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Metaheuristic Algorithms in Industry 4.0
Aim and Scope
Optimization is widely used in all disciplines for various
industrial applications including product design, static/transient
analyses, plant layout, supply chain, inventory planning,
production planning/scheduling, automation, robotics, building
architecture, material handling, tooling, assembly line balancing,
system modeling/identification, tuning of various controllers,
machine learning and many more. Due to increasing industry 4.0
practices, massive industrial process data is now available for
researchers for modeling and optimization. Artificial intelligence
methods can be applied to the ever-increasing process data to
achieve robust control against foreseen / unforeseen system
fluctuations. Smart computing techniques, machine learning, deep
learning and computer vision will be inseparable from the highly
automated factories of tomorrow. Effective cybersecurity will be a
must for all internet of things (IoT) enabled work and office
spaces.
Optimization promises to play a pivotal role in this interplay of
physical machines, control systems and artificial intelligence.
However, the traditional optimization methodologies are inept at
handling complexities of big data analytics and new age dynamic
systems. Metaheuristics are nature inspired answers to such 21st
century world problems. Metaheuristics are typically socio
inspired, bio inspired or physics derived algorithms based on
simple principles that have proven effective in varied domains.
With respect to advanced control systems, metaheuristics can be
applied for selection of controllers as per different applications
such as auto tuning of systems. Effective industry 4.0
implementation will include integration of cyber physical systems,
control systems, IoT, smart computing, novel sensor applications,
collaborative robotics, intelligent fault diagnosis and predictive
maintenance for smart factories of tomorrow.
We invite original chapter contributions (industrial case studies
will be preferred) associated with metaheuristics in industry 4.0
as per the following list (not limited to) -
1. Introduction to Metaheuristics
2. Introduction to Industry 4.0
3. Survey on Metaheuristics in Control Systems
4. Survey on Metaheuristic Applications in Sensor Networks
5. Real Time System Identification and Advanced Controllers for
Industry 4.0 - case studies involving metaheuristics
6. Wireless Sensor Networks and Metaheuristics in Industry 4.0
7. Survey on Cyber Physical Systems and Smart Computing
8. Cyber Physical Systems and Metaheuristics in Industry 4.0
9. Metaheuristics in Machine Learning / Deep Learning and
Cybersecurity (Industry 4.0 perspective)
10. Survey on Evolution of Robotics and Smart Factories
11. Metaheuristics in Robotics and Smart Manufacturing
12. Metaheuristics in Predictive Analytics / Predictive
Maintenance
Interested contributors are requested to prepare chapter(s) from
the above list and send submissions to the Editors at
chair.oatresearchlab@gmail.com<mailto:chair.oatresearchlab@gmail.com>.
Important Dates
Full Chapter Submission: October 31, 2020
(No more than 30 pages)
Chapter Review Notification: November 25, 2020
Revised Chapter Due: December 25, 2020
Final Acceptance: January 15, 2021
Expected Publication Date: March 15, 2021
Editors
Pritesh Shah
Symbiosis Institute of Technology
Symbiosis International (Deemed University)
Pune 412115, MH, India
Email:
pritesh.shah@sitpune.edu.in<mailto:pritesh.shah@sitpune.edu.in>
Ravi Sekhar
Symbiosis Institute of Technology
Symbiosis International (Deemed University)
Pune 412115, MH, India
Email:
ravi.sekhar@sitpune.edu.in<mailto:ravi.sekhar@sitpune.edu.in>
Anand J Kulkarni
Symbiosis Center for Research and Innovation
Symbiosis International (Deemed University)
Pune 412115, MH, India
Email:
anand.kulkarni@sitpune.edu.in<mailto:anand.kulkarni@sitpune.edu.in>;
kulk0003@ntu.edu.sg<mailto:kulk0003@ntu.edu.sg>
Patrick Siarry
Laboratory of Image, Signal and Intelligent Systems
Paris-Est Creteil University, France
Email:
siarry@u-pec.fr<mailto:siarry@u-pec.fr>
--
Anand J Kulkarni PhD, MASc, BEng, DME
Associate Professor
Symbiosis Center for Research and Innovation
Symbiosis International (Deemed University)
Pune 412 115, MH, India
Email:
anand.kulkarni@sitpune.edu.in<mailto:anand.kulkarni@sitpune.edu.in>
kulk0003@ntu.edu.sg<mailto:kulk0003@ntu.edu.sg>;
anandmasc@gmail.com<mailto:anandmasc@gmail.com>
URL:
sites.google.com/site/oatresearch/anand-jayant-kulkarni
<http://sites.google.com/site/oatresearch/anand-jayant-kulkarni>
Ph: 91 20 6193 6790
ResearcherID:
www.researcherid.com/rid/O-3585-2016<http://www.researcherid.com/rid/O-3585-2016>
ORCID ID:
orcid.org/0000-0001-6242-9492
<http://orcid.org/0000-0001-6242-9492>
Google Scholar:
scholar.google.ca/citations?user=IAvtDokAAAAJ&hl=en
<http://scholar.google.ca/citations?user=IAvtDokAAAAJ&hl=en>
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