individual lens elements vs assemblies vs final test

DE: And so the automated testing that we saw was one complete, assembled lens. What do you do for quality control to characterize the individual elements as they come off of the polishing line? How do you measure those to make sure that they’re in-spec?

Canon: So the last part that we saw was the “final-final” check of how it would work. So we would have another stage before that where we do a slight adjustment for each of the lenses, where we actually have a certain adjustment specification that the lens should meet. So that sort of quality control assurance is done at that stage, before going into that final check.

DE: And is that testing sub-assemblies or do you optically test the individual lenses before they go in? Or do you do a statistical sample of a batch that comes off [the production line]?

Canon: We would have a certain optical adjustment that would happen beforehand for each of the lenses. So it won’t be just a sub-sample from the batch. We would do it for all of the lenses that come out to make sure that the optical adjustments are to the spec.

DE: So you’re 100% testing each individual lens to make sure that it meets spec?

Canon: Yes.

DE: And is it an optical test, or is it a profile test with a probe to check the lenses?

Canon: So all the assembly of the floating part would happen before that, and then you would actually go into the phase of doing the actual optical adjustments.

DE: Oh, so you’re testing assembled lenses, not individual elements?

Canon: In terms of the optical inspection, it would happen as we do the assembling itself. For example, if the lens is decentered and we need to adjust the centering of the lens, we would actually do the adjusting in the process of the assembly and then actually test it as it is assembled.

WB: So you do probe profiling of the individual elements and then once it passes that, then they assemble and they test it optically, and then make adjustments as necessary?

DE: So, individual lenses that we’re going to stack up, but the individual lens is tested by probing?

Canon: Aspherical lenses, yes.

DE: Aspherical lenses you do probe, but non-aspherical lenses, you can assume from the production process that they are going to have the right shape, that they don’t need to be tested?

Canon: So we do light testing [with] an interferometer.

DE: Oh, an interferometer! So you have like a master and then an interferometer to check. So has the automated testing really affected just the final assembly? With the grinding process, it’s always just been interferometric measurement, and so there hasn’t been a change over time, or has there been any sort of quality control improvement that could feed back into the conventional grinding process? Where that question came from was thinking that there’s the automated grinding and it would check each one and if it was a little bit off one way, then it could adjust the grinding for the next one.

Canon: The second gentlemen who we saw downstairs, when he was talking about the automated process, said that when we actually see that the [divergence from] the specification, that the adjustment is reflected from the next lens. That’s how the process is learning to kind of reflect that.

DE: Can you do something like that with the conventional, manual grinding process? If you grind a batch of lenses, look at it with the interferometer and it’s maybe a little one way or the other, do you adjust then, the same as the automated machine does?

Canon: In a way, we’ve actually always been having those step-by-step inspections with an amount of human process, if you will. What we’ve been doing in the automation is one thing, but in this process of how we create the lenses by hand, we’ve always had the inspection stages of each step by step to make sure that it does reach that level of specification that it requires, and if it’s not to the bar, we would actually go back to adjust it accordingly.

DE: So [it’s] really the same process, it’s just done manually by a human as opposed to the computer figuring it out?

Canon: Yes.

 

Automation: Not just mass-production, but mass customization

WB: I have a related question to that: Will there be a point in time when all of Canon’s lenses undergo an automated production or is there always something that’ll require a human touch? It sounds like the optical checking process might still need to be manually checked [for some lenses].

Canon: We are looking to actually introduce more automation; we’d like to go fully automated. And what we would mean is that not just for the mass-produced lenses. We mean mass-customization. For mass-produced lenses, for like 3000-5000 [units] per month, that would be something we could accommodate in the near future. But we are looking to introduce that [even for lots with just] 10-20 units per month. We’d like to create a machine where it can cater to the different lens specifications according to the lot that would come in. So it’s a small lot, but still we’d like to go for full automation. But having said that, the 0.3 micron precision that we were talking about with the Takumi experts, that’s actually something for the 4K or 8K level of resolution. But obviously technology is evolving, so we might see [higher] resolutions coming in [the future], and more precision required. So in other words, we need to expect the Takumi experts to up their game, if you will, to maintain the demands that come into the future. And in the factory next door, we have something called the 30-meter telescope that we’re producing, which has an incredibly large lens.

DE: Oh, yeah.

Canon: Obviously for things like that, we would still need to have that Takumi expert to come in.

WB: Yeah, there’s no machine for that yet!

<laughter>

DE: That’s very interesting. So what that means is that if you can achieve sufficient automation, it will become efficient to produce specialty lenses that people really want, but it’s [only] a very small group of people. With the full automation, you can produce lenses like that efficiently, and so for a good price?

Mass customization? Another Really.Big.Deal.

