RESONIKS provides AI-powered acoustic testing for fast, automated detection of internal structural defects in manufactured components. This inline quality control solution offers 100% real-time inspection, eliminating the need for slow, costly legacy methods like X-ray or ultrasound. The system enables manufacturers to find defects early in the production process, reducing scrap and improving overall product integrity.
Funding
$2.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
KVFounders
Product
Problem
Metal part manufacturing relies on manual quality control processes, which are prone to human error, subjective assessment, and high labor costs. Traditional non-destructive testing methods often struggle to detect internal defects like cracks, voids, and porosity efficiently, leading to potential quality issues and safety risks. The shortage of skilled labor further exacerbates these challenges, hindering manufacturers' ability to maintain consistent quality and meet production demands.
Solution
RESONIKS provides an AI-powered acoustic sensor solution for non-destructive testing of cast, forged, and welded metal parts. The system uses unique acoustic signatures to detect internal defects such as cracks, voids, and porosity. By integrating AI, the solution can operate effectively in noisy industrial environments, accurately distinguishing between good and defective parts. The technology automates the defect detection process, reducing reliance on manual inspections and ensuring consistent quality.
Target Audience
The primary target audience includes manufacturers of cast, forged, and welded metal parts across various industries, such as automotive, aerospace, and heavy machinery.
Features
- AI-powered acoustic sensors for detecting internal defects in metal parts
- Non-destructive testing methodology preserves the integrity of inspected parts
- In-line integration for continuous monitoring of production lines
- Standalone system for specific inspection requirements
- Automated defect detection process reduces reliance on manual labor
- Compatible with various industrial manufacturing systems via standard communication protocols
- AI algorithm continuously learns and improves defect detection accuracy