Journal articles on the topic 'Model Based Systems Engineering Approach'

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1

Živčák, Jozef, Tatiana Kelemenová, Michal Kelemen, and Vladislav Maxim. "Model-based Approach to Development of Engineering Systems." Acta Mechanica Slovaca 17, no. 3 (October 31, 2013): 56–62. http://dx.doi.org/10.21496/ams.2013.033.

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2

Friedland, Brittany, Robert Malone, and John Herrold. "Systems Engineering a Model Based Systems Engineering Tool Suite: The Boeing Approach." INCOSE International Symposium 26, no. 1 (July 2016): 386–98. http://dx.doi.org/10.1002/j.2334-5837.2016.00167.x.

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3

Ramos, A. L., J. V. Ferreira, and J. Barcelo. "Model-Based Systems Engineering: An Emerging Approach for Modern Systems." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42, no. 1 (January 2012): 101–11. http://dx.doi.org/10.1109/tsmcc.2011.2106495.

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4

Zhan, Guoxiong, Bingfeng Ge, Minghao Li, and Kewei Yang. "A Data-Centric Approach for Model-Based Systems Engineering." Journal of Systems Science and Information 3, no. 6 (December 25, 2015): 549–60. http://dx.doi.org/10.1515/jssi-2015-0549.

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Abstract A data-centric approach is proposed to facilitate the design and analysis of challenging complex systems and address the problems of currently existing model-based systems engineering (MBSE) methodologies. More specifically, based on three core steps of current MBSE methodologies, a high-level data meta-model, depicting the semantic relationships of high-level data concepts, is first presented to guide the data modeling for systems engineering (SE). Next, with respect to the six high-level data concepts, the data elements are collected as the modeling primitives to construct static and/or executable models, which can also act as a common and consistent data dictionary for SE. Then, the mapping associations amongst core data elements are established to associate the model elements in different steps and achieve the requirement traceability matrix. Finally, the feasibility of the proposed approach is demonstrated with an illustrative example.
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5

Holt, Jon, Simon Perry, Richard Payne, Jeremy Bryans, Stefan Hallerstede, and Finn Overgaard Hansen. "A Model-Based Approach for Requirements Engineering for Systems of Systems." IEEE Systems Journal 9, no. 1 (March 2015): 252–62. http://dx.doi.org/10.1109/jsyst.2014.2312051.

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6

WANG, Haoqi. "Model-based Axiomatic Design Approach for Complex Engineering Systems." Journal of Mechanical Engineering 54, no. 7 (2018): 184. http://dx.doi.org/10.3901/jme.2018.07.184.

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7

McDermott, Tom, and Molly Nadolski. "Integrated Community Resilience, A Model Based Systems Engineering Approach." INCOSE International Symposium 26, no. 1 (July 2016): 205–19. http://dx.doi.org/10.1002/j.2334-5837.2016.00155.x.

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8

Friedland, Brittany, John Herrold, Glendora Ferguson, and Robert Malone. "Conducting a Model Based Systems Engineering Tool Trade Study Using a Systems Engineering Approach." INCOSE International Symposium 27, no. 1 (July 2017): 1087–99. http://dx.doi.org/10.1002/j.2334-5837.2017.00414.x.

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9

Neureiter, Christian, and Christoph Binder. "A Domain-Specific, Model Based Systems Engineering Approach for Cyber-Physical Systems." Systems 10, no. 2 (March 26, 2022): 42. http://dx.doi.org/10.3390/systems10020042.

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Model Based Systems Engineering as a scientific discipline tries to address the increasing complexity of today’s cyber-physical systems by utilizing different kinds of models. In practical application, however, this approach is often constrained to SysML-based object modeling. Even though this appears to be a suitable approach for dealing with complexity, various restrictions limit stakeholder acceptance. Considering scientific discussions in the context of modeling shows two different schools of thought. On the one hand, arguments for more formalized and rigorous concepts can be found, where on the other hand, the need for more stakeholder-oriented and easier-to-understand concepts is postulated. As both are reasonable, the question of integration arises. To address this aspect, we developed the concept of Domain Specific Systems Engineering. Our research in this field lasted for nearly a decade, and different aspects have been investigated. This paper contributes a summary of the overall approach that integrates the various aspects investigated so far. Thus, the underlying concepts are explained, and the corresponding modeling stack and tool-chain are described in more detail. Further, the practical experiences from various case studies are summarized, and identified shortcomings are discussed.
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10

Beery and Paulo. "Application of Model-Based Systems Engineering Concepts to Support Mission Engineering." Systems 7, no. 3 (September 4, 2019): 44. http://dx.doi.org/10.3390/systems7030044.

