AI PCB on Korea Invest Insights

Why Korea Part 1: Why Korea Has So Many Semiconductor Substrate Companies and the U.S. / Europe Do Not

Thu, 07 May 2026 21:45:00 +0900

Why Korea series, Part 1. This is the strategic layer behind the AI PCB and Substrate Hub. Read it together with AI PCB and Substrate Thesis, Korea AI PCB Ecosystem: 10 Companies, and Samsung Electro-Mechanics AI Infrastructure Re-Rating.

📚 Subsequent parts: Part 2 — Korean Cosmetics · Part 3 — Samsung / SK hynix → Korean Economy Re-rating · Part 4 — $6.7B Inflows, Korea-Discount Dissolving or Value Trap?

There is a question sitting underneath the Korean AI substrate work that deserves its own note: why does Korea have so many listed substrate and PCB-adjacent companies in the first place?

The U.S. has Nvidia, AMD, Broadcom, Apple, Qualcomm, Synopsys, Cadence, Applied Materials, Lam Research and KLA. Europe has ASML, Infineon, STMicroelectronics, NXP and specialist materials companies. But if an investor looks for large-scale commercial semiconductor substrate manufacturers, the map quickly tilts toward Japan, Taiwan and Korea.

That is not because the U.S. or Europe lack engineering ability. It is because, over roughly 30 years, they chose a different layer of the semiconductor stack. The U.S. concentrated on design, software, IP and tools. Europe concentrated on lithography, power semiconductors, industrial chips and selected materials. The messy, wet-chemistry, high-volume work of plating, laminating, drilling, etching, testing and yield improvement moved to Asia.

The result is a regional compounding effect. Customers, material suppliers, equipment vendors, technicians, line managers, failure databases and yield-learning loops accumulated in Japan, Taiwan and Korea. That is why this niche is harder to rebuild than it looks from a slide deck.

TL;DR

The U.S. and Europe did not fail to make semiconductor substrates. They largely chose not to build the high-volume commercial substrate manufacturing base that Asia built.
Substrates are not just drawings. They are yield data. Large AI substrates require many layers, fine wiring, microvias, warpage control, chemical stability and reliability qualification.
Japan is strong because of materials and time: Ajinomoto Build-up Film, Ibiden, Shinko and three decades of high-end CPU substrate learning.
Taiwan is strong because TSMC, ASE, SPIL and the OSAT / foundry cluster created the natural customer base for Unimicron, Nan Ya and Kinsus.
Korea is strong because Samsung Electronics and SK Hynix created world-class local demand, while smartphone, memory and display manufacturing created the process culture needed for substrates.
Korea is not strong everywhere. Memory substrates are a structural Korean strength, but the highest-end AI accelerator FC-BGA market is still led by Japanese and Taiwanese incumbents.
The investment implication is not “buy every Korean substrate stock.” It is that Korea’s substrate cluster has a real historical base, but the company-level position differs sharply by product, customer, material dependency and yield history.

1. What Is a Semiconductor Substrate?

A semiconductor chip is tiny and extremely dense. A printed circuit board is much larger and coarser. The terminals on the chip cannot be connected directly to the board without an intermediate layer.

That intermediate layer is the package substrate.

Semiconductor chip
 |
Package substrate
 |
Main board / system board

The package substrate does three things:

Function	What it means
Signal routing	Carries data between the chip and the system board
Power delivery	Supplies stable power to high-wattage chips
Mechanical support	Protects the chip from heat, moisture, warpage and shock

The point is simple, but the manufacturing is not. Advanced substrates require many layers, fine traces, precisely aligned vias, tight copper plating, low-loss materials, warpage control and high reliability. In AI accelerators and server CPUs, the substrate can be large, high-layer-count and extremely unforgiving.

This industry is not about whether one can make a sample. It is about whether one can make millions of units at a yield that makes economic sense.

2. The Real Barrier Is Yield, Not the Drawing

For a non-specialist, the easiest mistake is to think of substrates as flat boards with patterns printed on them. That misses the real problem.

A high-end FC-BGA substrate is a multi-layer structure. Each layer has wiring. Layers are stacked. Holes are drilled and plated to connect layers. Materials expand and shrink with heat. The entire structure can warp. A tiny defect can kill the package.

As the substrate gets larger and the layer count rises, the number of defect opportunities rises quickly. A process that works for a small package can fail economically when the package is four times larger and twice as thick.

The hard question is not:
"Can you make one?"

The hard question is:
"Can you make it at stable yield, with repeatable quality,
through material-lot changes, customer design changes,
equipment drift and reliability testing?"

That kind of knowledge is not downloaded from a manual. It is learned from years of sampling, qualification, production failures, customer audits, material variation and line tuning. This is why substrate capability clusters geographically. Once the customer, material, equipment and people loops sit in one region, the region keeps getting better.

3. Why the U.S. and Europe Stepped Away

The U.S. semiconductor model concentrated on higher-return layers:

U.S. strength	Examples	Economic profile
Chip design	Nvidia, AMD, Broadcom, Qualcomm, Apple	High gross margin, asset-light relative to manufacturing
EDA and IP	Synopsys, Cadence, Ansys	Software-like economics
Semiconductor tools	Applied Materials, Lam Research, KLA	High-value capital equipment

Substrate manufacturing has a different profile:

Substrate manufacturing characteristic	Why it mattered
Heavy chemical process	Plating, etching, cleaning and wastewater management
Large capex	Dedicated factories, long qualification periods
Labor and process intensity	Skilled operators and process engineers matter
Lower software-like margin	Less attractive to U.S. public-market preferences
Environmental burden	Wet processes face stricter local constraints

This was a rational division of labor for a long time. U.S. companies could design the chip, control the software and own the equipment layer while Asian partners handled PCB, substrate, assembly and packaging. The problem is that a rational supply-chain decision became a strategic dependency.

IPC has been explicit about this gap. Its North American advanced packaging work argues that the U.S. has almost no capability to produce the most advanced IC substrates such as FCBGA and FCCSP, and that lower-end substrate capacity is also limited. The IPC report also describes barriers such as roughly billion-dollar factory requirements, long know-how gaps, weak sub-tier supply, raw-material gaps and workforce shortages.

Europe is a little different, but the conclusion is similar. Europe has AT&S, and AT&S is a real high-end PCB and IC substrate company. But even AT&S’s manufacturing map is global and Asia-heavy, with major production sites in China and Malaysia and a European competence center in Austria. Europe has expertise, but it does not have a broad, dense, high-volume substrate cluster comparable to Japan, Taiwan or Korea.

4. Japan: Materials Plus 30 Years of Yield Learning

Japan’s substrate strength starts with materials.

The key word is ABF, Ajinomoto Build-up Film. ABF is an interlayer insulating film used in high-performance package substrates. Ajinomoto’s official innovation history describes ABF as a standard material for high-performance CPUs, first adopted by a major semiconductor manufacturer in 1999, and developed from the company’s fine-chemistry expertise.

That matters because the substrate is not just copper wiring. The insulating material between the layers determines how fine the circuit can be, how stable the structure is, and how the substrate behaves under heat and stress.

Japan then added three decades of process learning:

Japanese node	Why it matters
Ajinomoto	ABF material standard for high-performance substrates
Ibiden	Deep history with Intel and high-end CPU / AI substrate customers
Shinko Electric	Long-standing high-end package substrate player
Japanese material ecosystem	CCL, copper, chemicals, tools and precision components

Domestic media and Bloomberg-linked coverage have described Ibiden as a dominant substrate supplier to Nvidia AI chips. Whether one uses the most aggressive market-share estimates or a more conservative wording, the direction is clear: at the highest-end AI accelerator substrate layer, Japan still has the strongest incumbent position.

Japan’s edge is not simply “good engineering.” It is the combination of material control, customer qualification history and yield data that started in the CPU era and now carries into AI accelerators.

5. Taiwan: Foundry and OSAT Cluster Pull

Taiwan’s path is different. Japan starts from materials and long CPU history. Taiwan starts from the semiconductor manufacturing cluster.

TSMC: foundry
ASE / SPIL: assembly and test
Unimicron / Nan Ya / Kinsus: substrates

Substrate companies do not grow in isolation. They grow near demanding customers. A foundry or OSAT customer needs samples, qualification lots, reliability testing, process changes and fast feedback. When the customer is nearby, the learning cycle shortens.

This is the core of Taiwan’s substrate advantage. TSMC, ASE and SPIL created the local production pull. Unimicron, Nan Ya and Kinsus grew inside that pull.

Market-research estimates show Taiwan and Korea running very close in total package substrate production share, with Taiwan often cited around 28% of 2024 production and Korea around 27%. Exact numbers vary by source and definition, but the direction is stable: Taiwan and Korea are not niche participants. They are central production nodes.

The Taiwan risk is geopolitical. The Taiwan advantage is that the customer cluster is one of the densest semiconductor manufacturing clusters on earth.

6. Korea: Customers, Mass Production and Speed

Korea’s advantage starts with a simple fact: Samsung Electronics and SK Hynix are local.

