Digital Twin in Process Planning of the Additive and Subtractive Process Chain for Laser Metal Deposition and Micro Milling of Stainless Steel

authored by

Berend Denkena, Marcel Wichmann, Talash Malek, Hai Nam Nguyen, Makoto Kato, Kaito Isshiki, Ryo Koike, Yasuhiro Kakinuma

Abstract

Additive and subtractive (Add/Sub) manufacturing processes are increasingly being combined to produce complex parts with unique geometries and properties. However, the design of such combined processes is often challenging as it requires a deep understanding of the interaction between the different processes. On the other hand, digital twin (DT) technology has become a powerful tool in recent years for optimizing manufacturing processes. This article explores the use of the digital twin technology for a holistic process planning of combined additive and subtractive processes. The article describes the integration of laser metal deposition (LMD) and micro-milling prediction models of resulting geometry (width and height), hardness, and surface roughness into the digital twin. This is then used for combined process planning to achieve different target values regarding resulting geometry and surface roughness. For the planning of this combined process chain, further criteria such as tool life, energy, and process time are considered in the optimization, showing the potential for sustainable and efficient production. Sensorless cutting force estimation is also used to detect small cutting forces, with the potential to use this as a soft sensor for roughness estimation. The measured width, height, and roughness as a result of the process parameters suggested by the optimization algorithms showed a mean absolute percentage error (MAPE) of 4, 17, and 16%, respectively.

Organisation(s)

Institute of Production Engineering and Machine Tools
PhoenixD: Photonics, Optics, and Engineering - Innovation Across Disciplines

External Organisation(s)

Keio University

Type

Article

Journal

Journal of Manufacturing Science and Engineering

Volume

146

No. of pages

11

ISSN

1087-1357

Publication date

07.2024

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Control and Systems Engineering, Mechanical Engineering, Computer Science Applications, Industrial and Manufacturing Engineering

Electronic version(s)

https://doi.org/10.1115/1.4065415 (Access: Closed)