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This paper presents an approach to the utilization of model-based systems engineering (MBSE) early in the system lifecycle, which focuses on early identification of desirable system characteristics to support mission engineering (ME). The paper relies on the definition of an analysis approach and the associated mapping of architectural products. The analysis strategy focuses on integration of the results of operational simulations and system synthesis models through tradespace visualization. The architectural mapping presents the association of Systems Modeling Language (SysML) products to the analysis strategy. The coordination of these elements is presented as a demonstration of the role that MBSE concepts can play in support of ME. The approach is demonstrated through a case study analysis of a conceptual mine warfare system conducting mine countermeasure operations.
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11

Ordoukhanian, Edwin, and Azad Madni. "Model-Based Approach to Engineering Resilience in Multi-UAV Systems." Systems 7, no. 1 (February 15, 2019): 11. http://dx.doi.org/10.3390/systems7010011.

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Multi-UAV Operations are an area of great interest in government, industry, and research community. In multi-UAV operations, a group of unmanned aerial vehicles (UAVs) are deployed to carry out missions such as search and rescue or disaster relief. As multi-UAV systems operate in an open operational environment, many disrupting events can occur. To this end, resilience of these systems is of great importance. The research performed and reported in this paper utilizes simulation-based research methodology and demonstrates that resilience of multi-UAV systems can be achieved by real-time evaluation of resilience alternatives during system operation. This evaluation is done using a dynamic utility function where priorities change as a function of context. Simulation results show that resilience response can in fact change depending on the context.
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12

Herzig, Sebastian J. I., Ahsan Qamar, and Christiaan J. J. Paredis. "An Approach to Identifying Inconsistencies in Model-based Systems Engineering." Procedia Computer Science 28 (2014): 354–62. http://dx.doi.org/10.1016/j.procs.2014.03.044.

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13

Micouin, Patrice. "Property-Model Methodology: A Model-Based Systems Engineering Approach Using VHDL-AMS." Systems Engineering 17, no. 3 (July 11, 2013): 249–63. http://dx.doi.org/10.1002/sys.21267.

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14

Mkaouar, Hana, Bechir Zalila, Jérôme Hugues, and Mohamed Jmaiel. "A formal approach to AADL model-based software engineering." International Journal on Software Tools for Technology Transfer 22, no. 2 (March 7, 2019): 219–47. http://dx.doi.org/10.1007/s10009-019-00513-7.

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15

Berges, Julius Moritz, Kathrin Spütz, Georg Jacobs, Julia Kowalski, Thilo Zerwas, Jörg Berroth, and Christian Konrad. "Automated Identification of Valid Model Networks Using Model-Based Systems Engineering." Systems 10, no. 6 (December 9, 2022): 250. http://dx.doi.org/10.3390/systems10060250.

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To handle increasing complexity in product development, model-based systems engineering (MBSE) approaches are well suited, in which the technical system is represented in a system model. To efficiently test requirements, domain models are integrated into the system model. For each purpose (e.g., battery lifetime calculation), there are typically several models at several fidelity levels. Since the model signatures (i.e., necessary inputs for the models and their outputs) differ depending on the fidelity level, not all models can be used in any development phase. In addition, due to the different model signatures, not all models can be combined arbitrarily to model networks. Currently, valid model networks in system models must be determined in a time-consuming, manual process. Therefore, this paper presents an approach that automates this task via the implementation of an algorithm that analyzes a system model and the model signatures and automatically returns all valid model networks. When input parameters, models or their signatures change, the algorithm updates automatically, and the user receives the valid model network without any manual effort. The approach is demonstrated with the running example of battery system development.
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Madni, Azad, and Shatad Purohit. "Economic Analysis of Model-Based Systems Engineering." Systems 7, no. 1 (February 20, 2019): 12. http://dx.doi.org/10.3390/systems7010012.

