Details
| Original language | English |
|---|---|
| Article number | 071004 |
| Number of pages | 11 |
| Journal | Journal of Manufacturing Science and Engineering |
| Volume | 146 |
| Issue number | 7 |
| Early online date | 21 May 2024 |
| Publication status | Published - Jul 2024 |
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.
Keywords
- additive manufacturing, machining processes, modeling and simulation, process planning
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computer Science Applications
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Journal of Manufacturing Science and Engineering, Vol. 146, No. 7, 071004, 07.2024.
Research output: Contribution to journal › Article › Research › peer review
}
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 -