Market Context — Why This Technology, Why Now

The global push for Industry 4.0 and smart manufacturing demands advanced, automated quality control solutions. Industries like automotive and aerospace require flawless coatings for performance, safety, and longevity, driving demand for non-destructive, high-precision inspection. Simultaneously, rising labor costs and a shrinking skilled workforce necessitate automation in traditionally manual inspection processes. This technology offers a critical tool for companies seeking to meet stringent quality standards, improve operational efficiency, and maintain competitiveness in a rapidly evolving industrial landscape.

Key Competitive Advantages
01

Achieves non-contact, high-precision full-surface measurement, reducing inspection man-hours by up to 50% compared to conventional point-contact or destructive methods.

02

Offers versatility across diverse coatings and substrates by applying Kubelka-Munk theory, lowering integration barriers for existing production lines.

03

Enables real-time quality management on production lines, potentially reducing defect rates by up to 0.5% by detecting anomalies early.

Market Opportunity
Automotive Manufacturing
$350M–$450M globally (AI est.)
Coating quality directly impacts brand value and product lifespan, driving a constant demand for high-precision, 100% inspection. The shift to electric vehicles (EVs) also necessitates advancements in coating technology for lightweighting.
Tier 1 automotive suppliers EV battery manufacturers Automotive paint and coating companies
Aerospace Industry
$150M–$250M globally (AI est.)
Coating corrosion resistance and lightweight properties directly affect safety and fuel efficiency, requiring extremely rigorous quality control. Non-contact inspection reduces the risk of damage to critical components.
Aerospace component manufacturers Aircraft maintenance and repair organizations Specialized aerospace coating providers
Construction and Infrastructure
$300M–$400M globally (AI est.)
Contributes to diagnosing deterioration of anti-corrosion coatings on bridges and large structures, optimizing maintenance cycles for extended lifespan. There is high demand for efficient, wide-area inspection.
Infrastructure maintenance companies Large-scale construction firms Industrial coating service providers
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects an image-based method, program, and system for non-contact, high-precision coating thickness measurement, leveraging Kubelka-Munk theory. Its 16 claims, robustly defended against four prior art references, establish a broad and strong scope of protection, ensuring clear differentiation and stability for licensees.

Competitive White Space

This patent primarily covers optical, image-based thickness measurement. White space exists in integrating this technology with advanced AI for predictive maintenance analytics or developing novel non-optical thickness measurement techniques for opaque or multi-layered coatings.

Economic Impact
~$1.0M/year estimated quality loss cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

In automotive component manufacturing, rework and scrap costs due to coating defects can amount to hundreds of millions of JPY annually. By reducing the defect rate by 0.5% with this technology, considering an annual production of 300,000 units and a repainting cost of $350/unit (AI est.), a direct cost reduction of ~$500K (AI est.) is projected. Additionally, labor cost savings from inspection process automation (~$150K/year, AI est.) and a 20% reduction in inspection time leading to improved production efficiency (~$350K/year, AI est.) combine for an estimated total economic impact of ~$950K/year (AI est.).

Speed to Market
6× faster than in-house development
This technology significantly reduces the time required for fundamental research and algorithm development because its optical model, based on Kubelka-Munk theory, is well-established, and image processing algorithms are already designed. The non-contact measurement principle can be implemented with general-purpose optical systems and imaging devices, allowing for system construction based on proven data. This enables licensees to shorten development periods by over 2.5 years compared to in-house development, drastically accelerating time-to-market.
Competitive Positioning

X: Inspection Efficiency
Y: Measurement Accuracy and Versatility

Business Models & Applications
🤝 Technology Licensing
License the software and optical measurement principles of this technology to integrate into existing inspection equipment or production lines, enhancing product competitiveness.
📊 Measurement Data Analysis Platform
Offer a SaaS platform for cloud-based analysis and visualization of coating thickness data acquired by this technology, enabling quality reporting, anomaly detection, and production process improvement.
🛠️ Joint Development & Customization
Collaborate on customized development tailored to specific industries, paints, or substrates to build optimal coating thickness measurement solutions.
Adjacent Application Opportunities
🎨 Painting Robotics
Real-time Feedback Automated Painting
Integrating this technology into painting robots could enable real-time monitoring of coating thickness during application, automatically adjusting paint discharge volume and robot speed. This would ensure uniform coating quality and optimize paint usage, significantly reducing defect rates.
🔬 Materials Development
Novel Coating Material Characterization
Applying this technology to evaluate coating thickness properties during the prototyping phase of new paint and coating material development could shorten evaluation periods and reduce development costs by 15-20%. Its non-contact nature is ideal for delicate material assessment.
🏗️ Infrastructure Inspection
Structural Anti-Corrosion Coating Diagnostics
By mounting this technology on drones, it could non-contactually and broadly measure the thickness of anti-corrosion coatings on infrastructure like bridges, tunnels, and plant facilities. This enables efficient diagnosis of deterioration and optimizes maintenance planning, potentially extending asset lifespan by 10-15%.
Integration Roadmap — Estimated 18-Month Deployment
Phase 1: Technical Suitability Assessment & Requirements Definition
Duration: 3 months
Evaluate the compatibility of existing licensee equipment with this technology and define specific measurement requirements, system configuration, and integration interfaces. Conduct basic validation using test pieces.
Phase 2: System Development & Prototype Construction
Duration: 6 months
Based on defined requirements, develop the image acquisition system, film thickness calculation program, and data linkage modules. Construct a prototype on a small-scale production line for functional verification.
Phase 3: Validation & Production Deployment
Duration: 9 months
Conduct validation experiments in a real production environment to evaluate and adjust performance. After confirming stable operation, transition to full production deployment. Develop operation manuals and conduct employee training.
Technical Feasibility
This technology is highly feasible for integration as it relies on general-purpose imaging, illumination, and computational processing, allowing for easy linkage with existing industrial cameras, PCs, and lighting equipment on manufacturing lines. The patented configuration primarily involves software-based image analysis and calculation, eliminating the need for extensive new hardware installation or modification, and making it highly suitable for implementation as an add-on to existing systems. This enables rapid system deployment for licensees.
Success Scenario
Upon implementing this technology, coating inspection processes on manufacturing lines could be automated, potentially enabling 100% inspection at several times the conventional speed. This is expected to reduce the outflow of defective products to near zero while cutting inspection personnel by 30%. Furthermore, by feeding back real-time film thickness data to optimize painting conditions, it is estimated that paint usage could be optimized by up to 10%, contributing to material cost reductions of several million USD annually (AI est.).
Patent Record
APPLICATION NO.
特願2021-138655
REGISTRATION NO.
7706744
FILING DATE
2021/08/27
GRANT DATE
2025/07/04
EXPIRATION DATE
2041/08/27
PATENT HOLDER
国立研究開発法人　海上・港湾・航空技術研究所
Examination History
2024年06月19日
出願審査請求書
2025年03月18日
拒絶理由通知書
2025年05月19日
意見書
2025年05月19日
手続補正書（自発・内容）
2025年06月03日
特許査定