That matters more than it sounds. Strong customers make strong suppliers. Samsung and SK Hynix pushed local suppliers through memory, mobile, display and advanced component cycles. Korean substrate companies learned how to operate inside fast node transitions, strict quality systems and brutal cost-down cycles.

Korean substrate roots are not only in semiconductors:

Korean manufacturing base	What transferred into substrates
Memory semiconductors	High-volume production discipline, rapid generation transitions
Smartphones	Thin, dense, high-reliability board requirements
Displays	Large-area process control, chemicals, plating and precision handling
Electronics supply chains	Fast customer response and process tuning

Korea also has investment speed. When AI server substrates became a priority, Korean companies moved capital quickly. Samsung Electro-Mechanics, Daeduck Electronics, Korea Circuit and other PCB / substrate-adjacent companies sit inside a system where large customers, local engineers, material suppliers and capital decisions can align faster than in many Western environments.

This does not mean every Korean company is a winner. It means Korea has the industrial preconditions for substrate winners to exist.

7. Korea’s Weak Spot: The Very Top-End AI Accelerator Substrate

The honest version of the thesis has to say this clearly: Korea is strong in substrates, but not equally strong in every substrate category.

Substrate category	Korea’s position	Read
Memory substrates	Very strong	Linked to Samsung and SK Hynix memory ecosystems
Mobile substrates	Strong legacy base	Growth is slower, but manufacturing base remains
PC / consumer FC-BGA	Capable, but cyclical	More exposed to oversupply and PC cycles
Server FC-BGA	Catching up	Korean suppliers are entering more serious qualification cycles
Highest-end AI accelerator FC-BGA	Still behind Japan / Taiwan	Incumbent qualification and yield history matter most

The reason is time. Korean suppliers have shorter large-server FC-BGA history than Japanese and Taiwanese leaders. In the highest-end AI accelerator substrates, customer qualification, warpage control, large-body yield, material behavior and long reliability records matter.

That is why the opportunity is not “Korea takes everything.” The opportunity is second-source entry, custom ASIC growth and capacity tightness at incumbents.

Big Tech custom chips are important here. Google, Amazon, Meta and Microsoft are all trying to reduce exclusive dependence on one AI accelerator vendor. Those custom chips still need substrates. If Japanese and Taiwanese leaders are full, customers need qualified alternatives. That is where Korea’s opening sits.

8. U.S. Re-Entry: The Glass Substrate and Advanced Packaging Route

The U.S. now understands the dependency.

NIST and CHIPS for America have announced major advanced packaging funding, including $1.4 billion in final awards under the National Advanced Packaging Manufacturing Program and $300 million for advanced substrates and material research. NIST’s Absolics page also describes up to $75 million in direct funding for a Georgia glass substrate facility tied to SKC’s Absolics.

The strategy is revealing. The U.S. is not simply trying to copy Asia’s 30-year ABF substrate base overnight. It is trying to build:

U.S. re-entry path	Meaning
Advanced packaging R&D	Build domestic process and pilot capability
Glass substrates	Try to enter through a next-generation material shift
HBM advanced packaging	Use AI memory packaging as a strategic entry point
University / pilot-line ecosystem	Rebuild the people and process loop

This is both an opportunity and a risk for Korea.

The opportunity is that the current ABF / FC-BGA substrate era still favors Asian incumbents. Yield, customers and materials are already in Asia. The risk is that a material transition, especially glass substrates, can reset part of the game.

Korea is not badly placed for that reset. The country has deep display and glass-processing experience, and Absolics itself is SKC-linked. But the point remains: the substrate advantage is durable, not permanent.

9. Why This Matters for the Korean Stock Map

The fact that Korea has many substrate companies is not, by itself, an investment thesis. The useful question is why those companies exist and where their advantage stops.

The answer creates a better stock map:

Layer	Korean names	Why Korea matters
Large-cap anchor	Samsung Electro-Mechanics	FC-BGA and MLCC exposure with AI server relevance
FC-BGA / MLB balance	Daeduck Electronics	A more focused substrate / board exposure
Optional FC-BGA / SoCAMM exposure	Korea Circuit, Simmtech, TLB	More product-specific and qualification-dependent
High-end MLB	Isu Petasys	Network / server board exposure
CCL and materials	Doosan Electronic BG, Kolon Industries, Pamicell	Upstream bottleneck and low-loss material exposure

The AI PCB and Substrate Thesis explains why substrates are a system bottleneck. The 10-company ecosystem note compares listed Korean names. This Why Korea note adds the historical base: Korea has the companies because the customer, manufacturing and process-learning loops accumulated there.

That does not eliminate valuation risk. It just explains why the cluster is real.

10. Two Things to Keep Honest

First, Korea is not number one in every layer. Memory and mass-production substrates are a real strength. The highest-end AI accelerator substrate layer is still led by incumbents with longer server / CPU histories.

Second, the U.S. and Europe are not permanently absent. CHIPS funding, advanced packaging programs, glass substrates and HBM packaging investments are explicit attempts to rebuild missing parts of the stack. The time horizon is years, not quarters, but the direction is real.

The right conclusion is not “Asia owns substrates forever.” The right conclusion is: the current substrate advantage is the product of decades of accumulated production learning, and that makes it durable enough to matter for this AI cycle.

Final Note

Korea has more than ten listed substrate and PCB-adjacent companies because this capability did not appear overnight. The U.S. and Europe prioritized design, software, tools, lithography, industrial chips and selected materials. The wet, process-heavy, capex-heavy work of making substrates at commercial yield moved to Asia.

Japan became strong through ABF materials and 30 years of CPU substrate learning. Taiwan became strong through TSMC and the OSAT cluster. Korea became strong through Samsung, SK Hynix, memory, mobile, display and fast investment execution.

That is the real “Why Korea” answer. It is not national branding. It is industrial compounding.

For investors, the takeaway is practical. Do not treat every Korean substrate stock as the same asset. Ask which layer it occupies, which customer drives it, which material bottleneck matters, how long the qualification cycle is, and whether the company’s strength is memory, mobile, server, AI accelerator, CCL or low-loss materials.

That is how the Korea substrate map becomes usable: not as a theme, but as an industrial structure.

Source notes: This article uses IPC’s North American advanced packaging work for the U.S. substrate capability gap, NIST / CHIPS for America releases for advanced packaging and substrate funding, Ajinomoto’s official ABF innovation history for material background, AT&S official site materials for the European IC substrate footprint, and market-research estimates for regional substrate production shares. Research OS local market data was also checked for listed Korean substrate names as of May 7, 2026; the post’s thesis does not depend on short-term price action.

Disclaimer: For research and information purposes only. Not investment advice. Names cited are for analytical illustration; readers should perform their own due diligence and consult licensed advisors before any investment decision.

Samsung Electro-Mechanics (009150) Analysis: Mirae Asset's KRW 1.3M Target and the MLCC/FC-BGA Re-Rating Frame

Thu, 07 May 2026 18:10:00 +0900

Related reading: AI PCB and Substrate Hub, Samsung Electro-Mechanics AI Infrastructure Re-Rating, AI PCB and Substrate Thesis, and Korea AI PCB Ecosystem: 10 Companies.

Mirae Asset Securities raised its Samsung Electro-Mechanics target price from KRW 530,000 to KRW 1.3 million. The number looks dramatic, but the mechanism is simple: move the valuation year from 2026 to 2028 and apply a 37x PER, which Mirae Asset links to the early phase of the 2017 MLCC shortage cycle.

That makes this less a normal earnings revision and more a valuation-frame revision. The core debate is whether Samsung Electro-Mechanics should still be read as a cyclical electronics component company, or whether AI server MLCC and FC-BGA demand has moved it into an AI-infrastructure bottleneck category.

TL;DR

Mirae Asset’s target math is 2028F EPS of KRW 34,764 multiplied by 37x, or KRW 1,286,268, rounded to KRW 1.3 million.
The 37x multiple is the key assumption. It is not a normal-cycle multiple; it is a peak shortage-cycle multiple drawn from the 2017 MLCC shortage setup.
At the May 7, 2026 close of KRW 917,000, Samsung Electro-Mechanics already trades at 26.4x that 2028F EPS. That is above a normal upcycle frame of roughly 25x and close to the 2018 shortage-peak frame of 28x.
Shortage signals are visible: some MLCC lead times are reportedly 20-24 weeks versus a normal 10 weeks, 2Q26 MLCC utilization is discussed around 95%, and inventory coverage is cited around 4 weeks versus a normal 6 weeks.
FC-BGA is the more structural leg. Mirae Asset lifted its FC-BGA ASP assumption by 13%, and package-solution operating profit is forecast to compound strongly through 2030.
The stock is no longer undiscovered. Hana, NH, Meritz, iM, KB and Mirae Asset have all moved into the KRW 1.0-1.3 million target range. The remaining question is how much of the shortage multiple is already in the price.

