Intelligent control of interconnected manufacturing infrastructures (i-CNC)
Developed under the Trials Net Open Call.
In collaboration with FOGUS and LMS.
CNC Milling
Among the three CNC cutting technologies -drilling, lathing, and milling- milling has been the go-to method for over 100 years. Its flexibility and precision make it ideal for creating parts from a wide range of materials. With continuous technological advancements, CNC milling machines now offer even more efficient and accurate production solutions.
The Challenge of Chatter in CNC Milling
Despite its benefits, CNC milling faces a common issue: "chatter." This is an uncontrollable vibration between the cutting tool and workpiece, leading to poor surface quality, and reduced component and tool lifespan. While traditional methods like adjusting tools or workpieces can help minimize chatter, these approaches are often manual and trial-based, falling short of the demands of today's high-performance machinery.
The key principles of i-CNC use case
The i-CNC use case focuses on transforming CNC machining by addressing the chatter problem through an end-to-end solution that replaces traditional trial-and-error chatter supervision with a cloud-based, Al-enabled autonomous system. This approach ensures precise, scalable, and secure CNC operations based on the latest research and industry advancements in machinery control systems, setting a new standard for efficiency and precision in CNC machining. The key principles of i-CNC use case:
5G Connectivity
Ensures fast, reliable data transfer between geographically distributed machines and data entity for efficient remote control.
Al-Powered Data Analysis
Vibration signals are processed and classified using advanced Al models to predict and reduce chatter in real time.
Cloud-Based Scalability
Cloud service provisioning enables scalable, remote decision-making applications, reducing the need for costly local setups.
Security and Interoperability
The platform complies to industry standards for secure data exchange, ensuring compatibility across different systems.
Continuous Data Collection
Distributed sites continuously contribute data for long-term analysis, supported by the CNC training centre and HTEC Network.
i-CNC sub-project under the Open Call framework of TrialsNet project
Project Programme: European Union's Horizon-JU-SNS-2022 Research and Innovation Programme
Grant Agreement No: 101095871
Project Title: Intelligent control of interconnected manufacturing infrastructures
Project Acronym: i-CNC
Project Duration: 05/2024 - 04/2025
Project Partners
PARTNER 1:
P. Gounas - K. Enezlis G.P.
Partner Abbreviation:
CNC Solutions
Type of Partner:
Business
PARTNER 2:
Fogus Innovation Services
Partner Abbreviation:
Fogus
Type of Partner:
Research and Innovation SME
PARTNER 3:
Laboratory for Manufacturing Systems & Automation, University of Patras
Partner Abbreviation:
LMS
Type of Partner:
Research Organization
