Three Mechanisms Driving a Multi-Cluster Innovation Landscape

Laser cleaning surface treatment works by directing pulsed or continuous-wave laser radiation onto a surface to selectively remove unwanted material while preserving the substrate — and the specific removal mechanism determines everything from laser wavelength selection to substrate compatibility. A 2023 review from Shantou University’s Key Laboratory of Intelligent Manufacturing Technology explicitly categorises three primary mechanisms: thermal ablation, thermal stress-induced delamination, and plasma shock wave ejection. Each carries distinct operational ranges and substrate compatibility profiles, and this mechanistic diversity directly drives the multi-cluster innovation landscape observed in the patent and literature record.

The technology accommodates an unusually wide range of substrate materials and system configurations — from bench-top laboratory units to robot-integrated platforms for large-area industrial deployment. This breadth is what makes laser cleaning a genuinely disruptive proposition: a single platform architecture can, in principle, address contamination challenges across aerospace, shipbuilding, power infrastructure, and cultural heritage conservation, provided the laser parameters and monitoring systems are correctly matched to the removal mechanism required.

From Artworks to Aerospace: A 30-Year Innovation Timeline

The laser cleaning field spans at least three decades of development, with a clear acceleration toward integrated, intelligent systems concentrated in the period from 2020 onward. The dataset’s earliest signal is an Australian patent for surface erosion using lasers filed by Summit Technology in 1987, followed by a Spanish patent covering high-peak-power laser cleaning of stone, glass, steel, and ceramics for art restoration filed by ARDT in 1995. A French patent on real-time ellipsometry-based surface monitoring appeared in 1997, and a Japanese patent covering semiconductor wafer cleaning by diagonal laser irradiation was filed in 2001 by Japan Steel Works — establishing early microelectronics interest alongside the art restoration track.

Mid-stage development from 2010 to 2019 broadened research to cover process monitoring, multi-material substrates, and industrial integration. The Manufacturing Technology Centre (UK) demonstrated LIBS-based closed-loop laser cleaning of tungsten carbide in 2018. Samsung Heavy Industries Co., Ltd. filed two quality-monitoring laser cleaning patents in 2019, incorporating camera-based surface analysis and cleaning quality verification. A large-area laser ablation apparatus patent by Doowon Photonics Co., Ltd. (Korea) also appeared in 2019, using polygon mirrors for wide-field scanning.

“The period from 2020 onward shows the most concentrated activity in this dataset — 20+ records — reflecting rapid industrialisation of laser cleaning across aerospace, shipbuilding, power infrastructure, and semiconductor manufacturing.”

The most recent period (2020–2026) is defined by AI-assisted parameter optimisation (Chinese Academy of Sciences, 2020), femtosecond laser cleaning for pre-weld surface preparation (TOMOGEO Ltd., Hungary, 2023), water-jet-guided quasi-continuous laser cleaning (Shandong University of Technology, 2022), and robot-based off-line programming for large complex components (Qilu University of Technology, 2021). A 2023 EP-granted patent from Chengdu MRJ-Laser Technology Co., Ltd. covers an adjustable-focus galvanometer cleaning system, and a KR-active dry laser cleaning system for display substrates was filed in 2022.

Four Technology Clusters Shaping the Field

Laser cleaning surface treatment innovation is not monolithic — the dataset resolves into four distinct technology clusters, each with different maturity levels, substrate targets, and competitive dynamics. Understanding which cluster a given R&D programme falls into is essential for accurate freedom-to-operate assessment and differentiation strategy.

Cluster 1: Pulsed Laser Ablation and Thermal Stress Removal

This is the dominant approach in the dataset. Short-pulse (nanosecond to microsecond) fiber or Nd:YAG lasers are directed at contaminant layers; thermal stress gradients at the contamination-substrate interface drive delamination. Research from Beijing University of Technology (2018) demonstrates complete removal of a 100 µm paint layer from a steel substrate at a fluence of 10.19 J/cm² using a 1064 nm fiber laser. Daewoo Shipbuilding and Marine Engineering Co., Ltd. (2021) studied 100 W Q-switched fiber laser removal of thick epoxy coatings of 200 µm or greater from SS400 steel, with beam scan pattern identified as the key process variable. This cluster is applied extensively to paint removal, rust stripping, and oxide film removal — and is commoditising rapidly as nanosecond fiber laser hardware becomes widely available.

Cluster 2: Ultra-Short Pulse (Picosecond and Femtosecond) Laser Cleaning

Ultra-short pulse lasers deliver energy faster than thermal diffusion timescales, enabling cold ablation with minimal heat-affected zones. The University of West Bohemia (2016) established optimal picosecond laser parameters for cleaning and deoxidation of nickel-based superalloy AM1 without structural changes. The University of Manchester (2020) demonstrated excimer laser de-coating of a 3.2 µm DLC coating from tungsten carbide at 7 J/cm², 400 pulses, and 25 Hz — enabling tool re-grinding and recoating. TOMOGEO Ltd. (Hungary, 2023) demonstrated femtosecond pre-weld cleaning of drill bit end surfaces, with micro-CT and break-out testing confirming improved joint mechanical properties. This cluster represents the highest-differentiation segment in the current landscape.

