2017 International Conference on Advanced Systems and Electric Technologies (IC_ASET) 2017
DOI: 10.1109/aset.2017.7983729
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Data analytics for predictive maintenance of industrial robots

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Cited by 63 publications
(29 citation statements)
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“…Aivaliotis et al [106] developed a control system to predict the remaining time that the resources perform its intended function. The model simulate data from machine controller and external sensors to schedule maintenance activities.…”
Section: Predictive Maintenancementioning
confidence: 99%
See 1 more Smart Citation
“…Aivaliotis et al [106] developed a control system to predict the remaining time that the resources perform its intended function. The model simulate data from machine controller and external sensors to schedule maintenance activities.…”
Section: Predictive Maintenancementioning
confidence: 99%
“…Borgi et al [106] analyzed electrical data to diagnose and prognosticate industrial robot. Tsai and Ko [107] analyzed time-frequency signal of servo motors embedded in industrial robot.…”
Section: Predictive Maintenancementioning
confidence: 99%
“…Comprehensive insight into the current condition of a component or machine is necessary for PdM (Sipos et al 2014). In a broader sense, data are key for PdM (Borgi et al 2017). Usually, a central server is used to collect, transmit and process data (Wang et al 2017).…”
Section: Predictive Maintenance and The Related Literaturementioning
confidence: 99%
“…PdM uses data, especially sensor data obtained from IoT devices, to optimize maintenance activities. Often, this process also includes "condition monitoring" (Khazraei and Deuse 2011;Borgi et al 2017).…”
Section: Introductionmentioning
confidence: 99%
“…But the question arises do we know will the robot perform the given task accurately or even if it does it accurately, does it do it the right way. To overcome such difficulties and ease the human decision making for assigning task to robot, we need algorithms to predict the next result of robot [1], using its dynamic dataset which is integrated with the cloud [2]. The program will be connected to cloud system and will provide output with a prediction graph.…”
Section: Introductionmentioning
confidence: 99%