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In the face of ever-increasing complexity of systems and system development programs, several aerospace, automotive, and defense organizations have already begun or are contemplating the transition to model-based systems engineering (MBSE). The key challenges that organizations face in making this decision are determining whether it is technically feasible and financially beneficial in the long-run to transition to MBSE, and whether such transition is achievable given budgetary constraints. Among other cost drivers of this transition, are a new digital infrastructure, personnel training in MBSE, and cost-effective migration of legacy models and data into the new infrastructure. The ability to quantify gains from MBSE investment is critical to making the decision to commit to MBSE implementation. This paper proposes a methodological framework for analyzing investments and potential gains associated with MBSE implementation on large-scale system programs. To this end, the MBSE implementation problem is characterized in terms of: system complexity, environment complexity and regulatory constraints, and system lifespan. These criteria are applied to systems in twelve major industry sectors to determine MBSE investment and expected gains. Results from this cost-benefit analysis are used to justify investment in MBSE implementation where warranted. This approach is generic and can be applied to different sectors for economic evaluation of costs and benefits and justification of transition to MBSE if warranted.
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17

Ali, Michael. "2.3.2 Model-Based Systems Engineering And Object-Oriented Software Engineering: An Integrated Approach." INCOSE International Symposium 8, no. 1 (July 1998): 336–42. http://dx.doi.org/10.1002/j.2334-5837.1998.tb00049.x.

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18

Mažeika, Donatas, and Rimantas Butleris. "MBSEsec: Model-Based Systems Engineering Method for Creating Secure Systems." Applied Sciences 10, no. 7 (April 9, 2020): 2574. http://dx.doi.org/10.3390/app10072574.

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This paper presents how Model-Based System Engineering (MBSE) could be leveraged in order to mitigate security risks at an early stage of system development. Primarily, MBSE was used to manage complex engineering projects in terms of system requirements, design, analysis, verification, and validation activities, leaving security aspects aside. However, previous research showed that security requirements and risks could be tackled in the MBSE model, and powerful MBSE tools such as simulation, change impact analysis, automated document generation, validation, and verification could be successfully reused in the multidisciplinary field. This article analyzes various security-related techniques and then clarifies how these techniques can be represented in the Systems Modeling Language (SysML) model and then further exploited with MBSE tools. The paper introduces the MBSEsec method, which gives guidelines for the security analysis process, the SysML/UML-based security profile, and recommendations on what security technique is needed at each security process phase. The MBSEsec method was verified by creating an application case study that reflects real-world problems and running an experiment where systems and security engineers evaluated the feasibility of our approach.
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19

Hoffmann, Hans-Peter. "5.3.3 SysML-Based Systems Engineering Using a Model-Driven Development Approach." INCOSE International Symposium 16, no. 1 (July 2006): 804–14. http://dx.doi.org/10.1002/j.2334-5837.2006.tb02782.x.

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20

Zheng, Chen, Matthieu Bricogne, Julien Le Duigou, Peter Hehenberger, and Benoit Eynard. "Knowledge-based engineering for multidisciplinary systems: Integrated design based on interface model." Concurrent Engineering 26, no. 2 (October 26, 2017): 157–70. http://dx.doi.org/10.1177/1063293x17734591.

