Show simple item record

contributor authorQiao, Guixiu
contributor authorWeiss, Brian A.
date accessioned2019-09-18T09:01:18Z
date available2019-09-18T09:01:18Z
date copyright5/14/2019 12:00:00 AM
date issued2019
identifier issn1087-1357
identifier othermanu_141_7_071006
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4257959
description abstractRobot accuracy degradation sensing, monitoring, and assessment are critical activities in many industrial robot applications, especially when it comes to the high accuracy operations which may include welding, material removal, robotic drilling, and robot riveting. The degradation of robot tool center accuracy can increase the likelihood of unexpected shutdowns and decrease manufacturing quality and production efficiency. The development of monitoring, diagnostic and prognostic (collectively known as prognostics and health management (PHM)) technologies can aid manufacturers in maintaining the performance of robot systems. PHM can provide the techniques and tools to support the specification of a robot’s present and future health state and optimization of maintenance strategies. This paper presents the robotic PHM research and the development of a quick health assessment at the U.S. National Institute of Standards and Technology (NIST). The research effort includes the advanced sensing development to measure the robot tool center position and orientation; a test method to generate a robot motion plan; an advanced robot error model that handles the geometric/nongeometric errors and the uncertainties of the measurement system, and algorithms to process measured data to assess the robot’s accuracy degradation. The algorithm has no concept of the traditional derivative or gradient for algorithm converging. A use case is presented to demonstrate the feasibility of the methodology.
publisherAmerican Society of Mechanical Engineers (ASME)
titleIndustrial Robot Accuracy Degradation Monitoring and Quick Health Assessment
typeJournal Paper
journal volume141
journal issue7
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.4043649
journal fristpage71006
journal lastpage071006-7
treeJournal of Manufacturing Science and Engineering:;2019:;volume( 141 ):;issue: 007
contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record