STRUCTURAL INVESTIGATION OF PNEUMATIC GRIPPERS FOR HANDLING AUTOMOTIVE PARTS USING FINITE ELEMENT ANALYSIS AND TOPOLOGY OPTIMIZATION
Ömer Arat, Adam V. Duran, Barış Erman, Ali Kibar
- Year
- 2025
- Citations
- 2
- Access
- Open access
Abstract
Robotic grippers are widely used in the automotive industry for material handling processes. The lightweight, durable, and efficient design of these grippers is a critical factor for optimizing production operations. This study investigates the structural performance of a pneumatic gripper mechanism designed for a 500 kg material handling system, specifically for handling automotive parts. Finite element analysis (FEA) was used to evaluate the gripper’s ability to withstand applied loads without compromising its structural integrity. The initial analysis revealed a safety factor of 5.16, confirming the design's safety under an applied pressure of 5 bar. Following topology optimization, the gripper’s mass was reduced by 35%, resulting in a slight increase in the stress concentration and a decrease in the safety factor to 4.72. To better understand the benefits of topology optimization, a dimensionless SF/M ratio was introduced, which compares the relative safety factor per unit mass for both designs. The initial design served as the baseline with an SF/M ratio of 1.0, while the optimized design achieved a ratio of 1.42, indicating a 42% improvement in structural efficiency. This research demonstrated the effectiveness of FEA and topology optimization in optimizing gripper designs for material handling applications, emphasizing the importance of maintaining a sufficient safety factor. While the optimized design results in higher stress, it maintains structural integrity and reduces the mass, ensuring that the gripper can securely handle loads. These improvements ultimately enhance the functionality and efficiency of robotic grippers in industrial environments.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002