Call for Papers
Special Issue on Modern Automation Technologies and Virtual Engineering for Performance Analysis in Manufacturing
Modern automation technologies produce a high-quality product with minimum resource utilization to achieve sustainable manufacturing (SM). By developing innovative algorithms, models, heuristics, hardware, and software in broad areas, sustainable automation technology produces a more green, efficient, and environmental-friendly production system. Cyber-physical systems (CPS), virtual reality (VR), blockchain technology, artificial intelligence (AI), machine learning (ML), and big data analytics are considered as some of the key elements for modern automation technology. Virtual Engineering (VE) consistently has great benefits in structural system characterization, behaviour modelling, and communicating between the different subsystems. These days, with the factory engineering aspect VE, plays a major part in the development of cyber-physical systems at different levels of design validation. It also provides the ability to simulate and interchange those models based on their applications in the simulation and management process. It helps greatly in product enhancement and to maintain an optimal operation cycle.
Even though digitization in supply chains helps to achieve operational effectiveness and cost reduction, the impact of sustainable supply chains on automation technologies needs to be explored. Big data analytics help in future challenges related to smart manufacturing to attain sustainability. Modern automation technologies with virtual engineering for digital manufacturing to attain efficient performance, flexibility, safety, time and cost-effectiveness, etc., Performance assessment methodologies necessary for assuring better improvement manufacturing concerning wide applications with a real-time date. Optimized accumulation and analysis of these real-time data required for efficient handling of the complex and dynamic process. Thus, advancements in technological infrastructure with physical systems, management, and business models are in demand. Novel frameworks are to be developed to cover both the product and manufacturing system life cycle concerning the performance analysis.
We welcome submissions of state-of-the-art research of theoretical or practical significance that will support and foster technology improvements related to performance analysis based on modern automation and virtual engineering in manufacturing. Potential topics for the special issue include, but are not limited to:
- Performance analysis for efficient control in manufacturing
- Monitoring techniques for optimizing planning operations, productivity, decision-making
- Reliability analysis applications in the improvement of manufacturing
- Sustainability assessment tools for risk detection and prevention in manufacturing
- Virtual engineering and product life cycle analysis for efficiency
- Real-time advanced data analytics and automation in manufacturing applications
- Novel simulation-based performance analysis for manufacturing
- Virtual Prototyping in manufacturing for design and safety analysis
- 5G technology in digital manufacturing-based performance analysis
- Challenges and implementation CPS in manufacturing applications and analysis
- Sustainable production automation (SPA) and VE applications in manufacturing
- Advances in performance metrics framework for sustainable manufacturing
Timeline:
Manuscript Submission: August 01, 2022
Interim decision to authors: October 01, 2022
Revised submission: December 30, 2022
Accept decision: February 01, 2023
Guest Editors
Dr. Brian Prasad (Managing Editor)
Editor-in-Chief,
Concurrent Engineering Journal, Sage Publisher.
United States
Email: pradsadbiren@gmail.com, editor@brianprasad.com, brianprasad54@gmail.com
https://scholar.google.com/citations?user=pxEL5_YAAAAJ&hl=en
http://brianprasad.weebly.com/
Professor J. Paulo Davim
Department of Mechanical Engineering,
University of Aveiro, Portugal
Email: pdavim@ua.pt
https://scholar.google.com/citations?user=EqJnB5EAAAAJ&hl=en
http://machining.web.ua.pt/pers-davim.htm
Prof. Erwin Rauch
Industrial Engineering and Automation
Faculty of Science and Technology
Free University of Bozen-Bolzano,Italy
Email: Erwin.Rauch@unibz.it
https://scholar.google.de/citations?user=yzEy7PsAAAAJ&hl=de
https://www.unibz.it/de/faculties/sciencetechnology/academic-staff/person/17786-erwin-rauch
Dr. Tao Peng
Associate Professor
Institute of Industrial Engineering
School of Mechanical Engineering, Zhejiang University, China
Email: tao_peng@zju.edu.cn
https://person.zju.edu.cn/en/peng_tao
Dr.K. Vijayakumar
Department of Artificial Intelligence and Data science
St. Joseph’s Institute of Technology, India
Email: vijayakumar@stjosephstechnology.ac.in
https://www.stjosephstechnology.ac.in/web/cse/vijayakumar.php
http://scholar.google.co.in/citations?user=q2gS8pAAAAAJ&hl=en