Manufacturing Line Design Configuration with Optimized Resource Groups

  • Takahiro Nakano
  • , Kajita Daiki
  • , Heming Chen
  • , Ilya Kovalenko
  • , Efe Balta
  • , Yassine Qamsane
  • , Kira Barton

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

6 Scopus citations

Abstract

This research aims to develop methods to quickly build new manufacturing lines in response to changes in product varieties and manufacturing fluctuations in a factory. We propose a meta-heuristic algorithm for solving large-scale optimizations of the line design process, which includes resource configuration, process design, control design, and line configuration. The proposed framework improves the automation and system-level interactions of the line design process as compared to conventional methods that manually solve each step in the process design problem individually using skilled line engineers with previous experience. This research introduces the concept of a resource group or module that consists of various manufacturing resources such as robots, tools, autonomous guided vehicles, and conveyors. The line design process is then reconfigured for module or group configuration. To demonstrate the proposed framework, a case study is conducted in which the proposed framework is applied to the line design of an assembly manufacturing facility with production costs and manufacturing lead times selected as the key performance indicators of interest. Results indicate improved line costs and manufacturing lead times concurrently.

Original languageEnglish (US)
Title of host publication2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
PublisherIEEE Computer Society
Pages625-632
Number of pages8
ISBN (Electronic)9781665418737
DOIs
StatePublished - Aug 23 2021
Event17th IEEE International Conference on Automation Science and Engineering, CASE 2021 - Lyon, France
Duration: Aug 23 2021Aug 27 2021

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2021-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Country/TerritoryFrance
CityLyon
Period8/23/218/27/21

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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