(Editorial note by Dave Etchells)
This is another really big deal. Extreme automation doesn’t just mean cheaper mass-produced lenses, but also that it will be practical for Canon to produce lenses with much smaller market demand. This would open the way for lots of really interesting, niche-market lenses that just aren’t feasible today, and over time could radically expand the range of EF lenses. Rather than needing to produce tens of thousands of a given lens per year in order for it to be profitable, they could make lenses that only a couple of hundred people might buy in a given year.

How often have we heard virtually every manufacturer say “Yeah, that would be an interesting lens, but there’s just not enough demand to justify us making it”? There may not be big markets for any given speciality lens, but the existence of a range of them in EF-mount could be a strong reason for people to choose Canon over other lens/body systems.

 

The role of the Takumi experts

Canon: If the Takumi experts have developed the exact specification [for manufacturing the lens] for the exact rotation, the exact pressure, the exact ways to do the polishing and grinding, and that’s the knowledge and intelligence that we have developed, which is a strength of Canon. That learning is something we are actually incorporating into our machines, and to help to maintain that quality that Canon is known for, to be able to produce those lenses at more of a greater scale and more efficiency. In terms of just materials, we use over 100 types of material [with] different levels of hardness of the actual glass.

DE: 100 different glasses?!

Canon: …We’re talking about quite a vast amount of variety in terms of how we do it. But obviously, different lenses would require a different curvature, different [element] sizes, etc. And so we would have a set of standards that we would actually allocate for each of the lenses, and what we are looking for in the future is for the machine to be able to have this in itself as a [stored] data. So when this lens comes, [the machine] knows how to do this kind of curvature, this kind of size. So that’s the sort of automation we are looking to create.

DE: That was actually my next question, was how does the human skill get incorporated? And so it’s things like “For this shape, this size, this glass, how much pressure, how much do I move like that or like this, or how fast it rotates”, all those sorts of things.

WB: Yeah, how do you translate that [into something a computer can perform]?

DE: Well, I’m kind of amazed that even the humans can know that in the first place, if you have 100 different glasses and you know lenses of all these different sizes and shapes, and they somehow know how to polish each one! It’s amazing to me.

<laughter>

Canon: So I guess that’s a testament to our 80 years of history of building those skills over the years. And Saito-san, who you met, he joined Canon when he was 18 years old. At that time, he didn’t know [anything about lens manufacturing], but then he started learning from his bosses, going up the hierarchy. So we have a hierarchy of experts that we build up. Somebody who is talented will get that track to be able to develop and ascend to the next level, and the next level, and then they finally reach this Takumi expert level. And we’ve always had that as the skills that we pass on through generations of employees that we have had over the years, as well as keeping the data of that. So [we are] making sure that we have human side of skills, continuing on to build Canon skills as well as the data side to help up make sure we can actually leverage this as we go forward.

WB: And on average, how long does it take for a meister to be completely sufficient in their area?

DE: Depends on how smart the meister is…

<laughter>

Canon: 30-35 years. It took Saito-san about 36 years for him to become a meister, he just became a meister maybe in the last year or two years ago.

DE: Oh really, just a couple of years ago? Wow, that’s amazing!

 

Is Fluorite still relevant?

DE: Now, this is completely nothing to do with what we saw today, but it was just something that occurred to me as we talked about grinding lenses. I guess with modern glass, you have less need for fluorite lenses now? But I’m curious though, fluorite is so different from glass, what do you have to do to grind it? Is it a very different process, and if so what’s different about the processing? Fluorite lenses are very expensive — is that because of the raw material, or is it because of the processing is so difficult?

Canon: The actual raw material is not that expensive, but it has to do with the molecule complex of the fluorite as opposed to the glass. The molecule complex of the fluorite, the actual molecules are actually aligned nicely as opposed to glass where it’s all scattered about. And the processing stage is quite different. With glass you have the powder that you heat, as opposed to fluorite, it takes more of a slower process of making sure to treat the molecules properly. So in other words, because that process takes a longer time, that’s why it turns out more expensive. But it’s not actually the raw material that’s actually different in pricing.

DE: Hmm.

Canon: You saw the lens processing today, but in terms of fluorite, the processing that follows, there’s another material that’s similar to fluorite, which has a similar characteristic quality, and for those kinds of materials, the processing is a bit more complex, hence the reason for the price difference. But we have the technology inside Canon that we can actually use the fluorite as well as this similar-quality material to be able to produce it into a glass that can be turned into a lens. So we have this technology in-house.

DE: You can create the fluorite material yourself from the raw material?

Canon: So like the glass sample that we saw earlier, where we mentioned that we buy [raw blank glass] from Hoya and Ohara, [it’s] similar to that. We buy [fluorite] in a similar format as well, but the processing technology that follows from that base is something that we have in-house.

 

How the heck do you automate something as complex as lens assembly?

