TY - JOUR

T1 - Digital Twin in Process Planning of the Additive and Subtractive Process Chain for Laser Metal Deposition and Micro Milling of Stainless Steel

AU - Denkena, Berend

AU - Wichmann, Marcel

AU - Malek, Talash

AU - Nguyen, Hai Nam

AU - Kato, Makoto

AU - Isshiki, Kaito

AU - Koike, Ryo

AU - Kakinuma, Yasuhiro

N1 - Publisher Copyright: © 2024 by ASME.

PY - 2024/7

Y1 - 2024/7

N2 - 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.

AB - 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.

KW - additive manufacturing

KW - machining processes

KW - modeling and simulation

KW - process planning

UR - http://www.scopus.com/inward/record.url?scp=85194049126&partnerID=8YFLogxK

U2 - 10.1115/1.4065415

DO - 10.1115/1.4065415

M3 - Article

AN - SCOPUS:85194049126

VL - 146

JO - Journal of Manufacturing Science and Engineering

JF - Journal of Manufacturing Science and Engineering

SN - 1087-1357

IS - 7

M1 - 071004

ER -