1. What KRW 1.3 Million Actually Means

The target-price formula is straightforward:

Target price = 2028F EPS x target PER
 = KRW 34,764 x 37.0
 = KRW 1,286,268
 = roughly KRW 1.3 million

The arithmetic is not the thesis. The thesis sits inside two choices:

Input	Mirae Asset’s choice	Why it matters
Earnings year	2028F EPS	Pulls forward the Vietnam FC-BGA capacity contribution and the AI server mix shift
Multiple	37x PER	Imports the early 2017 MLCC shortage multiple into today’s AI MLCC/FC-BGA cycle

Moving the earnings base from 2026 to 2028 is already a large change. Mirae Asset’s EPS path, as reported by local coverage, implies roughly:

Year	EPS	Growth
2025	KRW 9,099	n/a
2026F	KRW 16,914	+86%
2027F	KRW 24,555	+45%
2028F	KRW 34,764	+42%

Using 2028 EPS rather than 2026 EPS almost doubles the earnings denominator. Applying 37x to that denominator turns an earnings upgrade into a re-rating call.

The question for investors is therefore not, “Is KRW 1.3 million possible?” A better question is, “What has to be true for a 37x multiple on 2028 earnings to become acceptable?”

2. The 37x Multiple Is the Debate

Mirae Asset’s reported historical PER frame can be summarized this way:

Frame	PER	Interpretation
10-year average	15x	Normal long-term electronics-component frame
+1 standard deviation	19x	Stronger but still ordinary upcycle
+2 standard deviations	25x	Normal-cycle upper band
2021 upcycle peak	22x	COVID recovery and component upcycle
2018 shortage peak	28x	MLCC shortage peak
2017 shortage early phase	37x	Market paying up before shortage earnings fully appeared

The 37x multiple is not a neutral number. It says Samsung Electro-Mechanics is entering a shortage cycle similar enough to 2017 that the market may again pay a peak shortage multiple before all earnings have been printed.

That may be right. It may also be too aggressive. A 37x multiple on a company whose 10-year average is closer to 15x requires a very specific regime: tight supply, visible pricing power, customer prepayments or volume commitments, and margin expansion that survives more than one quarter.

This is why the article should be read as a conditional re-rating framework, not as a mechanical target-price endorsement.

3. Where the Current Price Already Sits

Samsung Electro-Mechanics closed at KRW 917,000 on May 7, 2026 in the local Research OS market snapshot. Against the same 2028F EPS of KRW 34,764, that close implies:

Current implied PER = 917,000 / 34,764 = 26.4x

The scenario table looks like this:

Scenario	PER	Implied price	Distance from KRW 917,000
Bear case, EPS -20% and 19x	19x	about KRW 528,000	-42%
2021-style upcycle	22x	about KRW 765,000	-17%
Normal upper-band upcycle	25x	about KRW 869,000	-5%
Current close	26.4x	KRW 917,000	0%
2018 shortage peak	28x	about KRW 973,000	+6%
Mirae Asset frame	37x	about KRW 1,286,000	+40%

This is the most important practical point. The stock no longer prices Samsung Electro-Mechanics as a simple normal-cycle component recovery. At KRW 917,000, it is already above the normal upper-band frame and close to the 2018 shortage-peak frame.

From here, further re-rating depends less on “earnings are improving” and more on “the market accepts a 37x shortage multiple.”

4. Are the Shortage Signals Real?

The shortage indicators cited in the local report flow are meaningful:

Indicator	Normal level	Reported current level	Read-through
Some MLCC lead times	about 10 weeks	20-24 weeks	Lead time has roughly doubled
2Q26 MLCC utilization	not specified	around 95%	Close to full capacity
Inventory coverage	about 6 weeks	about 4 weeks	Inventory is being drawn down

These are valid shortage signals. Lead times stretch, utilization rises, and inventory falls. That combination is what gives price increases a path.

But the wording matters. The lead-time commentary refers to some global MLCC products, not necessarily every MLCC category. AI server MLCCs can be tight while commodity IT MLCCs remain less tight. The difference matters because the 2017 shortage cycle was broad. The 2026 cycle may be more AI-server-specific.

Samsung Electro-Mechanics’ own 1Q26 announcement supports the direction of demand. The company reported consolidated 1Q26 revenue of KRW 3.2091 trillion and operating profit of KRW 280.6 billion, with AI server, power and network demand driving growth. It also said demand for high-value-added FCBGA substrates for AI, servers and networks should remain strong in 2Q.

That is enough to say the AI-infrastructure leg is real. It is not enough to assume the whole MLCC market has already become 2017 again.

5. MLCC Price Hikes Are the Swing Factor

Mirae Asset’s upside logic depends heavily on AI server MLCC pricing. The reported scenario analysis frames the operating-profit impact roughly as:

AI server MLCC price increase	2026F OP uplift	2027F OP uplift	2026F component OPM	2027F component OPM
Base, no price hike	n/a	n/a	15.2%	16.3%
+15%	KRW 100.8B	KRW 184.5B	16.8%	18.9%
+20%	KRW 134.4B	KRW 245.9B	17.4%	19.8%
+25%	KRW 168.0B	KRW 307.4B	17.9%	20.7%

This is why 2Q26 matters. If AI server MLCC ASPs begin to move visibly, the shortage multiple becomes easier to defend. If utilization is high but pricing is slower, the 37x frame becomes more fragile.

The market has already paid for part of the pricing story. It now needs evidence that the price story is not just a sell-side assumption.

6. FC-BGA Is the Structural Leg

MLCC is the shortage signal. FC-BGA is the structural AI substrate signal.

Mirae Asset reportedly raised its FC-BGA ASP assumption by 13%. The logic is that raw materials remain tight, major suppliers are sold out, and customers are willing to support capacity through prepayments, volume discussions and pricing negotiations.

That last phrase should be handled carefully. “Customer support” is different from fully disclosed, legally binding purchase guarantees. Publicly available data does not provide enough detail to verify the size, duration or enforceability of those arrangements. The conservative interpretation is that customer behavior is supportive, but not all of the capacity expansion should be treated as risk-free.

Still, the direction is important for the broader Korea AI PCB thesis. If Samsung Electro-Mechanics can lift FC-BGA ASP assumptions by 13%, that is a read-through for the rest of the Korean substrate ecosystem:

Korean node	Read-through
Daeduck Electronics	FC-BGA and MLB exposure benefit if pricing remains firm
Korea Circuit	FC-BGA option becomes more valuable if high-end substrate demand persists
Isu Petasys	AI network MLB demand remains a parallel bottleneck
Doosan Electronic BG	High-end CCL pricing power is supported by downstream substrate tightness
Kolon Industries and Pamicell	Low-loss material demand becomes more durable if CCL tightness persists

This is why the report matters beyond Samsung Electro-Mechanics. It is one of the clearest large-cap confirmations that AI substrates are moving from a narrative into price, capex and margin numbers.

7. 1Q26 Was the First Accounting Checkpoint

Samsung Electro-Mechanics’ official 1Q26 numbers:

Item	1Q26
Revenue	KRW 3.2091T
Operating profit	KRW 280.6B
Revenue growth	+17% YoY
Operating-profit growth	+40% YoY

Local coverage also notes a KRW 71.4B one-off retirement-benefit cost tied to changes in wage-base accounting. Excluding that item, underlying operating profit is discussed around KRW 351.4B, which is materially stronger than the headline number.

The headline result already validates demand. The adjusted result validates the margin argument more clearly. The next checkpoint is whether 2Q26 shows:

Checkpoint	Why it matters
AI server MLCC price realization	Confirms that shortage can become earnings, not just lead time
FC-BGA ASP and margin	Tests the +13% ASP assumption
Package-solution OPM	Shows whether the business is moving toward mid-to-high-teens margins
Customer commitment details	Distinguishes demand-backed capex from ordinary capex risk

8. The Stock Is No Longer Undiscovered

Mirae Asset’s KRW 1.3 million target is the high-end call, but the rest of the street has also moved up. Reported target prices include roughly:

Broker	Target price
Hana Securities	KRW 1.0M
NH Investment & Securities	KRW 1.0M
Meritz Securities	KRW 1.02M
iM Securities	KRW 1.1M
KB Securities	KRW 1.1M
Mirae Asset Securities	KRW 1.3M

That matters. Samsung Electro-Mechanics is not a hidden second-derivative AI name anymore. It has been discovered by the market, and the valuation already reflects part of that discovery.

The May 7 flow also shows a divided tape: foreign investors were net sellers by roughly KRW 70.3B while institutions were net buyers by roughly KRW 47.2B in the local Research OS snapshot. That does not break the thesis, but it argues against treating the trade as a clean one-way crowding story.

9. What Could Break the 37x Frame?

The upside frame is clear. The failure paths are also clear.

Risk	Why it matters
MLCC tightness stays limited to a narrow product set	A narrow shortage deserves a lower multiple than a broad 2017-style shortage
AI server MLCC price increases lag expectations	Lead times do not automatically become margin
FC-BGA ASP lift is offset by depreciation or material costs	Capex-backed growth can dilute margins if pricing does not keep up
Customer prepayment and volume-support details remain vague	The market may discount the capex story if contract quality is unclear
Consensus becomes one-sided	With most brokers already constructive, disappointment can travel quickly
2028 EPS proves too far forward	Pulling valuation two years ahead increases duration and forecast risk

The most important distinction is between a real shortage and a priced-in shortage. Both can be true at the same time. The company can be in a strong AI component cycle while the stock already discounts a large part of it.

