IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Robotic CAM System Available for Both CL Data and NC Data

Robotic CAM System Available for Both CL Data and NC Data
View Sample PDF
Author(s): Fusaomi Nagata (Tokyo University of Science, Japan), Sho Yoshitake (Tokyo University of Science, Japan), Keigo Watanabe (Okayama University, Japan)and Maki K. Habib (The American University in Cairo, Egypt)
Copyright: 2019
Pages: 17
Source title: Rapid Automation: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-8060-7.ch030

Purchase

View Robotic CAM System Available for Both CL Data and NC Data on the publisher's website for pricing and purchasing information.

Abstract

This chapter describes the development of a robotic CAM system for an articulated industrial robot from the viewpoint of robotic servo controller. It is defined here that the CAM system includes an important function that allows an industrial robot to move along not only numerical control data (NC data) but also cutter location data (CL data) consisting of position and orientation components. A reverse post-processor is proposed for the robotic CAM system to online generate CL data from the NC data generated for a five-axis NC machine tool with a tilting head, and the transformation accuracy about orientation components in CL data is briefly evaluated. The developed CAM system has a high applicability to other industrial robots with an open architecture controller whose servo system is technically opened to end-users, and also works as a straightforward interface between a general CAD/CAM system and an industrial robot. The basic design of the robotic CAM system and the experimental result are presented, in which an industrial robot can move based on not only CL data but also NC data without any teaching.

Related Content

Rashmi Rani Samantaray, Zahira Tabassum, Abdul Azeez. © 2024. 32 pages.
Sanjana Prasad, Deepashree Rajendra Prasad. © 2024. 25 pages.
Deepak Varadam, Sahana P. Shankar, Aryan Bharadwaj, Tanvi Saxena, Sarthak Agrawal, Shraddha Dayananda. © 2024. 24 pages.
Tarun Kumar Vashishth, Vikas Sharma, Kewal Krishan Sharma, Bhupendra Kumar, Sachin Chaudhary, Rajneesh Panwar. © 2024. 29 pages.
Mrutyunjaya S. Hiremath, Rajashekhar C. Biradar. © 2024. 30 pages.
C. L. Chayalakshmi, Mahabaleshwar S. Kakkasageri, Rajani S. Pujar, Nayana Hegde. © 2024. 30 pages.
Amit Kumar Tyagi. © 2024. 29 pages.
Body Bottom