Cluster 3: Hybrid and Assisted Laser Cleaning Systems

This emerging cluster combines laser energy with secondary agents — water jets, airflow, or plasma — to enhance cleaning quality, reduce thermal effects, and improve debris removal efficiency. Shandong University of Technology (2022) demonstrated that water-jet-guided quasi-continuous laser cleaning eliminates the recast layer and heat-affected zone on 304 stainless steel substrates. Shenzhen Institute of Information Technology (2022) showed that a 532 nm nanosecond laser with airflow assist removes microparticles and oxide layers from silicon carbide crystal surfaces, validated by CFD and FEM simulations. King Mongkut’s University of Technology North Bangkok (2017) demonstrated a 1064 nm + 532 nm dual-wavelength system enabling depth-controlled paint removal by toggling between infrared and visible regimes. IP positions in this sub-field remain relatively open in the dataset.

Cluster 4: Intelligent Closed-Loop and Automated Laser Cleaning Systems

The most strategically significant cluster couples laser cleaning with in-process sensors — LIBS, probe beam reflection, camera-based imaging — and control algorithms to enable autonomous, damage-free cleaning with real-time quality verification. Beihang University (2021) showed that the LIBS relative intensity ratio of FeI 520.9 nm to CrI 589.2 nm serves as a quantitative endpoint indicator for oxide layer removal on hot-rolled stainless steel. The Chinese Academy of Sciences Institute of Automation (2020) demonstrated a PSO-SVM machine learning model that maps surface imaging features (GLCM, concave-convex features) to optimal laser cleaning parameters including power, velocity, and line spacing. Samsung Heavy Industries Co., Ltd.’s 2019 KR-active patents describe a dual-laser system with camera analysis of plume and flame characteristics for real-time surface quality determination.

Application Domains: Where Laser Cleaning Is Winning

Laser cleaning surface treatment has established credible application records across at least six distinct industrial and conservation domains, with the depth of innovation activity varying significantly by sector. The technology’s non-contact, residue-free characteristics make it particularly compelling wherever chemical or abrasive cleaning creates downstream contamination, substrate damage, or regulatory compliance challenges — as recognised by standards bodies including ISO and sector regulators aligned with WIPO‘s green technology classification frameworks.

Aerospace and defence applications include aircraft skin paint removal, pre-bond surface treatment of composites, and superalloy component cleaning. Civil Aviation Flight University of China demonstrated LIBS-based multi-layer paint removal monitoring from aluminium aircraft skin. Technische Universität Braunschweig evaluated composite bonding pre-treatment at 3 µm wavelength against conventional laser sources, addressing carbon-fibre-reinforced polymer structural bonds. The University of West Bohemia addressed picosecond cleaning of AM1 nickel superalloy surfaces prior to thermal spraying.

Shipbuilding and heavy industry is the domain with the most concentrated patent activity from named industrial assignees. Daewoo Shipbuilding and Marine Engineering Co., Ltd. specifically targets replacement of mechanical blasting in shipyard paint application cycles. Samsung Heavy Industries Co., Ltd. holds multiple KR-active patents for mobile, wheel-mounted laser cleaning devices with integrated quality inspection for ship hull rust removal — a direct commercial deployment signal.

Power infrastructure and electrical equipment is an active research area centred on laser cleaning of ceramic and porcelain insulators to prevent contamination flashover. Wuhan University of Technology (2022) and China Three Gorges University (2023) both publish thermal-stress simulation-validated parameter studies for ceramic insulator cleaning. Nuclear applications include fibre laser cleaning of optical mirror surfaces in the ITER fusion reactor diagnostic systems, demonstrated by National Research Nuclear University MEPhI (2015) — a high-stakes application where substrate damage is entirely intolerable.

Semiconductor and electronics manufacturing interest dates to Japan Steel Works’ 2001 patent covering diagonal-incidence laser cleaning for sub-0.1 µm particle removal from semiconductor wafers. Dry laser cleaning for display substrates, covering fine particle removal from display glass, is addressed by a KR-active 2022 patent.

Cultural heritage and art conservation is the earliest application domain in the dataset: the 1995 ARDT patent targets stone, glass, and ceramics; Warsaw University of Technology (2010) addresses historic metal artefacts; and the Institute of Electronic Structure and Laser, FORTH (Greece, 2013) demonstrates synchronised deformation monitoring during laser cleaning of cultural heritage objects. According to research published through channels tracked by Nature, non-contact laser methods have become the preferred conservation approach for irreplaceable substrates where chemical exposure is unacceptable.

Geographic and Assignee Landscape

Innovation in laser cleaning surface treatment is distributed rather than concentrated in a single dominant assignee — but the geographic pattern is clear: China dominates research-stage volume, while Europe and Korea lead commercial device IP. Understanding this split is essential for freedom-to-operate analysis in any major market.