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Due to the growing number of requirements and the introduction of new technologies, current trends indicate that more disciplines have been involved into the system design. The design of such multidisciplinary systems, especially during the detailed design phase, requires designers and expertise from different disciplines. Therefore, the research question about how to achieve an integrated design for multidisciplinary systems has attracted the attention from both academia and industry. In order to achieve such integrated design for multidisciplinary systems, more and more researchers focus on the interface of multidisciplinary systems because the interface plays a quite significant role to guarantee the components defined by the designers of different disciplines integrate correctly and to eventually help them to achieve the integrated design. This article presents an interface knowledge base to manage the design data and rules related to the interfaces. A knowledge-based engineering approach is then proposed. By applying the knowledge-based engineering approach, a synergistic integration of the discipline-specific components can be realised; however, the unnecessary iterations can be avoided so that a concurrent design process during the detailed design phase can be achieved. This knowledge-based engineering approach is demonstrated by the case studies based on a partial discharge detection system and a belt conveyor system.
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21

Gaydamaka, K. "Archimate-Based Approach to Requirements Engineering." International Journal of Mathematical, Engineering and Management Sciences 4, no. 4 (August 1, 2019): 841–50. http://dx.doi.org/10.33889/ijmems.2019.4.4-066.

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Requirements engineering represents the most crucial stage in the complex systems development process. Contemporary methods of requirements engineering assume a wide application of models (described, for example, with such languages as SysML or OPM), which allows to ensure the consistency and completeness of the system descriptions. The article assesses the applicability of the Archimate language to support the process of requirements engineering when creating complex technical systems. Requirements engineering method for complex technical systems, suitable for models described by the Archimate language is proposed. Detailed example demonstrating the proposed method when developing system requirements is given. The limitations of the Archimate language applicability for the engineering of systems of various classes are described.
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22

Gianni, Daniele, Lindman Niklas, Fuchs Joachim, Suzic Robert, and Fischer Daniel. "A Model-Based Approach to Support Systems-of-Systems Security Engineering for Data Policies." INSIGHT 14, no. 2 (July 2011): 18–22. http://dx.doi.org/10.1002/inst.201114218.

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23

Lakshminarayanan, Sitaraman, and Manyphay Souvannarnarth. "1.1.2 Applying Model Based Systems Engineering approach to Smart Grid Software Systems Security Requirements." INCOSE International Symposium 22, no. 1 (July 2012): 13–20. http://dx.doi.org/10.1002/j.2334-5837.2012.tb01318.x.

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24

Kwon, Steve, Kimberly Page, and Kevin Weinstein. "Integrating a Model-Based Systems Engineering and Model-Based Product Support Approach for Affordable System Sustainment." INCOSE International Symposium 28, no. 1 (July 2018): 1412–19. http://dx.doi.org/10.1002/j.2334-5837.2018.00557.x.

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25

Motegi, Kazuhiro. "A Model-Based Approach for Micro Mobility Systems." Journal of The Japan Institute of Electronics Packaging 21, no. 5 (August 1, 2018): 438–43. http://dx.doi.org/10.5104/jiep.21.438.

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26

Verlan, Andriy, and Jo Sterten. "Approach to Energy Objects’ Dynamics Modelling Based on Singular Systems’ Elements." Mathematical and computer modelling. Series: Technical sciences 23 (December 6, 2022): 31–36. http://dx.doi.org/10.32626/2308-5916.2022-23.31-36.

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Over the last decades there has been substantial progress on the development of theory and numerical methods for singular systems (known also as descriptor systems, semistate systems, differential alge-braic systems, generalized state-space systems, etc.). The need for such methodsarisen primarily from the increased practical interest for a more general system description which takes the intrinsic physical sys-tem model structure into account. Besides that, many physical process-es are most naturally and easily modelled as mixed systems of differen-tial and algebraic equations (DAE). As the title implies the paper de-scribes the singular systems theory application in power systems dy-namics simulation, particularly considered an alternative method for energy systems’ mathematical models formulation based on the singu-lar systems theory elements with some indicative examples illustrating feasibility and efficiency of this approach
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Maleki, Elaheh, Farouk Belkadi, and Alain Bernard. "A Meta-model for Product-Service System based on Systems Engineering approach." Procedia CIRP 73 (2018): 39–44. http://dx.doi.org/10.1016/j.procir.2018.04.016.

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28

Göhler, Simon Moritz, Daniel D. Frey, and Thomas J. Howard. "A model-based approach to associate complexity and robustness in engineering systems." Research in Engineering Design 28, no. 2 (August 27, 2016): 223–34. http://dx.doi.org/10.1007/s00163-016-0236-1.

