TY - GEN
T1 - Smartmanufacturing
T2 - ASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018
AU - Mehta, Parikshit
AU - Rao, Prahalada
AU - Wu, Zhenhua David
AU - Jovanović, Vukica
AU - Wodo, Olga
AU - Kuttolamadom, Mathew
N1 - Publisher Copyright:
Copyright © 2018 ASME.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Advanced Analytics
KW - Data Infrastructure
KW - Data-driven Quality Control
KW - Digital Manufacturing
KW - Industrial Processes
KW - Industry 4.0
KW - Process Mining
KW - Process Modeling
UR - https://www.scopus.com/pages/publications/85054990170
U2 - 10.1115/MSEC2018-6658
DO - 10.1115/MSEC2018-6658
M3 - Conference contribution
AN - SCOPUS:85054990170
SN - 9780791851371
T3 - ASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018
BT - Manufacturing Equipment and Systems
PB - American Society of Mechanical Engineers (ASME)
Y2 - 18 June 2018 through 22 June 2018
ER -