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International Journal of System Assurance Engineering and Management - Call for Papers: Special Issue on 'Knowledge Based Strategies for Industrial Automation Systems'

Industrial automation systems are contemplated to function automatically to improve effectiveness and to decrease human tasks within the industry. Such automation helps to improve productivity, homogeneity of the products also reduces assembly times and human error. Industrial automation is accomplished mainly by using computer-aided planning, computer-supported design and manufacturing, automated storage and retrieval systems, and by material handling systems.

A knowledge-based system (KBS) aims to capture the knowledge from a variety of sources similar to an artificial intelligence (AI) system including human experts and use it to achieve an efficient and quick decision-making process. AI is transfiguring almost all sectors of technology. Other than decision making, these systems are also used to support humans in solving problems, particularly complex issues, learning, and other activities. KBS is composed of a knowledge base, which acts as the knowledge repository, and an interface engine, which acts as the search engine. Similarly, AI can be used in the industrial sector for predicting future machinery problems, maintenance, and repair and make the industry professionals take suitable preventive measures.

Industrial automation along with AI has developed remarkably in recent years. With AI applications any machine can be able to replete real-world human jobs. Development in machine learning techniques, advances in sensors, and therefore the growth of computing power has helped the industrial automation systems. Some of the common skills currently imitated by AI include voice realization, visual understanding, versatility, and decision-making. Industrial AI can be easily included with all available services or products to create a more productive, faithful, safer, and improve products lifetime. By analyzing the sensor data with AI technology industrialists can easily find out the potential discontinuance and serious incidents and also forecast its maintenance and repairing schedule before the failure.

The aim of the present special issue is to provide an overview of novel applications for knowledge-based technologies and strategies for industrial automation systems, to improve the product quality, production systems, and overall performance. Submissions involving case studies, scientific papers, and innovative applications are welcomed.

Included potential topics but not limited to:

  • Efficient knowledge-based planning for industrial automation systems
  • Impacts of AI in industrial automation systems
  • Real-time applications of industrial automation systems
  • Evaluating the performance of industrial automation systems based on AI
  • Knowledge-based strategic approach better implementation of automation system
  • Knowledge-based cyber-physical systems for industrial automation
  • Applications of automated perception approach in industrial automation
  • Knowledge-based strategies in complex system design for automation in the manufacturing industry
  • Knowledge-based decision support system and its applications
  • Data and knowledge-based management strategies for industrial automation systems
  • Innovative tools for industrial automation system
  • IoT and Machine learning algorithms for industrial automation system
  • AI and ML for Analysis and predictive maintenance to enhance industrial automation
  • Programmable automation system and flexible automation system
  • Intelligent data processing and system modeling methods for industrial automation with Knowledge-based technologies 

Manuscript Submission Information:

Original and unpublished works on any of the topics aforementioned or related are welcome. The Journal has a rigorous peer-reviewing process and at least two referees will review papers. All submitted papers must be formatted according to the journal's instructions, which can be found at: 
https://www.springer.com/journal/13198/submission-guidelines (this opens in a new tab)

Please submit your manuscript through the Journal’s homepage at https://www.springer.com/journal/13198 (this opens in a new tab)

To ensure a paper is considered for the Special Issue, reply “yes” when asked during submission whether it is intended for a special issue and select “Special Issue on Knowledge Based Strategies for Industrial Automation Systems” from the drop-down menu.

For questions, please contact:

Guest Editors:

Mazdak Zamani, Adjunct Assistant Professor, Courant Institute of Mathematical Sciences, New York University, USA; Email: mazdak.zamani@nyu.edu (this opens in a new tab)

Jiří Koziorek, Head of Department, Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science,  VSB-Technical University of Ostrava, Czech Republic; Email: jiri.koziorek@vsb.cz

Shahpour Alirezaee, Assistant Professor, Faculty of Engineering, University of Windsor, Canada; Email: alirezae@uwindsor.ca (this opens in a new tab)


Important Dates:
Manuscript submission deadline:  30 April 2024
Interim decision: 30 May 2024
Revised version due date: 20 July 2024
Second round of review: 25 August 2024
Acceptance: 30 September 2024

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