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Multiple Setups Analysis of Industrial Robotic Operation

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2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Manufacturing Division Technical Session - Robotics and Manufacturing

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Hayder Zghair P.E. Pennsylvania State University

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The operational motion program of industrial robots is based on point location learning. The program has been developed to content a set of programmable blocks of moving commands and characteristics of point-to-point jogging. Each bock specifies the movement type from current point to next point and defines associated characteristics in terms of trajectory design requirement (TDR). Robotic’ speed and path of the movements are cumulatively essential variables for the programming in terms of resulting robotic trajectory resolution (RTR). An efficient cycle time is required to plan the utilization of industrial robotic operation (IRO) for certain production terms, therefore programming the speed to be as fast as possible is satisfying IRO productivity. Likewise, the designated path needs to be undeviated during IRO operating. Therefore, RTR can be measured relatively by changing the speed and the path characteristics that eventually optimize TDR objectively. One of the challenges to effectively operate IRO is that users need to program with a trade-off approach for optimizing the TDR; in other words, re-programming the speed rate and path termination as motion program variables for an effective RTR. This research work presents an empirical approach that analyzing the TDR variables depending on measuring the response characteristics of RTR. Single-factorial design of experimentation has been applied for operating FANUC Robot LR-Mate 200iB and collecting the data. Results analysis of variables effect validates the applicability of the empirical approach.

Zghair, H. (2021, July), Multiple Setups Analysis of Industrial Robotic Operation Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference.

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