Final Note

Mirae Asset’s KRW 1.3 million target for Samsung Electro-Mechanics is not just an earnings upgrade. It is a claim about market regime. The claim is that Samsung Electro-Mechanics has moved from a mobile/electronics-component cycle into an AI-infrastructure bottleneck cycle, and that the market can value this cycle with a 2017-style MLCC shortage multiple.

The evidence is not imaginary. Samsung Electro-Mechanics reported a strong 1Q26, AI server and network demand is visible, FC-BGA pricing assumptions have moved up, and MLCC lead-time, utilization and inventory data point to tightness in high-end products.

But the price has already moved into a demanding frame. At KRW 917,000, the stock is around 26.4x Mirae Asset’s 2028F EPS, already above a normal upper-band upcycle multiple and close to a 2018 shortage-peak frame. The remaining re-rating requires the market to accept something closer to 37x.

For the broader Korea AI PCB thesis, this report is useful even if one does not accept the full 37x multiple. It confirms that FC-BGA, MLCC, CCL and low-loss materials are being discussed in pricing, capacity and margin terms, not only as a theme. That strengthens the logic behind the AI PCB hub, Daeduck, Korea Circuit, Doosan Electronic BG, Kolon Industries and Pamicell as linked parts of the same system bottleneck.

The next evidence window is 2Q26: AI server MLCC price realization, FC-BGA ASP, package-solution margins and more concrete customer-commitment language. Until then, the cleanest interpretation is this: the business has improved, the shortage signals are real, and the stock now requires a peak-shortage multiple to unlock the final leg of Mirae Asset’s target-price math.

Source notes: Samsung Electro-Mechanics’ official 1Q26 announcement reported KRW 3.2091T revenue and KRW 280.6B operating profit, with AI server, power and network demand supporting growth. MoneyToday/Daum coverage of Mirae Asset’s May 6 report cited the KRW 1.3M target, 13% FC-BGA ASP assumption lift, 2028 valuation-year shift, 20-24 week MLCC lead times and 95% utilization / 4-week inventory framework. Local Research OS market data confirms the May 7, 2026 close at KRW 917,000.

Korea AI PCB Ecosystem: 10 Companies Across FC-BGA, CCL, SoCAMM, Materials and Equipment

Tue, 05 May 2026 23:55:00 +0900

Sector map: This is the company-matrix companion to the AI PCB and Substrate Thesis and the AI PCB and Substrate Hub. The earlier thesis explained why AI substrates are a system-level bottleneck. This note asks which parts of the Korean ecosystem carry the better business quality, and where the factor setup still looks less fully priced.

TL;DR

The strongest accounting signal in Korea’s AI PCB ecosystem is not always inside the board manufacturers. It is upstream. Doosan Electronic BG’s high-end CCL business is running at roughly a 30% operating-margin profile, and Pamicell’s low-dielectric materials profile also sits around the 30% zone. Most board manufacturers sit closer to the mid-teens to low-20s. When margins cluster like that, the market is telling us where pricing power is concentrated: the shortage is partly in substrates, but the tighter bottleneck may be in CCL and low-loss materials.

Business quality and factor attractiveness are not the same ranking. A simple business-quality stack would put Doosan Electronic BG near the top, followed by Samsung Electro-Mechanics, Kolon Industries’ mPPO option, Isu Petasys, Daeduck Electronics and Pamicell. A price-aware factor stack looks different: Daeduck Electronics screens better because it has FC-BGA plus MLB exposure at a less demanding multiple; Kolon Industries is interesting because the mPPO option is diluted inside a low-multiple chemical and industrial-materials company; Pamicell offers upstream leverage but carries customer-concentration risk; Doosan has the best business, but the public-market access route is Doosan the holding company.

Doosan Electronic BG is the best business in the map, but not automatically the cleanest stock setup. Investors do not buy a separately listed Electronic BG. They buy Doosan, which includes other subsidiaries and holding-company complexity. The business may be excellent; the access route may already be expensive.

Kolon Industries is the most interesting dilution case. mPPO sales are estimated to move from roughly ₩20bn in 2024 to ₩80bn in 2025 and about ₩180bn by 2027. Yet this sits inside a company with roughly ₩5tn revenue and a single-digit enterprise multiple profile. A sell-side SOTP view can value the mPPO option near ₩1.5tn, while the whole market cap has been around the ₩2.5tn to ₩2.9tn range. The core issue is not whether mPPO matters. It is whether the market can see it through the rest of the company.

Taesung belongs in the ecosystem but not in the same valuation table. With 2025 revenue around ₩38bn, operating losses and a market cap around the multi-trillion-won zone, its price is not earnings-driven. It is an option on PCB capex and glass-substrate equipment. That can be valuable, but it must be held in a separate option basket, not compared one-for-one with profitable substrate and materials names.

My working portfolio lens is not a buy list. It is a factor map: Daeduck Electronics as the balanced core substrate factor; Kolon Industries and Pamicell as the upstream-materials barbell; Korea Circuit as an option; Doosan as a high-quality CCL anchor that requires entry discipline; Samsung Electro-Mechanics, Isu Petasys and Simmtech as higher-recognition names where valuation and pullback discipline matter; TLB as the SoCAMM-specific factor; Taesung as a separate equipment-option basket.

1. From A Manufacturer Screen To An Ecosystem Map

A narrow AI substrate screen usually starts with the board manufacturers: Samsung Electro-Mechanics, Isu Petasys, Daeduck Electronics, Simmtech and Korea Circuit. That is a useful starting point, but it is incomplete.

AI infrastructure does not stop at the board house. Advanced boards require high-end CCL, low-loss resin, glass fiber, copper foil, ABF-like inputs, module boards and the equipment that enables substrate capacity. Once the upstream layer is added, the map becomes more revealing.

AI infrastructure capex
 -> GPU / ASIC / CPU / switch ASIC demand
 -> package substrates, MLB, memory modules, SoCAMM
 -> CCL, low-dielectric resin, mPPO, hardeners, glass fiber, copper foil
 -> PCB and glass-substrate equipment

The ten-company ecosystem looks like this:

Layer	Companies	What they represent
Package substrate / FC-BGA	Samsung Electro-Mechanics, Daeduck Electronics, Korea Circuit	AI accelerator, CPU and ASIC package substrates
MLB / network boards	Isu Petasys, Daeduck Electronics, Simmtech, Korea Circuit	Server boards, switch boards, high-layer MLB
Memory module / SoCAMM	TLB, Simmtech, Korea Circuit, Daeduck Electronics	DDR5 and LPDDR-based server memory modules
CCL anchor	Doosan Electronic BG inside Doosan	High-end copper-clad laminate for AI accelerators and high-speed networking
Low-dielectric materials	Kolon Industries, Pamicell	mPPO, low-loss resin, hardeners and upstream inputs
Equipment	Taesung	PCB equipment and glass-substrate optionality

This is why a simple “AI PCB beneficiary” label is not enough. The ecosystem contains different margin structures, qualification risks, customer concentration risks and valuation regimes.

2. The Key Accounting Clue: Margins Are Higher Upstream

The most important observation is the margin gap.

Category	Company / segment	Working 2027E OPM profile
Upstream CCL	Doosan Electronic BG	~31%
Upstream low-dielectric materials	Pamicell	30%+ profile in recent / sell-side frames
MLB pure-play	Isu Petasys	~22%
Balanced substrate	Daeduck Electronics	~19%
Module substrate	TLB	~16%
Memory substrate	Simmtech	~14%
FC-BGA + MLCC large cap	Samsung Electro-Mechanics	~14%
FC-BGA option	Korea Circuit	high-single-digit to low-teens path
Diluted materials option	Kolon Industries	low-single-digit consolidated OPM, because mPPO is diluted

The margin message is simple: where pricing power is strongest, operating margin tends to show it first. If Doosan Electronic BG and Pamicell sit near 30% while many board makers sit in the 14% to 22% zone, the shortage is not just “boards are scarce.” It is also that the materials stack enabling those boards has pricing power.

This does not mean board makers are unattractive. It means the ecosystem must be separated into two questions:

Question 1: Which businesses have the highest quality and pricing power?
Question 2: Which public stocks still offer the best factor setup after price?

Those two answers are not the same.

3. The Ten-Company Working Matrix

The table below is a working matrix using May 4-5, 2026 price references and sell-side estimate sets where available. It is not a real-time quote sheet. Several lines use segment estimates or company-specific model work rather than standardized consensus.

