Milling CPPS
Table of contents
Important data at a glance
| Project titel: | Setup of a demonstrator for a milling CPPS |
|---|---|
| Collaborative project: | yes |
| Subproject title: | Milling CPPS |
| Duration: | 11/2021 – 08/2022 |
| Funding: |
European Union's Horizon 2020 TRINITY: Digital Technologies, Advanced Robotics and increased Cyber-security for Agile Production in Future European Manufacturing Ecosystems |
| Processor: | |
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Cooperation: |
Objective
Motivation
The "milling CPPS" demonstrator belongs to the field of metal-cutting manufacturing. There, the demands on quality and productivity are constantly increasing. These requirements can hardly be met efficiently with classical methods of process improvement. The results of current research projects (TUD) show possibilities how process optimization can work with the help of process data in cooperation with simulation models. However, a smooth interaction of data acquisition from machine and process, data management and simulation models is necessary for an industrial implementation.
This requires partners from mechanical engineering (line TOS) and IT (line Symate). For these, the demonstrator is to be a test bed for development. This is because companies specializing in IT (such as Symate) have neither experience in production engineering nor the equipment to develop their IT application for production machines. Equally important is demonstrating the technical capabilities to potential users (machine tool manufacturers and users in manufacturing companies like TOS). To this end, the demonstrator shows the interaction of data acquisition from machine and process, data management and simulation models to form a cyberphysical production system (CPPS). For barrier-free transfer of research results to industry, the demonstrator will serve in the university's public laboratory. In addition, the university needs the living demonstrator for training mechanical engineering students.
Objective
In 2 to 3 years, CPPS-based manufacturing should be successfully implemented in industrial machining. Symate aims to develop AI functions for milling processes in software Detact. The POC provides realistic test conditions for industrial Big Data developments. TOS wants to use the demonstrator to learn about the possibilities of CPPS technology and to understand how its own developments need to be adapted. On the other hand, TOS wants to define the new generation of machines with its customers. To this end, the demonstrator will be transferred to the production of a milling head.
Challenges
An important challenge in the implementation of the demonstrator is the real-time processing of Big Data by powerful interface drivers in the Detact Connect module. The next challenge is the conversion of time and process data into the geometric reference of the milling progress on the workpiece. Last but not least, integrating milling process simulation models into process control is challenging. The Detact IoT platform from Symate is designed to solve this.
Solution
The approach is to integrate the innovative partial solutions into a CPPS demonstrator: a) "milling machine" to generate the machine data, b) the interfaces to the machine control to acquire the milling data, c) the IoT platform Detact with the necessary APPs for analytics and visualization and with the interfaces to: d) "milling digital twin" to evaluate the milling process and for simulation-based prediction, e) module "AI-based control". TUD carries out the work on the milling machine (installation, tests, simulation model). The developments on the IOT platform are performed by Symate. TOS offers the transfer of the test setup to a machine with production background. The milestones "Connection of the simulation module for the application of digital process data twins", "Milling monitor" and "Demonstration and technology transfer" enable a solid project implementation.
Fig. 1: Overview of the structure of the demonstrator "Milling CPPS" (cyberphysical production system) and the planned project phases.
Results
As a result, there is a demonstrator of the milling simulation model that can predict the quality of the milled part. The machining simulation model calculates and visualizes the process variables in a discrete location. For the first time, it will be possible to process live data in the machining simulation model and thus build an active digital twin.
Another result is the IOT platform Detact as an integration platform for real-time applications. The Detact IOT platform has extensive algorithms for data analysis and AI. These capabilities are used to calculate technology knowledge for milling.
Fig. 2: Machining tests with data acquisition on the mCPPS demonstrator
Disclaimer
"Demonstrator for a milling CPPS" is part of a subproject that has indirectly received funding from the European Union’s Horizon 2020 research and innovation programme via an Open Call issued and executed under project TRINITY (GA No 825196)
Contact
© Crispin-Iven Mokry
Research associate
NameMr Dipl.-Ing. Frank Arnold
Process Informatics and Machine Data Analysis
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Chair of Machine Tools Development and Adaptive Controls
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