Chinese institutions and companies contributing to the dataset include Shantou University, Beihang University, Qilu University of Technology, Shandong University of Technology, Wuhan University of Technology, the Chinese Academy of Sciences Institute of Automation, China Three Gorges University, Chengdu MRJ-Laser Technology Co., Ltd. (which has extended its IP into EP jurisdiction), and Civil Aviation Flight University of China. This breadth across both academic and industrial filers reflects a strong national push toward laser cleaning commercialisation, consistent with broader advanced manufacturing policy priorities tracked by the OECD.

Korean assignees are notably active in the patent record. Samsung Heavy Industries Co., Ltd. holds three KR-active filings (2019) on quality-inspection-enabled laser cleaning devices. SIS Co., Ltd. filed a KR-active laser cleaning device with adjustable polygon mirror spot size in 2022. Doowon Photonics Co., Ltd. holds a KR-active large-area laser ablation apparatus patent from 2019 using polygon mirrors for wide-field scanning.

European assignees contribute important foundational and niche patents. French assignee ARDT holds the early 1995 ES-jurisdiction surface cleaning patent. ONET S.A. (France) filed a monitoring method in DE jurisdiction in 1999. HRD Co., Ltd. (Japan) holds two JP-active laser cleaning method patents covering two-pass scanning strategies for metal cut surfaces from 2015 and 2018. US-jurisdiction active patents include the P-LASER N.V. design patent for a laser cleaning device (2021), reflecting commercial product-level IP protection. HOCHSCHULE MITTWEIDA (Germany, DE active, 2010) covers high-brilliance galvoscanner-based micromachining and cleaning with average power of 1 kW or greater.

Emerging Directions and Strategic Implications

The most recent filings and publications from 2021 to 2023 in this dataset signal five forward-looking directions that will define the next competitive cycle in laser cleaning surface treatment. Each represents both a technology opportunity and a potential freedom-to-operate risk for new market entrants.

Femtosecond laser cleaning for structural integrity improvement moves beyond contamination removal. TOMOGEO Ltd.’s 2023 femtosecond study demonstrates that femtosecond pre-weld cleaning measurably improves tensile strength and toughness of welded joints, confirmed by micro-CT and break-out testing. This positions laser cleaning as a mechanical property engineering step, not merely a surface preparation step — a significant value-chain shift.

Machine learning and AI integration for autonomous parameter optimisation is the trajectory that will define the next commercial standard. The Chinese Academy of Sciences (2020) demonstrates PSO-SVM integration for real-time parameter forecasting, mapping surface imaging features (GLCM, concave-convex features) to optimal power, velocity, and line spacing. Daewoo’s 2021 study uses plume and plasma imaging for cleaning endpoint detection. Together, these signal closed-loop AI-laser systems as the next commercial standard.

Hybrid laser–fluid systems address the heat-affected zone barrier that limits quasi-continuous laser cleaning of sensitive substrates. Water-jet-guided quasi-continuous laser cleaning (Shandong University of Technology, 2022) and airflow-assisted green laser cleaning of silicon carbide crystals (Shenzhen Institute of Information Technology, 2022) represent a convergence of laser and fluid dynamics engineering. IP positions in this sub-field remain relatively open in the dataset.

Multi-wavelength and tunable-focal systems for substrate-adaptive cleaning point toward single-platform systems capable of dynamically adapting beam parameters — wavelength, focal depth, power density — to heterogeneous surfaces. The EP-active Chengdu MRJ-Laser adjustable-focus galvanometer (2022) and the dual-wavelength system study from King Mongkut’s University of Technology North Bangkok (2017) both demonstrate this direction, enabling single-pass cleaning of multi-layer coatings without manual re-configuration.

LIBS as standardised process endpoint sensor is converging across multiple independent groups: Beihang University, Civil Aviation Flight University of China, and Instituto Politécnico Nacional have all independently adopted LIBS as the preferred real-time monitoring method. Standardisation of LIBS spectral signatures as cleaning endpoint criteria appears imminent for industrial quality standards.

“Ultra-short pulse (ps/fs) cleaning is the highest-differentiation segment: nanosecond fiber laser cleaning is commoditising rapidly, while picosecond and femtosecond systems targeting aerospace superalloys, semiconductor substrates, and pre-weld structural applications represent defensible differentiation space with growing application pull.”

From a strategic IP perspective, organisations seeking freedom-to-operate in commercial laser cleaning equipment markets — particularly EU and KR jurisdictions — should conduct thorough clearance searches against Samsung Heavy Industries Co., Ltd., Chengdu MRJ-Laser Technology Co., Ltd. (EP), and the HRD Co., Ltd. JP portfolio. Robotic integration and off-line programming are critical for large-structure deployment: Qilu University of Technology’s robot off-line programming work and Samsung Heavy Industries’ mobile cleaning systems together indicate that scalable laser cleaning for shipbuilding, aerospace structures, and civil infrastructure requires robot path planning as a core system competency, not a peripheral feature. The EPO‘s green technology patent classification (CPC Y02P) is increasingly relevant for laser cleaning filings that displace solvent-based processes.