Company	Reference price / market cap	2027E revenue	2027E OP	2027E OPM	2027E PER	OP growth 26 -> 27
Samsung Electro-Mechanics	~₩68.6tn market cap in the working sheet	₩13.83tn	₩1.94tn	14.0%	46.5x	+26.2%
Isu Petasys	~₩10.94tn	₩2.13tn	₩462bn	21.7%	29.7x	+44.4%
Daeduck Electronics	~₩5.65tn	₩1.88tn	₩363bn	19.3%	19.5x	+48.8%
Simmtech	~₩3.25tn	₩2.07tn	₩284bn	13.7%	18.5x	+70.1%
Korea Circuit	~₩2.19tn	₩2.20tn	₩190bn	8.6%	15.4x	+40.7%
Doosan Electronic BG via Doosan	~₩27.6tn Doosan market cap	₩3.44tn segment revenue	₩1.08tn segment OP	31.3%	20.9x Doosan-level frame	+41.8%
TLB	~₩0.89tn	₩415bn	₩65bn	15.6%	21.7x	+38.8%
Kolon Industries	~₩2.5tn to ₩2.9tn market cap range	₩5.18tn consolidated	₩241bn	4.7%	9.7x	+17.6%
Pamicell	~₩1.2tn market cap range	standardized consensus limited	–	30%+ margin profile	–	–
Taesung	~multi-trillion-won option valuation	consensus limited	loss / early-stage option frame	–	not meaningful	–

Several caveats matter. Doosan Electronic BG is a segment inside Doosan, not a separately listed company. Kolon Industries’ consolidated OPM understates the economics of the mPPO line because the option is diluted inside a much larger chemical and industrial-materials company. Taesung’s valuation is not an earnings multiple; it is an equipment-option price.

The arithmetic behind selected rows:

Doosan Electronic BG 2027E OPM = 1.076tn / 3.441tn = 31.3%
Doosan Electronic BG OP growth = 1.076tn / 0.759tn - 1 = 41.8%

TLB 2027E OPM = 64.8bn / 415.4bn = 15.6%
TLB OP growth = 64.8bn / 46.7bn - 1 = 38.8%

Kolon Industries consolidated OPM = 241.0bn / 5.18tn = 4.7%

4. GARP Re-Ranking

I use a simple GARP score as a sorting tool:

GARP score = operating-profit growth x operating margin / PER

This is not a valuation model. It is a way to keep growth, margin and price in the same frame.

Company / segment	OP growth	OPM	PER	GARP score
Doosan Electronic BG via Doosan	+41.8%	31.3%	20.9x	62.6
Simmtech	+70.1%	13.7%	18.5x	51.9
Daeduck Electronics	+48.8%	19.3%	19.5x	48.3
Isu Petasys	+44.4%	21.7%	29.7x	32.4
TLB	+38.8%	15.6%	21.7x	27.9
Korea Circuit	+40.7%	8.6%	15.4x	22.7
Kolon Industries consolidated	+17.6%	4.7%	9.7x	8.5
Samsung Electro-Mechanics	+26.2%	14.0%	46.5x	7.9

The GARP table says three useful things.

First, Doosan Electronic BG screens extremely well as a business. High growth plus a 31% operating-margin profile is rare.

Second, Daeduck Electronics remains the most balanced substrate-factor setup among the board manufacturers because it combines FC-BGA, MLB and a still-reasonable valuation frame.

Third, Kolon Industries looks weak on consolidated GARP precisely because mPPO is diluted. That is not a reason to ignore it. It is the reason to analyze it separately.

5. Doosan Electronic BG: Best Business, Imperfect Access Route

Doosan Electronic BG is the cleanest business-quality leader in the map. Public reports around Doosan’s 1Q26 results show Doosan’s own business revenue rising sharply, with Electronics BG strength driven by high-end CCL for AI accelerators, memory semiconductors and high-speed systems.

This is the business-quality case:

Point	Why it matters
OPM around 30%	Pricing power is concentrated in high-end CCL
AI accelerator and networking exposure	CCL content rises with GPU, CPU, switch ASIC and high-speed board complexity
Capacity expansion	Suggests management sees a multi-year cycle rather than one strong quarter
Customer qualification	High-end CCL is not a commodity slot once qualified into the AI supply chain

But the public-market access route is not pure. Investors buy Doosan, not separately listed Doosan Electronic BG. Doosan includes Electronics BG, Doosan Bobcat, Doosan Enerbility exposure, other self-business pieces and holding-company discount or premium dynamics.

That is the whole reason business quality and stock setup diverge. The business itself can be first-rate while the stock entry point is less clean.

What a Doosan share includes:
 - Electronics BG economics inside the holding company
 - Other affiliate values
 - Holding-company structure
 - Non-CCL volatility

What it does not give:
 - A pure listed CCL instrument
 - Direct 100% exposure to Electronics BG margin
 - Isolation from other subsidiary volatility

So Doosan Electronic BG is the benchmark for business quality. Doosan the stock needs price and holding-company discipline.

6. Kolon Industries: The mPPO Dilution Case

Kolon Industries is a different kind of opportunity. The interesting part is not consolidated operating margin. The interesting part is that mPPO can be material while still hidden.

The mPPO revenue path in the working sheet:

Item	2024	2025	2026F	2027F
mPPO revenue	~₩20bn	~₩80bn	~₩130bn	~₩180bn

A DS-style SOTP view can assign about ₩1.5tn of value to the mPPO option by applying a high multiple to estimated 2027 EBITDA. That is meaningful versus a total market-cap range around ₩2.5tn to ₩2.9tn.

The dilution mechanism is straightforward:

Kolon Industries consolidated:
 - revenue around ₩5tn
 - operating margin around mid-single digits
 - market sees a chemical / industrial-materials company

mPPO line:
 - much smaller revenue base
 - faster growth
 - higher implied margin
 - tied to high-end CCL and low-dielectric material demand

Result:
 - the consolidated multiple stays low
 - the option is visible to analysts but not fully separated by the market

If mPPO reaches about ₩180bn revenue in 2027 and around ₩59bn EBITDA, its standalone economics look nothing like a low-single-digit-margin commodity chemical business. The analytical question is whether the market begins to value Kolon as two businesses: a mature industrial-materials core plus a fast-growing mPPO option.

There are two ways for that to happen. The first is accounting visibility: more frequent IR disclosure, clearer segment commentary and sell-side SOTP models. The second is structural separation, which would require company action and should not be assumed. The more realistic path is accounting visibility.

7. Pamicell: Upstream Of The Upstream

Pamicell deserves a separate company-level treatment; this ecosystem note keeps the lens narrower: where does it sit inside the ten-company map, and why does that position matter for the broader AI CCL chain?

It is upstream of Doosan Electronic BG’s CCL.

Pamicell low-dielectric resin / hardeners
 -> Doosan Electronic BG high-end CCL
 -> FC-BGA / MLB / AI server boards
 -> AI accelerator, CPU, NIC and switch systems

That position creates both the upside and the discount.

The upside is operating leverage. If a small upstream supplier becomes qualified into a high-margin CCL cycle, incremental orders can move the income statement quickly. Pamicell’s 2025 operating margin was around 30%, and sell-side 2026 frames have discussed margins in the mid-30s.

The discount is customer concentration. Pamicell is not a broad board manufacturer. It is not Doosan Electronic BG. It depends on the order cadence, qualification status and sourcing decisions of a narrow upstream materials chain.

The key follow-up variables are the same ones from the Pamicell work:

Variable	Why it matters
1Q26 operating profit and margin	Confirms whether high-margin materials are flowing into reported earnings
Follow-on Doosan contracts in May-June	Tests whether the February contract was a new run-rate or timing pull-forward
Third Ulsan plant progress	Determines whether 2027 capacity can support the thesis
KRX reclassification after May 4	Tests whether market perception is moving from biotech to electronics materials

Pamicell is one of the sharper expressions of the upstream thesis, but it must be sized and analyzed as a customer-concentration story.

8. TLB: The SoCAMM-Specific Factor

TLB deserves a separate slot because its factor exposure is different. It is closest to a SoCAMM and server memory-module board angle.

TLB working 2027E:
 revenue: ₩415bn
 operating profit: ₩65bn
 OPM: 15.6%
 PER: 21.7x
 GARP: 27.9

SoCAMM matters because LPDDR-based server memory modules can become part of the next-generation CPU and AI inference memory stack. The more CPU-heavy agentic AI becomes, the more interesting the memory-module board layer becomes.

But SoCAMM is still a factor, not a fully proven revenue base. Vera CPU adoption, OEM design wins and the final module-standard path all matter. That makes TLB cleaner than many diversified PCB names for the SoCAMM angle, but also more dependent on one thesis becoming real.

The practical map:

SoCAMM purity:
 1. TLB
 2. Simmtech
 3. Korea Circuit
 4. Daeduck Electronics

TLB is not the highest-quality company in the ecosystem, but it is a useful single-factor monitor for SoCAMM.

9. Taesung: Do Not Put It In The Same Table

Taesung belongs in the AI substrate ecosystem because equipment matters. If substrate makers expand capacity, equipment suppliers can benefit. If glass substrates become a real production path, specialized equipment can gain option value.

But Taesung should not be ranked like the other nine names.

