The global push for Industry 4.0 and smart manufacturing demands advanced sensor technologies for continuous process monitoring. Stricter environmental regulations and consumer safety standards across the US, EU, and APAC regions necessitate robust, verifiable quality control in liquid-based production. This technology enables manufacturers to meet these demands by providing unprecedented real-time data, driving operational efficiency, and ensuring compliance, thereby gaining a critical edge in competitive markets.
Enables real-time, high-precision concentration measurement through impedance matching layers and reflected wave detection, contributing to immediate process feedback and quality stabilization.
Eliminates contamination risk and sampling loss by measuring concentration without direct contact, offering significant advantages in hygiene-critical applications.
Supports concentration changes for a wide range of aqueous substances, potentially allowing one device to manage diverse solutions, optimizing capital investment and operational costs.
This patent protects a method and apparatus for aqueous solution concentration measurement using electromagnetic waves, specifically covering the use of an impedance matching layer to detect changes in reflected waves. Its claims have been rigorously examined and strengthened through a successful response to office actions, establishing a robust and stable scope of protection against prior art.
This patent primarily covers electromagnetic wave-based concentration measurement. White space exists in integrating this technology with other sensor modalities for multi-parameter analysis or developing advanced AI/ML models for predictive process control based on the real-time data.
Assuming an average quality defect rate of 2% in food factories due to concentration management, resulting in an estimated annual loss of $1,000,000 (AI est.) from product disposal and reprocessing. By implementing this technology, real-time high-precision measurement could reduce the defect rate to 0.5%, leading to an estimated annual cost reduction of ~$200,000 (AI est.).
X: Real-time Measurement Accuracy
Y: Deployment & Operational Cost Efficiency