Design Optimization of a Six Degrees of Freedom Parallel Mechanism Based Robotic Machining Bed

In precision manufacturing, the stability of the machining element is of utmost importance, and it is provided by the machining beds. To enhance the functionality and dexterity of these machining beds, parallel manipulators are integrated with them. Although these manipulators offer more flexibility and execution of various complex tasks, still guaranteeing their optimal performance is a challenge. To overcome this issue, the present research suggests an optimization technique employing Particle Swarm Optimization (PSO) which improves the performance of the proposed robotic machining bed by minimizing its conditioning index and increasing the overall workspace. PSO is a stochastic searching algorithm inspired by the concept of fish schooling or murmuration of birds. The outcomes of the research provide an optimized model of robotic machining bed which leads towards accurate machining operations and efficient precision manufacturing facilities.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/etecte63967.2024.10823973
Citations
2
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
0.66
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article

Design Optimization of a Six Degrees of Freedom Parallel Mechanism Based Robotic Machining Bed

Muhammad Faizan Shah, Zareena Kausar, Syed Saad Farooq, Asna Kalsoom
2 citations
Robotic Mechanisms and Dynamics
0.66
article

Design Optimization of a Six Degrees of Freedom Parallel Mechanism Based Robotic Machining Bed

Muhammad Faizan Shah, Zareena Kausar, Syed Saad Farooq, Asna Kalsoom
article en
2 citations

Abstract

In precision manufacturing, the stability of the machining element is of utmost importance, and it is provided by the machining beds. To enhance the functionality and dexterity of these machining beds, parallel manipulators are integrated with them. Although these manipulators offer more flexibility and execution of various complex tasks, still guaranteeing their optimal performance is a challenge. To overcome this issue, the present research suggests an optimization technique employing Particle Swarm Optimization (PSO) which improves the performance of the proposed robotic machining bed by minimizing its conditioning index and increasing the overall workspace. PSO is a stochastic searching algorithm inspired by the concept of fish schooling or murmuration of birds. The outcomes of the research provide an optimized model of robotic machining bed which leads towards accurate machining operations and efficient precision manufacturing facilities.

University of Canberra (AU), Khwaja Fareed University of Engineering and Information Technology (PK)
Peace, Justice and strong institutions
Openalex Percentile: Top 28%
Robotic Mechanisms and Dynamics
0.66
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