The reason is valuation structure. The working numbers point to a company with 2025 revenue around ₩38bn, operating losses and a multi-trillion-won market cap. That implies a price-to-sales ratio in the dozens, closer to an option valuation than a normal earnings stock.

Taesung 2025 working frame:
 revenue: \~₩38bn
 operating profit: negative
 market cap: multi-trillion-won zone
 PSR: roughly 60x+

That is not automatically wrong. Options can be valuable. But the analysis method changes.

Taesung driver	What to monitor
PCB equipment cycle	Large orders from substrate capacity expansion
Glass substrate option	Evidence of pilot-to-mass-production transition
Consensus formation	Whether 2026-2027 earnings estimates become real enough to underwrite

Until those variables mature, Taesung belongs in a separate option basket, not a GARP table beside Doosan Electronic BG or Daeduck Electronics.

10. Business Quality Versus Factor Attractiveness

This is the most important conclusion.

Business quality ranking:

1. Doosan Electronic BG
2. Samsung Electro-Mechanics
3. Kolon Industries mPPO, if separated
4. Isu Petasys
5. Daeduck Electronics
6. Pamicell

Price-aware factor attractiveness:

1. Daeduck Electronics
2. Kolon Industries
3. Korea Circuit
4. Pamicell
5. Doosan
6. TLB
7. Isu Petasys
8. Simmtech
9. Samsung Electro-Mechanics
10. Taesung, separate option basket

The point is not that the second list is a trading recommendation. It is a reminder that good businesses and good factor setups are different things.

Good business -> market recognizes quality -> price rises -> incremental alpha shrinks
Hidden or complex business -> market discounts the story -> price lags -> alpha can remain

Doosan Electronic BG is excellent, but the stock route is a holding company. Samsung Electro-Mechanics is excellent, but the market has already recognized a lot of it. Daeduck is less pure, but has balanced FC-BGA and MLB exposure at a less demanding multiple. Kolon Industries looks cheap because mPPO is hidden inside a larger company. Pamicell still carries the old biotech label in some investors’ minds, even though its materials economics have changed.

Alpha rarely comes from the highest-quality business after everyone agrees it is high quality. It more often comes from the place where the market has not yet cleanly separated the valuable part from the rest.

11. What Could Be Wrong

Several parts of this framework can fail.

Doosan Electronic BG’s 30% margin could be a peak-cycle outcome rather than a structural margin. If CCL capacity catches up quickly, the margin signal weakens.

Kolon Industries’ mPPO revenue path could lag. If the line moves slower than the ₩130bn to ₩180bn path, the dilution discount may be justified.

Doosan’s holding-company structure could remain a permanent discount. A great segment does not always create full value for minority shareholders if the access route is complex.

Taesung’s glass-substrate option could remain an option and never convert into revenue. In that case, the option multiple normalizes.

Pamicell’s customer concentration could become the wrong kind of leverage. If follow-on contracts slow, the small-base upside works in reverse.

The framework is useful only if the quarterly data keeps validating it.

12. Verification Checklist

Layer	Company	Signals to track
CCL anchor	Doosan / Electronic BG	Electronics BG OPM near 30%, CCL capacity expansion, customer diversification
mPPO	Kolon Industries	mPPO revenue path, separate IR commentary, SOTP adoption by sell-side
Upstream materials	Pamicell	1Q26 margin, follow-on Doosan contracts, third-plant progress
Balanced substrate	Daeduck Electronics	FC-BGA customer wins, MLB capacity, server-grade product mix
MLB	Isu Petasys	800G / 1.6T demand, pricing pass-through, OPM durability
Premium anchor	Samsung Electro-Mechanics	AI data-center package substrate wins, MLCC price / mix, estimate revisions
Memory substrate	Simmtech	SoCAMM revenue, 2026 OPM recovery
Option substrate	Korea Circuit	Broadcom-linked FC-BGA revenue, SoCAMM ramp, consolidated margin
SoCAMM	TLB	SoCAMM module-board ramp, DDR5 high-value mix
Equipment option	Taesung	Major orders, glass substrate equipment production, credible consensus formation

FAQ

What is the Korea AI PCB ecosystem?

It is the listed Korean supply chain around AI substrates: FC-BGA, MLB, memory module boards, SoCAMM, high-end CCL, low-dielectric materials and PCB / glass-substrate equipment.

Why do margins matter so much in this analysis?

Margins show where pricing power is accumulating. If upstream CCL and low-dielectric material companies show higher margins than board manufacturers, the bottleneck may be closer to the material stack than to assembly alone.

Why is Doosan Electronic BG not simply the top stock?

Because it is not separately listed. The public-market route is Doosan, a holding-company structure with other affiliate values and risks. Business quality and stock access are not the same thing.

Why is Kolon Industries interesting despite low consolidated margins?

Because the mPPO option may be hidden inside a much larger chemical and industrial-materials company. The consolidated margin and PER can obscure the economics of the mPPO line.

Is Taesung comparable to the other nine companies?

No. Taesung is better treated as an equipment and glass-substrate option. Its valuation is not driven by current earnings in the same way as the profitable substrate or material names.

Selected Public Sources

Doosan 1Q26 high-end CCL strength, Seoul Economic Daily: https://en.sedaily.com/finance/2026/04/29/doosan-q1-operating-profit-jumps-717-percent-on-high-end
Doosan earnings document summary, MarketScreener: https://www.marketscreener.com/news/doosan-earnings-document-ce7f59d3dd81f224
Pamicell 2026 Doosan Electronic BG supply contract report: https://www.g-enews.com/article/Securities/2026/02/20260219100622493844093b5d4e_1
Lotte Energy Materials and Doosan Electronic BG high-performance PCB copper foil alliance: https://en.sedaily.com/finance/2026/03/22/lotte-energy-materials-doosan-electronics-unit-partner-on
Taesung financial overview, StockAnalysis: https://stockanalysis.com/quote/kosdaq/323280/financials/

Final Note

The statement “AI substrates are scarce” is true, but it is too shallow. The better question is: where does the scarcity convert into margin?

The ten-company map suggests the answer is upstream. Doosan Electronic BG and Pamicell show margin profiles around the 30% zone, while many board manufacturers sit in the 14% to 22% range. That does not make board makers bad. It means the material stack deserves its own analytical weight.

The most important investment lesson is that business quality and factor attractiveness diverge. Doosan Electronic BG may be the best business, but the listed route is Doosan. Samsung Electro-Mechanics may be the premium anchor, but recognition is already high. Daeduck Electronics may be less glamorous, but the combination of FC-BGA, MLB and valuation looks more balanced. Kolon Industries may look like a low-multiple chemical company, but mPPO can create a hidden option. Pamicell still carries old-label risk, but that is exactly why the recognition gap can matter.

The work from here is straightforward: track margins, contract cadence, mPPO disclosure, SoCAMM adoption, glass-substrate equipment orders and whether the market starts separating the valuable hidden parts from the consolidated wrappers.

AI PCB and Substrate Thesis: GPU, CPU, NIC and CCL Demand Are One System Bottleneck

Tue, 05 May 2026 23:15:00 +0900

Sector map: This is the upper-layer AI PCB and substrate thesis behind the Pamicell work. The company comparison continues in Korea AI PCB Ecosystem: 10 Companies, and the full reading path sits in the AI PCB hub. Read it together with Pamicell Part 1, Pamicell Part 2, and the Samsung Electro-Mechanics AI infrastructure re-rating note.

The company-level question is narrower: which Korean names have the best position in AI PCB, FC-BGA and low-loss material supply? This note moves one level up. It asks why capital should enter the whole ecosystem in the first place.

The answer is not “substrates are the next theme after GPUs.” That is too linear. AI infrastructure is no longer a GPU card. It is a rack-scale system. A modern AI rack has GPUs, CPUs, DPUs, NICs, switch ASICs, memory modules, power delivery, cooling control and high-speed boards. Each layer adds silicon. Each piece of silicon needs a package substrate, a module board, a motherboard, a switch board or a low-loss material stack.

That is the core point: the PCB and substrate layer is not the next stop in a simple rotation. It is the common denominator of the entire AI system bill of materials.

TL;DR

The market’s “GPU to memory to substrate” sequence is directionally useful, but incomplete. The better frame is simultaneous system expansion: GPU, HBM, CPU, DPU, NIC, switch ASIC and memory modules all rise together, and all require substrates or boards.
NVIDIA Vera Rubin NVL72 makes the point concrete. The platform combines 72 Rubin GPUs, 36 Vera CPUs, NVLink 6 switching, ConnectX-9 SuperNICs, BlueField-4 DPUs and Spectrum-X / Spectrum-6 Ethernet scaling. The CPU:GPU ratio is 0.5, or one CPU for every two GPUs. This is no longer a single-chip story.
Agentic AI raises the CPU intensity of inference. Tool orchestration, retrieval, code execution, database access, memory management and security isolation all lean on CPUs, DRAM, NICs and DPUs. If CPU content rises, server CPU FC-BGA, memory module boards, SoCAMM, motherboards and low-loss CCL all get pulled along.
Physical AI expands the thesis outside the data center. Autonomous vehicles, humanoids, industrial robots and space electronics all use more boards, more sensors, more edge AI modules and more reliability-sensitive PCB material. The time curve differs: data center first, autonomous driving second, humanoids later, space as a high-reliability margin premium.
For Korea, the investable map becomes layered. Samsung Electro-Mechanics is the high-end FC-BGA plus MLCC node. Daeduck Electronics is the FC-BGA / MLB / SoCAMM factor candidate. Doosan Electronic BG is the CCL anchor. Kolon Industries and Pamicell sit upstream in low-dielectric materials. Pamicell is not just a standalone stock idea; it is one compressed proxy inside a larger AI substrate system.

