Market Context — Why This Technology, Why Now

The global manufacturing sector is undergoing a profound transformation driven by Industry 4.0, demanding higher precision, efficiency, and automation. Simultaneously, demographic shifts exacerbate the scarcity of experienced craftspeople, particularly in specialized fields like casting. This technology offers a timely solution, enabling manufacturers to overcome labor dependency, meet escalating quality standards, and maintain competitiveness in a rapidly evolving industrial landscape.

Key Competitive Advantages
01

Achieves High-Precision Pouring Estimation: Integrates ladle tilt angle, weight, and internal shape data to accurately estimate molten metal volume in real-time.

02

Standardizes Manual Pouring Quality: Digitally visualizes and standardizes pouring operations, significantly reducing quality variability across operators.

03

Provides Real-time Feedback: Continuously monitors pouring, detects anomalies instantly, and enables rapid adjustments to reduce defect risk.

Market Opportunity
Casting and Die-casting Industry
$65B–$70B globally (AI est.)
Increasing demand for lighter and more precise automotive and industrial machine parts necessitates stable quality in manual pouring operations.
Automotive component manufacturers Industrial machinery OEMs Die-casting foundries
Special Alloy Manufacturing
$1.5B–$3.5B globally (AI est.)
Special alloys used in aerospace and medical fields cannot tolerate even minor quality defects, making strict control of the pouring process essential.
Aerospace material suppliers Medical device manufacturers High-performance alloy producers
High-Precision, High-Mix Production
$1.5B–$6B globally (AI est.)
In high-mix low-volume production, pouring conditions frequently require adjustment for each product, creating a strong demand for operational standardization and efficiency through this technology.
Custom parts manufacturers Specialized industrial foundries Prototyping and R&D facilities
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a system for accurately estimating molten metal pouring state by integrating ladle tilt angle, weight, and internal shape data. With 13 claims and a history of successfully overcoming examiner challenges, it establishes a robust and stable scope of protection for real-time pouring process control.

Competitive White Space

This patent focuses on estimating pouring volume. White space exists in advanced process control beyond estimation, such as automated robotic pouring systems or integration with AI for predictive maintenance of casting equipment.

Economic Impact
~$100K/year estimated cost savings per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming annual losses from defective products (material and rework costs) in a casting factory are ~$0.5M (AI est.). If this technology reduces the defect rate caused by pouring issues by 20%, direct annual cost savings could be ~$0.5M (AI est.) × 20% = ~$100K (AI est.). Indirect benefits like improved customer trust from higher quality are also expected.

Speed to Market
6× faster than in-house development
This technology could shorten market entry by ~2.5 years compared to in-house development. The core algorithm is established, and required sensors for angle, weight, and internal shape data are commercially available. Designed as an add-on to existing pouring equipment, it enables rapid prototyping and deployment without significant capital investment.
Competitive Positioning

X: Pouring Accuracy
Y: Operational Efficiency

Business Models & Applications
📄 System License Provision
Provide software licenses for this estimation system, allowing adopting companies to integrate it into existing pouring equipment to enhance product quality and productivity.
📊 Data Analysis Service
Analyze pouring data collected by the system on a cloud platform, offering quality improvement consulting and predictive maintenance services.
⚙️ Sensor Module Sales
Package and sell angle/weight sensors and internal shape acquisition modules, essential for implementing this technology, to manufacturers.
Adjacent Application Opportunities
🍲 Food Processing
Quality Control for Liquid Filling Processes
Applicable to high-viscosity liquid bottling or container filling in food factories. This could improve filling accuracy, prevent foreign object contamination, and enhance yield by up to 15% in automated lines.
🧪 Chemicals & Pharmaceuticals
Precision Liquid Mixing and Dispensing Systems
Applicable to precise mixing and dispensing of chemicals and pharmaceuticals. Expected to reduce errors and enhance safety in handling hazardous or expensive reagents, potentially cutting material waste by 10-20%.
🏗️ Construction & Building
Optimizing Concrete Pouring Volume
Applicable to concrete pouring in construction. Real-time management of pouring volume and speed into formwork could reduce risks of insufficient strength or cracking, optimizing material costs by 5-10%.
Integration Roadmap — Estimated 12-Month Deployment
Phase 1: Verification & Definition
Duration: 3 months
Evaluate compatibility with the adopting company's existing pouring equipment and define system requirements based on specific quality and production targets.
Phase 2: Prototype Development & Test
Duration: 6 months
Based on requirements, install sensors, build data collection systems, adjust estimation algorithms, and conduct prototype testing in a real environment.
Phase 3: Production & Optimization
Duration: 3 months
Optimize the system based on test results and proceed with deployment to the production environment. After deployment, continuous data analysis will aim for further accuracy improvement and maximum effectiveness.
Technical Feasibility
This technology estimates pouring volume using physical data (ladle tilt angle, weight, internal shape) and can be integrated into existing pouring equipment via add-on sensors and data interfaces. Its components utilize general-purpose measurement technology, allowing for relatively low-cost, rapid implementation without extensive equipment modification. High compatibility with existing software-driven systems is expected.
Success Scenario
Implementing this technology could reduce the defect rate in manufacturing line pouring processes from ~5% to under 2%. This is estimated to cut material costs and rework significantly, potentially boosting annual productivity by 10%. Additionally, by capturing skilled operators' expertise within the system, new employee training times could be shortened, fostering a more stable production environment.
Patent Record
APPLICATION NO.
特願2020-012528
REGISTRATION NO.
7421211
FILING DATE
2020/01/29
GRANT DATE
2024/01/16
EXPIRATION DATE
2040/01/29
PATENT HOLDER
国立大学法人山梨大学
Examination History
2020年01月31日
手続補正書（自発・内容）
2022年11月02日
出願審査請求書
2023年08月29日
拒絶理由通知書
2023年10月20日
意見書
2023年10月20日
手続補正書（自発・内容）
2023年12月12日
特許査定