An Integrated Framework for Dynamic Manufacturing Planning to Obtain New Line Configurations

Laxmi Poudel, Ilya Kovalenko, Ruijie Geng, Matsui Takaharu, Youichi Nonaka, Nakano Takahiro, Umeda Shota, Dawn M. Tilbury, Kira Barton

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

2 Scopus citations

Abstract

With an increase in demand for individualized and personalized products, manufacturers are turning their attention to more flexible manufacturing systems that can be rapidly reconfigured, based on needs. However, the existing approaches primarily rely on manual reconfiguration performed or managed by subject-matter experts, which is time-consuming and labor-intensive. To this end, we propose an integrated framework that generates multiple feasible configurations, conducts simulations to evaluate the performance of the proposed configurations, and performs a multi-objective optimization to derive a set of ordered solutions from which the manufacturer may select their desired option. The framework consists of three core components: Digital Twin Pool, Application Plane, and Decision Maker. The DT pool consists of DTs grouped together based on functionalities. The individual DT request required information from different applications in the Application Plane. The applications include a semantic-based ontology map for knowledge representation and storage, and a simulation application for simulating generated line configurations to obtain necessary attribute values such as throughput, yield, cycle times, etc. The Decision Maker includes an optimizer, which takes multiple configurations obtained from the DT pool and runs a multi-objective optimization. The output of the Decision Maker is a set of feasible solutions that will be provided to the user. A case study is presented to demonstrate the efficacy and usefulness of the proposed framework.

Original languageEnglish (US)
Title of host publication2022 IEEE 18th International Conference on Automation Science and Engineering, CASE 2022
PublisherIEEE Computer Society
Pages328-334
Number of pages7
ISBN (Electronic)9781665490429
DOIs
StatePublished - 2022
Event18th IEEE International Conference on Automation Science and Engineering, CASE 2022 - Mexico City, Mexico
Duration: Aug 20 2022Aug 24 2022

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2022-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference18th IEEE International Conference on Automation Science and Engineering, CASE 2022
Country/TerritoryMexico
CityMexico City
Period8/20/228/24/22

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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