Funding
Funding not disclosed
Founders
Product
Problem
In manufacturing, inaccurate tool wear assessment leads to subjective evaluations, unplanned machine downtime, and inefficient maintenance schedules, resulting in production delays, increased costs, and inconsistent product quality. Existing solutions often require manual labor or lack industry-relevant metrics for comprehensive tool status assessment.
Solution
This startup offers a predictive maintenance solution for the manufacturing industry that uses computer vision and AI to measure metal cutting tool wear during machining cycles. The system leverages a neural network to segment tool images, optimizing tool life and reducing downtime through process automation. Data is stored on cloud-based dashboards, providing insights for ERP systems and purchase planning. The solution integrates with existing CNC machines, providing real-time data on tool wear without human intervention.
Target Audience
The primary target customers include manufacturing companies (SMEs and large enterprises), tool manufacturers, coolant manufacturers, and machine tool manufacturers.
Features
- Computer vision-based tool wear measurement using deep learning algorithms
- Real-time monitoring of cutting tools during machining cycles
- Cloud-based platform for data storage, visualization, and analysis
- Integration with ERP systems for purchase planning
- Automated alerts for tool replacement based on wear prediction
- Web-hosted application accessible from any location with an internet connection
- Machine model agnostic, designed to integrate with various CNC machines
- Compliant with ISO 27001 (Information Security Management) and ISO 9001 (Quality Management) standards