A Digital Twin Model for Enhancing Performance Measurement in Assembly Lines

Research output: Chapter in Book/Published conference outputChapter

Abstract

Dynamic manufacturing processes are characterized by a lack of coordination, complexity and sheer volumes of data. Digital transformation technologies offer the manufacturers the capability to better monitor and control both assets and production. This provides also an ever-improving ability to investigate new products and production concepts in the virtual world while optimizing future production with IoT-captured data from different devices and shop floor machine centres. In this study, a digital twin is presented for an assembly line, where IoT-captured data is fed back into the digital twin enabling manufacturers to interface, analyse and measure the performance in real-time of a manufacturing process. The digital twin concept is then applied to an assembly production plan found in the automotive industry, where actual data is considered to analyse how the digital duplicate can be used to review activities and improve productivity within all production shifts.

Original languageEnglish
Title of host publicationA Digital Twin Model for Enhancing Performance Measurement in Assembly Lines.
EditorsMaryam Farsi, Alireza Daneshkhah, Amin Hosseinian-Far, Hamid Jahankhani
Pages53-66
Number of pages14
ISBN (Electronic)978-3-030-18732-3
DOIs
Publication statusPublished - 23 Jul 2019

Publication series

NameInternet of Things
ISSN (Print)2199-1073
ISSN (Electronic)2199-1081

Keywords

  • Assembly lines
  • Automotive industry
  • Digital twins
  • Performance measurement

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