DE: When you began to automate the assembly process,what did the beginning of that [process] look like? Did you have a machine that could just do one very simple operation and you began using that? Or did you wait until you had figured out a number of operations that could be done together before you first deployed it?

Canon: I would say from 10 years ago we started actually automating different small stages, modules or cells, you could call it, and what we did was develop those different little stages and sort of put that together.

DE: So you might have a machine that would just put the top on, and then another machine that would just do something else. And now one machine can do all of those.

Canon: Right.

DE: And in the tour [there was a] woman who, I think, was assembling a stack of lenses into an assembly. But our guide at that point said that that’s the next job that they’re going to automate. I’m wondering what was that job specifically that’s the next step, because I couldn’t really see what she was doing? And, what are the challenges in managing to take that human job and automate it?

Canon: So what she was doing was [attaching] the flexible circuit board and putting it into the connector. When the material is quite flexible and soft, it’s actually quite difficult for a machine to operate that. At the moment, we can do it with the machine, but it’s more costly and so it’s cheaper to do it with human hands. Hence the reason [why we haven’t automated it yet]. But still, that’s something we’re looking into.

DE: What’s next after that? Certainly it seems like there’s a large human element in assembling the individual lens elements into the subassemblies. Is that the next thing that comes, to be able to do that with machines?

Canon: We are working to make sure we can automate that next year.

DE: Next year, wow! Because there’s a lot of human labor in that. That’s a big part of the process in terms of time, I think.

Canon: It is, but we are looking to automate that next year.

 

Three current lenses are assembled by machine

DE: How many lens models use automated assembly now? We saw the 16-35mm f/2.8L III being assembled, but I’m wondering are there other stations for other lenses in the product line?

Canon: So the exact levels of automation that would happen vary, but in terms of full automation [there are] three types [of lenses with fully-automated production]

DE: And what are the other two types?

Canon: The 24-70mm f/2.8L II and 11-24mm f/4L.

DE: Ah, all wide-angle.

Canon: Yes. So for all the other lenses we have, they would have certain levels of automation, as well. Some have 30%, some have 80%. So there are elements of automation that are happening in our lens production across the board.

DE: It’s just a matter of how much in each one. And I guess, the goal is to eventually automate everything?

Canon: So in addition to that, obviously, we have mass customization for small lots of lenses. So in other words, one machine [is required] to be able to do different sorts of specifications, depending on what lens comes through. So that’s something worth looking into and we’re developing [it] as we speak.

DE: And we saw super telephotos being made, and also the 16-35mm. And obviously you have many other areas producing other lenses. I’m curious though, how do you organize the production? Is it that there is one group that just continuously produces one lens, or is it that you will take an area, configure it for making a particular lens, build a large number of them, and then reconfigure for a different lens? Do you do them in batches, or do you always have separate lines for them?

Canon: We have a flexible factory, you can say. We don’t have a certain section just dedicated to creating just that one [lens model], per se. We have the machines to be able to cater to more, we have a section [catering] to the different models that would come in [and] out.

DE: And I could imagine the telephoto section might always produce telephotos of some kind, because they would need special fixturing for that size lens, whereas another area might usually produce wide angle, etc.

Canon: For the lens processing that’s not the case, but in terms of assembling, obviously as you mentioned, they require different fixtures to be able to cater to the different sizes.

 

Assembly precision and Intranet of Things

DE: I’m curious about how much the assembly precision has increased, compared to say five years ago, in terms of the closer tolerances you can hold? And to what extent has that helped previously-existing lens designs. Have you been able to reduce sample variation due to the new measurement techniques, etc?

Canon: So we’re actually incorporating Internet of Things (IoT) in our factory, and what that would mean is that we have sensors built into the lenses as well. So that would allow us to really do the feedback from each lens as to what sort of adjustments are required, etc. And that actually helped us to reduce the variance of the different lenses. So yes, the precision is rising, and that’s based on the IoT that we’ve introduced.

DE: Interesting that it’s IoT. Everything is IoT, right?

<laughter>

Canon: I said Internet of Things, but it’s actually “Intranet of Things”.

<laughter>

DE: Intranet, haha, we get it. No internet!! Ah, that’s interesting.

Canon: So this final inspection data that we were talking about, we saw earlier and that’s actually obviously done with the glass processing as well as the assembly side of things. So whatever data that we can pickup at that point in terms of assembly would come from a slight variance in the parts, as well, and how it has been assembled. Those kinds of data are something that can tell us if there is a certain tendency for this kind of assembly. So we would actually have a feedback system where we would have that learning to be fed back so that we can make adjustments accordingly.

 

Not just final test data, each lens carries its full production history

DE: Wow, that’s very interesting. So the lens itself is carrying with it a history of the adjustments that were made as it was built, and then at the end you can download that data and see what needs tweaking in your process?

