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Examining Workcell Kinematic Chains to Identify Sources of Positioning Degradation

Published

Author(s)

Alexander S. Klinger, Brian A. Weiss

Abstract

Automated industrial workcells are becoming increasingly complex and varied due to greater accessibility of advanced robotic and sensing technologies. Degradation monitoring and diagnostics must advance to reduce the impact of increased system complexity on troubleshooting faults and failures and to optimize system operations. A new methodology is being developed for the design and implementation of monitoring kinematic chains commonly found in robot workcells. This method will enable the identification of degraded components which contribute to relative positioning accuracy error between moving objects, tools, devices, and other components. The proposed methodology is being developed and tested on a six degree of freedom industrial robot arm workcell use case developed at the National Institute of Standards and Technology (NIST). Industrial robot users and integrators can use this method to examine the kinematic chains within their workcells and design a key position monitoring implementation. With the added key position monitoring, degradations can be identified at a designed resolution allowing for enhanced maintenance planning and production control. The methodology will be extended to other manufacturing workcells in the future.
Proceedings Title
Annual Conference of the Prognostics and Health Management Society 2018
Conference Dates
September 24-27, 2018
Conference Location
Philadelphia, PA, US

Keywords

industrial robot systems, diagnostics, manufacturing processes, manufacturing systems, condition monitoring, prognostics, use cases, test bed, workcell, kinematics

Citation

Klinger, A. and Weiss, B. (2018), Examining Workcell Kinematic Chains to Identify Sources of Positioning Degradation, Annual Conference of the Prognostics and Health Management Society 2018, Philadelphia, PA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=926386 (Accessed April 26, 2024)
Created September 26, 2018, Updated April 11, 2022