Joint optimization of operating mode and part sequence for robot loading process considering real-time health condition

Yunyi Kang, Feng Ju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we develop a decision-making framework for real-time production control considering the condition variation of robotic arms. Specifically, the temperature dynamics of robotic arms under different operation conditions is analyzed to assess the robotic arm's health status. Statistical models based on the observation of real-time information is firstly built to characterize the relationship between the robot temperature and time, considering various operation modes (i.e., capacity, working mode, speed). Then a loading process using the robotic arm is investigated and a continuous space Markov decision model is formulated to minimize the total processing time for a limited batch of products with different types. Numerical studies suggest that the performance of the proposed method is significantly better than the benchmark plans. Such a study reflects the necessity of joint consideration on the health condition of production assets together with production control, to maintain high productivity and utilization of the assets in production systems.

Original languageEnglish (US)
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE Computer Society
Pages48-53
Number of pages6
ISBN (Electronic)9781728103556
DOIs
StatePublished - Aug 2019
Event15th IEEE International Conference on Automation Science and Engineering, CASE 2019 - Vancouver, Canada
Duration: Aug 22 2019Aug 26 2019

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2019-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference15th IEEE International Conference on Automation Science and Engineering, CASE 2019
Country/TerritoryCanada
CityVancouver
Period8/22/198/26/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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