1. The Linear Frame: Useful, But Too Small

The market likes sequences because sequences are easy to trade.

First came GPUs: NVIDIA captured the budget because accelerators were scarce. Then came HBM: GPUs could not scale without memory bandwidth, so SK hynix, Samsung Electronics and Micron moved to the center of the discussion. The next step is usually described as substrates or advanced packaging: if GPUs and HBM scale, then FC-BGA, interposers, MLBs and CCL should follow.

That frame is not wrong. A larger GPU needs a larger and more complex package substrate. HBM expansion raises packaging intensity. Server boards become denser and faster. From that angle, substrates do come after GPUs and HBM in the recognition cycle.

But the frame misses the most important change in system architecture. AI infrastructure in 2026 is not a pile of GPUs. It is a rack-scale platform that co-designs compute, memory, networking, security and system control.

The NVIDIA Vera Rubin NVL72 configuration is the cleanest example. Public NVIDIA materials describe a system built around 72 Rubin GPUs and 36 Vera CPUs, with NVLink 6 switching, ConnectX-9 SuperNICs and BlueField-4 DPUs. NVIDIA’s own Rubin platform materials also frame the platform as a six-chip co-design: Vera CPU, Rubin GPU, NVLink switch, ConnectX-9 SuperNIC, BlueField-4 DPU and Spectrum-6 Ethernet switch.

The arithmetic matters:

Vera CPUs = 36
Rubin GPUs = 72
CPU:GPU = 36 / 72 = 0.5

One CPU for every two GPUs is not a trivial host-processor footnote. It says the rack is a system, not a GPU shelf. Once that is true, the substrate thesis stops being a downstream echo of GPU demand. It becomes a multi-chip system thesis.

2. Why Every Chip Pulls A Board

The easiest way to see the substrate layer is to walk the system bill of materials.

System layer	Chip or module	Board / substrate demand
AI acceleration	GPU, custom ASIC, TPU	Large FC-BGA, advanced package substrate, high-density board
Host and orchestration	Server CPU, Vera CPU, x86 / Arm CPU	Large FC-BGA, CPU socket board, motherboard MLB
Memory bandwidth	HBM, DDR5, LPDDR-based server modules, SoCAMM	Interposer / substrate, memory module PCB, signal-integrity material
Networking	NIC, SuperNIC, Ethernet switch ASIC, InfiniBand switch	Switch board, optical module PCB, low-loss MLB
Data movement and security	DPU, SmartNIC	Package substrate, accelerator card PCB
Power and control	VRM, power modules, BMC and control boards	Power PCB, MLCC, high-reliability board

This is why “GPU demand” is too narrow. A hyperscaler does not buy a GPU in isolation. It buys a working rack. That rack contains compute chips, memory chips, networking chips, control chips and power electronics. The more the system expands, the more the board layer is asked to carry high-speed signals, heat, power and reliability.

The Korean equity translation is also clearer under this frame:

Korean layer	Companies to track	What they represent
High-end package substrate	Samsung Electro-Mechanics, Daeduck Electronics, Korea Circuit	FC-BGA and package substrate exposure
Multi-layer board and module PCB	Isu Petasys, Daeduck Electronics, TLB, Simmtech, Korea Circuit	Server motherboard, switch board, memory module and SoCAMM exposure
CCL anchor	Doosan Electronic BG	High-end copper-clad laminate for AI servers and networking
Low-loss materials	Kolon Industries, Pamicell	mPPO / low-dielectric resin and hardener inputs
Power stability	Samsung Electro-Mechanics and MLCC peers	MLCC content per AI server and high-voltage component mix

Pamicell belongs in this map as an upstream material proxy to Doosan Electronic BG. Samsung Electro-Mechanics belongs as the premium listed Korean node in FC-BGA and MLCC. Daeduck belongs as the broader FC-BGA / MLB / SoCAMM factor candidate. These are not separate stories. They are different points on the same system BOM.

3. Agentic AI Makes The CPU Layer Bigger

Traditional LLM inference looked simple from a hardware lens:

prompt
 -> GPU forward pass
 -> response

Agentic AI changes the workload. The model does not just answer. It plans, calls tools, searches, reads files, executes code, queries databases, manages memory, verifies output and may coordinate with other agents. The GPU is still central, but the non-GPU work becomes much heavier.

Agentic function	Main hardware pull
LLM forward pass	GPU + HBM
Tool orchestration	CPU
Retrieval and search	CPU + DRAM + storage
Code execution	CPU, sandbox, compiler / interpreter
Session memory and state	CPU + DRAM
Networked tool calls	NIC + switch ASIC + PCB
Security and isolation	CPU + DPU

TrendForce has been explicit about this direction. Its April 2026 agentic AI report and related public commentary describe a structural change in CPU:GPU ratios, tight server CPU supply and price increases by Intel and AMD. Tom’s Hardware reported the same direction from the industry side: AI server configurations that once used one CPU for four to eight GPUs can move toward much higher CPU intensity in agentic inference scenarios.

The exact ratio will vary by workload. A code-agent cluster is not the same as a video generation cluster. A retrieval-heavy enterprise agent is not the same as a pure batch inference system. But the direction is what matters for substrate investors: more CPU work means more CPU packages, more memory around the CPU, more networking, and more board-level signal integrity requirements.

The path from agentic AI to Korean substrates looks like this:

Agentic AI adoption
 -> CPU orchestration workload increases
 -> server CPU, DPU, NIC and switch ASIC content rises
 -> server CPU FC-BGA and high-layer MLB demand rises
 -> memory modules, SoCAMM and motherboard complexity rise
 -> low-loss CCL and low-dielectric materials become more important
 -> Korean substrate and material companies receive a share of the BOM expansion

That last line is important. Korea does not own the CPU market. Intel, AMD, Arm, NVIDIA and cloud-service-provider custom CPUs capture the chip value. Korean listed companies capture the board and material content around the chip. This is still meaningful because the substrate content grows with the system, not with a single product line.

4. Physical AI: Outside The Data Center

The data center is the first and largest near-term driver. Physical AI is the second expansion path. The timing is slower, but the direction is consistent: when intelligence moves into vehicles, robots, factories and satellites, more compute moves closer to the edge. More edge compute means more boards.

Autonomous driving

Autonomous driving is the most realistic second leg because cars already use large electronics stacks. A vehicle with advanced driver assistance or autonomous functions contains central compute, sensor fusion, camera modules, radar, lidar, vehicle Ethernet and redundant safety controllers.

Vehicle system	PCB and material pull
Central compute	High-density board, processor package substrate
Sensor fusion ECU	Multi-layer PCB, high-speed signal board
Camera / lidar / radar	Rigid-flex, RF board, module PCB
Vehicle Ethernet	Low-loss CCL and high-speed communication PCB
Safety redundancy	More ECUs and more board area

This does not hit earnings as quickly as AI data centers. Vehicle programs take time, qualification is slow and the revenue curve is model-cycle dependent. But the direction is not ambiguous: a smarter vehicle carries more board content than a traditional vehicle.

Humanoid and industrial robotics

NVIDIA Jetson Thor gives the physical AI argument a concrete hardware reference point. NVIDIA positions Jetson Thor for physical AI and robotics, with up to 2,070 FP4 TFLOPS, 128GB of memory and a 40W to 130W configurable power range. That kind of edge AI module needs high-density boards, power boards, sensor interconnect and flexible PCBs.

Humanoids will not drive Korean substrate earnings tomorrow. They are not yet a mass-volume market. But they extend the option value of the thesis. If edge AI modules become standardized across robots, factories and industrial machines, board content shifts from a data-center-only story to a distributed compute story.

Space and defense electronics

Space is different. It is not a volume story. It is a reliability and margin story. NASA and IPC-related materials for mission hardware emphasize high-reliability PCB requirements, supplier qualification and Class 3 / space-addendum type standards. For listed Korean PCB names, the relevance is not “space will absorb massive capacity.” It is that harsh-environment electronics can justify higher reliability standards and potentially better margins.

The time curve looks like this:

End market	Earnings timing	PCB intensity	Practical confidence
AI data center	Fast	Very high	High
Autonomous driving	Medium	High	Medium to high
Humanoids / robotics	Slow	Medium to high	Medium
Space / defense electronics	Slow	High specification, low volume	Medium

This ordering matters. The near-term model should still be data-center led. Physical AI is not a reason to stretch every valuation today. It is a reason the terminal market may be broader than the current AI server cycle implies.