Canon: Yes, that lens would actually have a history of what kind of adjustments have been made, but the machines will also carry that as well. So what it would do is that it would be able to understand the history of lenses that have gone through, and if there’s any sort of variance with the parts and we pick up on some tendencies, we would feed [that] back as well. And as you mentioned, it does have that history, so it’s a matter of being able to keep that together. And also during those stages, we would have optical inspections that would come into play which would sort of help to keep to that level, so that at the end of the day the final product would be to the specification that we’re looking for.

Even older designs are more consistent now

DE: And so, the Intranet of Things, the machines that you’re using to calibrate the lenses and measure them, those are also reporting back to the cloud, to the mothership? So that means that it’s helped older lens designs too, not to perform differently, but to be more consistent?

Canon: We wouldn’t be able to say that for all [lenses], but yes, for some existing models, that’s the case. The ones you buy today [have more of a] slighter variance.

DE: I’m curious too, because here you have production and design and everything together [in one location]. How have advancements in your manufacturing capability affected your lens design? Can you build lenses today that you wouldn’t have been able to build before, or that you couldn’t control the tolerances on well enough? And has that allowed the lens designers more latitude?

Canon: Because we have the lens production site here and we have R&D on the other side, and we have a separate high-standard production site on the other side, we have these three parties in this proximity, which actually helps in all aspects. Because there is technology that gets built with [each] plant that we can actually learn from. For example, treating some hard materials like quartz, [we might have] processing techniques that we could actually incorporate into all lenses, for example. We are the largest optics business to have production sites as well as the design and R&D sites all together, and what we would always do is collaborate with each other to make sure that we can actually optimize our capabilities and whatnot. I strongly believe that we shouldn’t let the technology lead into the product. What I was taught [is that] it’s a dream. Let’s say we have this ideal product that we want to create: We bring the teams together to make sure that [they] rise up to that level to realize that dream. It’s not the technology that defines us, it’s the dream that defines us. So in other words, if we have a certain ideal spec of a product that we envision, we would actually get the teams together to work towards that dream to make it happen. So that’s the whole process that we have here.

 

FINALLY! Someone tells us how nano-coatings are made!

DE: I’m very curious about your nano-coating technology, because from illustrations I’ve seen it appears fundamentally different than how other people’s nanocoatings are made. Other nanocoatings [have] sort of clumps of stuff that gradually get more space in between them, whereas the illustrations I’ve seen of Canon’s nanocoats [show] spikes that have grown. Are these diagrams accurate, or is that just an artist’s [interpretation] showing the surfaces as little microscopic spikes?

Canon: It’s easier to understand, so that’s why we [showed spikes in the diagrams]…

DE: Ohhhh!

<laughter>

DE: I was thinking, “How do they grow the spikes? Is it an electrochemical or something…?”

Canon: It’s a comparative density. The base is quite a high density, but as you go up it gets lighter…

DE: And you showed [the spikes] to illustrate. I got it. <laughs> Are nanocoats generally an organic material, or are they inorganic of some kind? I’m not asking what it’s made out of [exactly] but I’m just curious, because I know they are very, very soft.

Canon: [It’s alumina] (Al2O3). Not organic.

DE: Oh, alumina, interesting. How do you make it vary in density… Is alumina [using] vacuum evaporation?

Canon: [It’s] spin-coated. This alumina is really small, 5-10 nanometers. It’s actually liquefied and we put it into a spin coating [machine], and then that gets dried, and then that get put into hot water. Then when it dries, it crystallizes, and when it crystallizes at that stage, the density level changes from the base to the top, so it’s quite highly dense on the bottom side, and the density gets lower on the high side. So that’s how we create that.

DE: So it’s spin-coated and dried, and there was some kind of carrier material, a liquid that it was in…

Canon: The initial liquid that you put the material in hasn’t been…

DE: That’s proprietary, yeah.

Canon: … and then that gets spin-coated, and then we dry it.

DE: So the spin-coating is a uniform thickness, and it’s a uniform density at that point…

Canon: Yes, it’s uniform.

DE: And then you put it in the hot water, and…

Canon: It gets dried, and then it gets put into hot water. And in the process of crystallization, the density varies as you go higher.

DE: So the water is helping it re-crystallize, and it sort of consolidates towards the bottom and that’s how the density changes?

Canon: The re-crystallization starts from the surface closer to the hot water.

DE: Huh, closer to the water… I would think that would be higher density then, if it’s recrystallizing…

Canon: If you look at the patent documents you could find more.

<laughter>

DE: Good, good, that’s what I will do then, yes. And you must also have US patents, so I can read it in English then.

Canon: Yes, we have US patents too. And that’s our time. Thank you!

• • •

(See much more in our Canon Factory Tour article!)

Canon Factory Tour

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