Autonomous grinding algorithms with future prospect towards SMART manufacturing: A comparative survey. (January 2022)

• Record Type: Journal Article
• Authors: Pervez, Md. Riaz; Ahamed, Md. Hafiz; Ahmed, Md. Adnan; Takrim, Shah Mohammed; Dario, Paolo
• Is Part Of: Journal of manufacturing systems. Volume 62(2022)
• Page Start: 164
• Page End: 185
• Publication Date: 2022-01
• Subjects: Autonomous Grinding (AG) Algorithm -- Surface Tracking -- Vision -- Vibration and Green Manufacturing (GM) -- SMART Manufacturing; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2021.11.009
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: The importance of Industrial autonomous machining and the economic impact are surveyed. Based on the dimensional defects, the types of grinding operations are suggested. A list of control algorithms with improvements is systematically reviewed (Especially for the grinding and other machining operations). The significance of process manufacturing and SMART machining are summarized. Proposed several methods for future improvement of Autonomous manufacturing research. Abstract: Autonomous Grinding (AG) is a unique kind of manufacturing process which needs extra operative care, for both robot and environment. Due to the rapid growth of research on AG, a detailed analysis on autonomous grinding and the comparative analysis with other machining processes are gathered and listed (like calibration, contact state estimation) based on operating algorithms. This paper has come to the conclusion that there are still some spaces for certain techniques and planning for future growth in the domain of industrial grinding areas such as green manufacturing (GM) methodology for better safety of the environment and better planning for waste material disposal techniques which were not reviewed before in the autonomous grinding machining sectors. At the same time, because of the motion of the rotating motors, the effects of vibration are investigated carefully and how to minimize the various errors with the help of intelligent monitoring with SMART sensors are also observed. Finally, this standpoint survey provides a rigorous outlook of the various algorithms used in the last several years in autonomous grinding manufacturing which will help the Robot industry like factory 5.0 adopt GM practices.