Details
| Original language | English |
|---|---|
| Pages (from-to) | 286-291 |
| Number of pages | 6 |
| Journal | Procedia CIRP |
| Volume | 128 |
| Early online date | 15 Oct 2024 |
| Publication status | Published - 2024 |
| Event | 34th CIRP Design Conference, CIRP 2024 - Cranfield, United Kingdom (UK) Duration: 3 Jun 2024 → 5 Jun 2024 |
Abstract
Implementing industrial robots in manufacturing cells for automation requires specialized knowledge. Trajectory planning and end-effector design significantly increase the required effort. The trajectory planning is iterative and time-consuming and also depends on the robot base placement, which is why the automation of robot base placement is being explored. This paper presents a novel approach to automate the robot base positioning demonstrated on the example of the Central Research Center 1153 (CRC 1153) Tailored Forming. Accordingly, a three-step approach is developed: First, an accurate 3D environment has to be created to define the forging cell structure, otherwise problems may occur during the transition to the real-world application. Next, the robot's position and trajectory are calculated and optimized using a proprietary algorithm. If there is no arrangement that allows collision-free trajectory planning, another algorithm is applied that extends the robot's workspace by adjusting the arrangement of the robot's flange and the tool center point (TCP) of the end effector. Finally, AI-based methods are used to equip the end-effector and the robot with customized coupling elements depending on the TCP adjustment performed in the previous step. As a result of this work, a framework for automated robot placement in manufacturing cells using optimization algorithms and AI-based methods is presented. This increases the efficiency of automated manufacturing cell design and minimizes the dependency of the result's quality on the engineer's experience.
Keywords
- AI, Automation, Generative Design, Manufacturing
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 128, 2024, p. 286-291.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Approach of Automated Robot Arrangement in Manufacturing Cells
AU - Ince, C. V.
AU - Schönburg, J.
AU - Raatz, A.
N1 - Publisher Copyright: © 2024 Elsevier B.V.. All rights reserved.
PY - 2024
Y1 - 2024
N2 - Implementing industrial robots in manufacturing cells for automation requires specialized knowledge. Trajectory planning and end-effector design significantly increase the required effort. The trajectory planning is iterative and time-consuming and also depends on the robot base placement, which is why the automation of robot base placement is being explored. This paper presents a novel approach to automate the robot base positioning demonstrated on the example of the Central Research Center 1153 (CRC 1153) Tailored Forming. Accordingly, a three-step approach is developed: First, an accurate 3D environment has to be created to define the forging cell structure, otherwise problems may occur during the transition to the real-world application. Next, the robot's position and trajectory are calculated and optimized using a proprietary algorithm. If there is no arrangement that allows collision-free trajectory planning, another algorithm is applied that extends the robot's workspace by adjusting the arrangement of the robot's flange and the tool center point (TCP) of the end effector. Finally, AI-based methods are used to equip the end-effector and the robot with customized coupling elements depending on the TCP adjustment performed in the previous step. As a result of this work, a framework for automated robot placement in manufacturing cells using optimization algorithms and AI-based methods is presented. This increases the efficiency of automated manufacturing cell design and minimizes the dependency of the result's quality on the engineer's experience.
AB - Implementing industrial robots in manufacturing cells for automation requires specialized knowledge. Trajectory planning and end-effector design significantly increase the required effort. The trajectory planning is iterative and time-consuming and also depends on the robot base placement, which is why the automation of robot base placement is being explored. This paper presents a novel approach to automate the robot base positioning demonstrated on the example of the Central Research Center 1153 (CRC 1153) Tailored Forming. Accordingly, a three-step approach is developed: First, an accurate 3D environment has to be created to define the forging cell structure, otherwise problems may occur during the transition to the real-world application. Next, the robot's position and trajectory are calculated and optimized using a proprietary algorithm. If there is no arrangement that allows collision-free trajectory planning, another algorithm is applied that extends the robot's workspace by adjusting the arrangement of the robot's flange and the tool center point (TCP) of the end effector. Finally, AI-based methods are used to equip the end-effector and the robot with customized coupling elements depending on the TCP adjustment performed in the previous step. As a result of this work, a framework for automated robot placement in manufacturing cells using optimization algorithms and AI-based methods is presented. This increases the efficiency of automated manufacturing cell design and minimizes the dependency of the result's quality on the engineer's experience.
KW - AI
KW - Automation
KW - Generative Design
KW - Manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85208784131&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2024.06.023
DO - 10.1016/j.procir.2024.06.023
M3 - Conference article
AN - SCOPUS:85208784131
VL - 128
SP - 286
EP - 291
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
T2 - 34th CIRP Design Conference, CIRP 2024
Y2 - 3 June 2024 through 5 June 2024
ER -