Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Achievable tolerances in robotic feature machining operations using a low-cost hexapod Portable robotic machine tools potentially allow feature machining processes to be brought to large parts in various industries, creating an opportunity for capital expenditure and operating cost reduction. However, robots lack the machining capability of conventional equipment, which ultimately results in dimensional errors in parts. This work showcases a low-cost hexapod-based robotic machine tool and presents experimental research conducted to investigate how the widely researched robotic machining challenges, e.g. structural dynamics and kinematics, translate to achievable tolerance ranges in real-world production to highlight currently feasible applications and provide a context for considering technology improvements. Machining trials assess the total dimensional errors in the final part over multiple geometries. A key finding is error variation which is in the sub-millimetre range, although, in some cases, upper tolerance limits < 100 μ m are achieved. Practical challenges are also noted. Most significantly, it is demonstrated that dimensional machining error is mainly systematic in nature and therefore that the total error can be dramatically reduced with in situ measurement and compensation. Potential is therefore found to achieve a flexible, high-performance robotic machining capability despite complex and diverse underlying scientific challenges. Overall, the work presented highlights achievable tolerances in low-cost robotic machining and opportunities for improvement, also providing a practical benchmark useful for process selection. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Achievable tolerances in robotic feature machining operations using a low-cost hexapod

Loading next page...
 
/lp/springer_journal/achievable-tolerances-in-robotic-feature-machining-operations-using-a-30k5CY39u6

References (54)

Publisher
Springer Journals
Copyright
Copyright © 2017 by The Author(s)
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
DOI
10.1007/s00170-017-1266-1
Publisher site
See Article on Publisher Site

Abstract

Portable robotic machine tools potentially allow feature machining processes to be brought to large parts in various industries, creating an opportunity for capital expenditure and operating cost reduction. However, robots lack the machining capability of conventional equipment, which ultimately results in dimensional errors in parts. This work showcases a low-cost hexapod-based robotic machine tool and presents experimental research conducted to investigate how the widely researched robotic machining challenges, e.g. structural dynamics and kinematics, translate to achievable tolerance ranges in real-world production to highlight currently feasible applications and provide a context for considering technology improvements. Machining trials assess the total dimensional errors in the final part over multiple geometries. A key finding is error variation which is in the sub-millimetre range, although, in some cases, upper tolerance limits < 100 μ m are achieved. Practical challenges are also noted. Most significantly, it is demonstrated that dimensional machining error is mainly systematic in nature and therefore that the total error can be dramatically reduced with in situ measurement and compensation. Potential is therefore found to achieve a flexible, high-performance robotic machining capability despite complex and diverse underlying scientific challenges. Overall, the work presented highlights achievable tolerances in low-cost robotic machining and opportunities for improvement, also providing a practical benchmark useful for process selection.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Nov 10, 2017

There are no references for this article.