Call for Papers on Enabling Technologies for Smart Manufacturing
The Journal of Intelligent Manufacturing is seeking submissions to a forthcoming Special Issue on Enabling Technologies for Smart Manufacturing: Changing the Landscape of Research and Development.
- Enabling Technologies for Smart Manufacturing: Changing the Landscape of Research and Development
Closes December 31, 2020
Aims and Scope
New enabling technologies for smart manufacturing have been developed recently, thus providing promising approaches to address the above challenges. These new enabling technologies include Internet of Things (IoT), Cyber-Physics System (CPS), Big Data Analytics (BDA), Digital twin, and Cloud Computing (CC), have been changing the landscape of research and development (R&D) in Modern Manufacturing greatly; For instance, IoT devices can communicate and interact with each other, and thus enable the real-time monitoring and dynamic control. Big Data analytics together with AI can help to mine out potential rules, knowledge and patterns, in order to smart prediction, evaluation, optimization and decision-making. DT aims at constructing interactive virtual mirrors for physical assets and fusing both real and simulated data to give more insights. These technologies can be combined with each other and greatly promote the innovation of manufacturing in design, production, operation and maintenance, etc.
Technological advancements in the ability to collect, transfer and analyze vast amounts of data very rapidly are at the core of this trend. Closely related, smart manufacturing is a concept that aims at developing smart factories that integrate these new technologies to rapidly adapt and respond to changes in the markets’ demands for high-quality products. In practice, smart factories lie at the core of both, Industry 4.0 and smart manufacturing. During the past few years, many countries have put forward their national manufacturing strategies. Although these strategies are proposed and developed under different backgrounds, their common objective is to achieve smart manufacturing, which satisfies the demands of socialization, personalization, servitization, intelligence and energy-conservation. However, for the smart manufacturing, realizing smart interconnection and interaction, data mining, ubiquitous computing, and seamless cyber-physical fusion, etc., are always bottlenecks and challenges.
This special issue aims to provide a platform for researchers to showcase findings and explore emerging technologies in the design and implementation of smart manufacturing.
The research topics covered by the journal are (but not limited to):
- AI based algorithms and tools for smart manufacturing
- Machine learning techniques to improve process control and part quality.
- New IoT tools and applications for smart manufacturing
- Digital twin driven smart manufacturing
- New human machine interface and communication technologies.
- Cyber physical systems for the design and operation of smart manufacturing facilities.
- New sensors and controls for machine tools, fixtures, and other smart things.
- Use of cloud, distributed and digital manufacturing paradigms in cyberphysical systems.
- Manufacturing data analysis and diagnostics for real-time reporting using intranet capabilities and/or the cloud.
- Design and deployment of networked-distributed digital manufacturing paradigms.
Last Date for Manuscript Submission: 31 December 2020
Notification to Authors: 15 March 2021
Revised Manuscript Due: 15 May 2021
Decision Notification: 20 June 2021
Submission of a manuscript implies: that the work described has not been published before; that it is not under consideration for publication anywhere else; that its publication has been approved by all co-authors, if any, as well as by the responsible authorities – tacitly or explicitly – at the institute where the work has been carried out. The publisher will not be held legally responsible should there be any claims for compensation. https://www.editorialmanager.com/jims/default.aspx
Dr. V. Vinoth Kumar
Department of Computer Science and Engineering
MVJ College of Engineering, Bangalore-67, India,
Dr. Gautam Srivastava,
Department of Computer Science
Brandon University, Canada (IEEE Senior Member)
Dr. Ahmed A. Elngar
Faculty of Computers & Artificial Intelligence
Beni_Suef University Beni-Suef, Egypt,
Dr. Polinpapilinho F. Katina
Department of Informatics and Engineering Systems
University of South Carolina Upstate, USA.