5. What This Adds To The Pamicell Thesis

The Pamicell work started with a company-specific recognition gap. The market remembered a stem-cell company. The income statement increasingly looked like an AI CCL material supplier. The Doosan Electronic BG link, repeated supply-contract evidence, high-margin biochemicals and KRX industry reclassification all pushed in the same direction.

This sector thesis changes the question from “why Pamicell?” to “why does the upstream CCL material layer matter at all?”

The answer is that CCL and low-loss materials are not tied to one GPU generation. They sit under the system layer:

GPU / CPU / DPU / NIC / switch ASIC expansion
 -> high-speed signal and thermal constraints rise
 -> low-loss CCL demand rises
 -> CCL producers need low-dielectric materials
 -> upstream suppliers such as Pamicell become compressed proxies

Pamicell is still not the same as Doosan Electronic BG, and it is not a PCB manufacturer. It is further upstream. That means customer concentration and qualification risk are real. But it also means the company’s small size can make the same system-level demand look more powerful in percentage terms if orders keep compounding.

Put differently: Pamicell’s thesis becomes more durable if the AI board cycle is not just a GPU substrate cycle, but a multi-chip system substrate cycle.

6. What This Adds To The Samsung Electro-Mechanics Thesis

Samsung Electro-Mechanics was already re-rated around two ideas: high-end FC-BGA and AI-server MLCC. That older framing still works. The system-BOM thesis makes it cleaner.

If the only driver were GPUs, Samsung Electro-Mechanics would be a high-end package-substrate story with MLCC attached. If the driver is rack-scale system expansion, the company sits in more than one lane:

Lane	Why it matters
FC-BGA	Larger and more complex CPUs, GPUs, ASICs and networking chips need high-end package substrates
MLCC	AI servers, networking trays and power delivery all increase component density
Glass substrate option	Future large-package architecture may require new substrate materials and processes
Automotive and robotics electronics	Physical AI increases high-reliability component and board demand over time

This does not remove valuation discipline. Samsung Electro-Mechanics has already been recognized by the market more than Pamicell or some smaller PCB names. The factor question is not “is this a good company?” It is “how much of the system-level substrate expansion is already in the price, and how much must be confirmed through orders, margins and guidance?”

That is why this note treats Samsung Electro-Mechanics as the premium anchor rather than the highest-beta idea. It is the cleanest Korean large-cap expression of FC-BGA plus MLCC, but its future return depends on continued estimate revisions rather than simply discovering the theme.

7. Portfolio Frame: Core, Barbell, Options

The company ranking can change with price, but the factor map is stable.

Role	Candidate exposure	Reason
Premium anchor	Samsung Electro-Mechanics	FC-BGA + MLCC + customer qualification + scale
Core PCB factor	Daeduck Electronics	FC-BGA, MLB and potential SoCAMM / module board sensitivity
CCL anchor	Doosan Electronic BG inside Doosan	High-end CCL body of the domestic chain
Upstream material barbell	Kolon Industries and Pamicell	Low-dielectric resin / material exposure, smaller base and higher operating leverage
Optionality	Korea Circuit, TLB, Simmtech, Isu Petasys	Memory module, MLB, networking and broader AI PCB beta

The point is not to force one answer. The point is to avoid treating all “AI PCB” names as the same asset. Package substrates, multi-layer boards, CCL and low-dielectric chemistry have different margin structures, qualification periods and customer risks.

A useful portfolio view is:

Premium anchor:
 Samsung Electro-Mechanics

Core substrate / board factor:
 Daeduck Electronics, selected MLB names

Upstream material barbell:
 Kolon Industries + Pamicell

Higher-beta options:
 Korea Circuit, TLB, Simmtech, Isu Petasys

When the market says “the PCB cycle is over,” the system-BOM thesis helps test whether that is true. If GPU shipments slow but CPU content, networking ASICs, DPUs and memory module complexity keep rising, the board cycle may cool in one lane while staying tight in another.

8. What Could Break The Thesis

The common-denominator frame is not a claim that the cycle lasts forever. Four risks matter.

First, hyperscaler AI capex can slow. If AWS, Microsoft, Google or Meta guide down for more than one quarter, the entire hardware supply chain will feel it.

Second, substrate technology can change. Glass substrate or other new architectures could alter the FC-BGA cycle faster than expected. This does not remove board demand, but it can shift the winners.

Third, capacity can arrive. If high-end CCL, glass fiber or low-loss material capacity enters faster than expected, pricing power can normalize before volumes fully mature.

Fourth, physical AI can take longer than the market wants. Autonomous driving, humanoids and space electronics all have long qualification and adoption cycles. They are not substitutes for near-term data-center revenue.

These risks do not kill the thesis. They define the checklist.

9. Verification Checklist

The thesis should be tracked at the system level, not just through one company’s quarterly number.

Signal	Why it matters
NVIDIA rack-scale roadmap	More chip types and higher rack density extend the common-denominator substrate cycle
CPU:GPU ratio commentary	A higher CPU ratio strengthens the CPU FC-BGA and motherboard MLB leg
Hyperscaler capex guidance	The first-order demand source for AI data-center boards
CCL and glass-fiber lead times	Confirms whether material tightness is real or easing
Samsung Electro-Mechanics package and component margins	Tests whether premium substrate and MLCC pricing still hold
Daeduck / MLB order commentary	Tests whether broader PCB beta is converting into revenue
Pamicell and Doosan Electronic BG contract cadence	Tests whether upstream CCL material demand is still compounding
Automotive / robotics PCB comments in Korean company IR	Early sign that physical AI is moving from optionality to revenue

If these signals stay aligned, the substrate cycle is not simply a 2025-2027 theme. It becomes a multi-year system architecture shift.

FAQ

What is the AI PCB thesis?

The AI PCB thesis argues that AI infrastructure demand is no longer limited to GPUs and HBM. Rack-scale systems need GPUs, CPUs, NICs, DPUs, switch ASICs, memory modules and power boards. Each layer requires package substrates, multi-layer boards or low-loss materials.

Why does agentic AI increase CPU demand?

Agentic AI uses tools, retrieval, code execution, memory management and orchestration. Those tasks add CPU, DRAM, networking and DPU workload around the GPU. Higher CPU content can increase demand for server CPU FC-BGA, motherboards, memory module boards and low-loss CCL.

Why are Samsung Electro-Mechanics and Pamicell in the same sector map?

They sit at different points in the same AI substrate chain. Samsung Electro-Mechanics is a premium FC-BGA and MLCC node. Pamicell is an upstream low-dielectric material supplier linked to Doosan Electronic BG’s CCL cycle. The same system-level AI board demand can affect both, but with different risk and valuation profiles.

Is Pamicell a PCB company?

No. Pamicell is not a PCB manufacturer. The relevant thesis is upstream material exposure: low-dielectric / low-loss inputs used by CCL producers such as Doosan Electronic BG.

Is this investment advice?

No. This is a sector research framework. The right conclusion depends on valuation, order cadence, margin confirmation, customer concentration and each investor’s risk tolerance.

Selected Public Sources

NVIDIA Vera Rubin NVL72 product page: https://www.nvidia.com/en-us/data-center/vera-rubin-nvl72/
NVIDIA Technical Blog, Vera Rubin platform overview: https://developer.nvidia.com/blog/inside-the-nvidia-rubin-platform-six-new-chips-one-ai-supercomputer/
TrendForce, agentic AI and CPU:GPU ratio commentary: https://insights.trendforce.com/p/agentic-ai-cpu-gpu
TrendForce report page, 2026 Agentic AI Wave: https://www.trendforce.com/research/download/RP260408AD
Tom’s Hardware, agentic AI and CPU demand: https://www.tomshardware.com/pc-components/cpus/shifting-need-for-cpus-in-ai-workloads-drives-intensifying-shortages-price-hikes
NVIDIA Jetson Thor product page: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-thor/
NASA quality guidance for high-reliability PCB standards: https://sma.nasa.gov/sma-disciplines/quality
NASA GSFC-STD-8001 high-reliability PCB standard: https://standards.nasa.gov/sites/default/files/standards/GSFC/Baseline/0/gsfc-std-8001.pdf

Final Note

The cleanest version of the thesis is simple:

AI does not buy GPUs alone. It buys systems.

Systems add chips. Chips need substrates, boards and low-loss materials.

That is why the substrate layer should be read as a common bottleneck rather than a late-cycle afterthought. The implication is not that every Korean PCB or material stock deserves the same multiple. It is that the ecosystem should be evaluated as a system-level supply chain: Samsung Electro-Mechanics at the premium FC-BGA / MLCC node, Daeduck and MLB names at the board layer, Doosan Electronic BG at the CCL body, and Kolon Industries and Pamicell upstream in low-dielectric materials.

The work from here is not to repeat the theme. It is to track whether the system BOM keeps getting thicker, whether CPU and networking content continue to rise, and whether Korean companies convert that complexity into orders and margins.