Special Issue "Model-Based Systems Engineering: Rigorous Foundations for Digital Transformations in Science and Engineering"
Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 23783
2. Department of Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
Interests: conceptual modelling; object–process methodology; model-based systems engineering; systems and software engineering; Industry 4.0; complex systems; Internet of Things; Internet of Robotic Things; cyber-physical systems; model-based systems biology
Interests: model-based systems engineering; cyber-physical informatics; digital systems engineering; model informatics and analytics; modelling and simulation of cyber-physical systems; command and control; enterprise architectures
Over the last decade, recognition is growing that models are essential as formal representations of complex systems for transforming systems engineering (SE) in a rigorous and robust meta-engineering discipline, positioning the model-based systems engineering (MBSE) paradigm as the leading SE approach. Although enterprises and organizations of all kinds and sizes have started adopting MBSE, emerging information and communication technologies, such as the Internet of Things (IoT) and the Internet of Robotic Things (IoRT), are shaping Industry 4.0, the fourth industrial revolution. This is only one of the expressions of the digital transformation we are witnessing in a variety of traditional ecosystems, from product conception, design, development, and service delivery, through supply chains and manufacturing, to customer relationship management and social networking. These emerging technologies have been challenging traditional business and operations practices; they have also begun to pose new challenges for the MBSE paradigm, which, in addition to its previous role, must now adopt and adapt to the digital transformation. Leading paradigms for complex systems modelling, analysis, and simulation, including the systems modelling language (SysML), the unified modelling language (UML), or the object process methodology (OPM), must overcome new challenges, such as the modelling of cyber-physical interactions, the digital twin revolution, continuous integration and innovation, and high edge computing workloads supported by cloud-based infrastructure. To meet these challenges, novel approaches for modelling and executable simulation of conceptual models are needed. These include rich and evolving requirements modelling; joint conceptual–computational modelling and execution; model-in-the-loop frameworks; multi-model orchestration; model-based extended (MBX) approaches that rely on the system models for tasks such as risk management, testing, and verification; product and service cataloguing; maintenance and operations; and model analytics to drive stakeholder decisions. Given these developments, enablers, such as model-based teamwork, management commitment, stakeholder engagement, model curation, and model reuse, require fresh insight. Educating and training systems engineers that will be ready to cope with the digital systems engineering challenges, primarily Industry 4.0, need to be addressed as well. The recent COVID-19 pandemic is imposing even greater and historically unprecedented disruptions, transformations, and challenges in all avenues of human life, including healthcare, supply chains, manufacturing, commerce, energy, services, and socialization. MBSE can and should be instrumental in creating a smoother transformation to a new reality that will likely change how we live and operate in years to come.
We invite you to submit original research papers on these and related topics, some of which are listed in the keywords below.
Prof. Dov Dori
Dr. Yaniv Mordecai
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2300 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Model-based systems engineering (MBSE)
- Modelling languages and constructs for Industry 4.0
- Digital systems engineering
- Digital transformation
- Digital twin
- Smart factory, smart manufacturing
- Internet of Things (IoT)/Industrial Internet of Things (IIoT)
- Internet of Robotic Things (IoRT)
- Cyber-physical systems
- Cyber-physical informatics
- Model-based requirements
- Model-based testing
- MBSE training and education
- Model-based extended approaches (MBX): MB systems thinking, MB tradespace exploration, MB risk analysis, MB compliance assurance, MB diagnosis, MB operational planning, MB lifecycle support, etc.
- Model simulation and execution
- Model informatics and analytics
- Model-based application development and code generation
- Combining conceptual modeling with other SE techniques, such as systems dynamics, design structure matrix, axiomatic design
- Comparative studies in MBSE
- MBSE adoption, cost-benefit analysis, and return-on-investment case studies
- Model-based collaboration, teamwork, knowledge management, and group communication
- Innovative applications of MBSE, such as for digital enterprise architectures, evolving systems, intelligent transportation systems, mobilization of healthcare systems, and coping with COVID 19
Model-Based Systems Science
Modeling Applied Science Research Systems