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Smartmanufacturing: State-of-The-Art reviewin context of conventional &modernmanufacturing processmodeling,monitoring&control

  • Parikshit Mehta
  • , Prahalada Rao
  • , Zhenhua David Wu
  • , Vukica Jovanović
  • , Olga Wodo
  • , Mathew Kuttolamadom
  • Arconic Technology Center
  • University of Nebraska-Lincoln
  • Virginia State University
  • Old Dominion University
  • Texas A&M University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Scopus citations

Abstract

With the advances in automation technologies, data science, process modeling and process control, industries worldwide are at the precipice of what is described as the fourth industrial revolution (Industry 4.0). This term was coined in 2011 by the German federal government to define their strategy related to high tech industry [1], specifically multidisciplinary sciences involving physicsbased process modeling, data science and machine learning, cyber-physical systems, and cloud computing coming together to drive operational excellence and support sustainable manufacturing. The boundaries between Information Technologies (I.T.) and Operation Technologies (O.T.) are quickly dissolving and the opportunities for taking lab-scale manufacturing science research to plant and enterprise wide deployment are better than ever before. There are still questions to be answered, such as those related to the future of manufacturing research and those related to meeting such demands with a highly skilled workforce. Furthermore, in this new environment it is important to understand how process modeling, monitoring, and control technologies will be transformed. The aim of the paper is to provide state-ofthe-art review of Smart Manufacturing and Industry 4.0 within scope of process monitoring, modeling and control. This will be accomplished by giving comprehensive background review and discussing application of smart manufacturing framework to conventional (machining) and advanced (additive) manufacturing process case studies. By focusing on process modeling, monitoring, analytics, and control within the larger vision of Industry 4.0, this paper will provide a directed look at the efforts in these areas, and identify future research directions that would accelerate the pace of implementation in advanced manufacturing industry.

Original languageEnglish
Title of host publicationManufacturing Equipment and Systems
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Print)9780791851371
DOIs
StatePublished - 2018
EventASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018 - College Station, United States
Duration: Jun 18 2018 → Jun 22 2018

Publication series

NameASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018
Volume3

Conference

ConferenceASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018
Country/TerritoryUnited States
CityCollege Station
Period06/18/18 → 06/22/18

Keywords

  • Advanced Analytics
  • Data Infrastructure
  • Data-driven Quality Control
  • Digital Manufacturing
  • Industrial Processes
  • Industry 4.0
  • Process Mining
  • Process Modeling

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