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Manfredi, Massimiliano, and Lucio Tirone. "Application of the Model Based Systems Engineering Approach for Modern Warship Design." INCOSE International Symposium 28, no. 1 (July 2018): 363–77. http://dx.doi.org/10.1002/j.2334-5837.2018.00487.x.

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30

Navas, Juan, Jean-Luc Voirin, Stephane Paul, and Stephane Bonnet. "Towards a Model‐Based approach to Systems and Cyber Security co‐engineering." INCOSE International Symposium 29, no. 1 (July 2019): 850–65. http://dx.doi.org/10.1002/j.2334-5837.2019.00639.x.

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31

Gordy, Lowell W., Donald R. Noel, Russell P. Rhoads, Camille M. Nichols, and Carol J. Gutierrez. "Process Change in Systems Engineering: From Document-Driven to Model-Based Approach." INCOSE International Symposium 7, no. 1 (August 1997): 281–87. http://dx.doi.org/10.1002/j.2334-5837.1997.tb02183.x.

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32

Lethrech, Mohammed, Adil Kenzi, Issam Elmagrouni, Mahmoud Nassar, and Abdelaziz Kriouile. "A MDSD Approach for Adaptable Service Oriented Systems based on Domain Specific Language Engineering." International Journal of Adaptive, Resilient and Autonomic Systems 7, no. 1 (January 2016): 1–25. http://dx.doi.org/10.4018/ijaras.2016010101.

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The simultaneous use of the new computing paradigms: Domain Specific Modeling, Context Oriented Computing and Service Oriented Computing, raises many challenges. Particularly, the challenge of engineering such systems, which consists of the definition of modeling approaches, processes, techniques and tools to facilitate their construction. The proposed MDSD approach for context-aware service oriented systems is based on Domain Specific Language Engineering. The Context-Aware, Domain Specific and Service Oriented (CADSSO) development approach is based on five models. The first one is domain specific context model; it symbolizes the services context of use. The second is domain specific services model; it takes care of services modeling. The third is service variability model; it formulates services variants. The fourth is adaptation rules model, which is the joint between service variability model and context model. The fifth is business rules model, used to model domain business. A code generator is in charge of the transformation of the five models to the final code.
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33

Sivakumar, P., B. Vinod, R. S. Sandhya Devi, and S. Poorani Nithilavallee. "Model Based Design Approach In Automotive Software and Systems." International Journal of Applied Engineering Research 10, no. 11 (June 15, 2015): 29857. http://dx.doi.org/10.37622/ijaer/10.11.2015.29857-29865.

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34

Chen, Feng, Da Tang, Hongji Yang, and Mohammed Alawairdhi. "A precondition-based approach to workflow oriented software re-engineering." Computer Science and Information Systems 11, no. 1 (2014): 1–27. http://dx.doi.org/10.2298/csis121021064c.

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Workflow management systems (WfMSs) become the basic technology for organizations to build their Information Systems. To understand the business processes already implemented in the existing software systems and then build the workflow oriented Information System is a time-consuming and error prone process. This paper proposes a unified software reengineering approach from a business process perspective. A workflow extraction method is developed to elicit the business processes from existing systems. A precondition-based workflow model is designed for this purpose, which is an activity-centred method for program analysis. The calculation of the activity?s whole condition provides powerful analysis techniques to verify the correctness of the recovered workflow model. Through the proposed approach, the workflow procedures can be recovered from the existing system and verified by the precondition analysis.
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Kirmse, Sebastian, Robert J. Cloutier, and Kuang-Ting Hsiao. "A Comprehensive Commercialization Framework for Nanocomposites Utilizing a Model-Based Systems Engineering Approach." Systems 9, no. 4 (November 23, 2021): 84. http://dx.doi.org/10.3390/systems9040084.

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Nanocomposites provide outstanding benefits and possibilities compared to traditional composites but struggle to make it into the market due to the complexity and large number of associated challenges involved in, as well as lack of standards for, nanocomposite commercialization. This article proposes a commercialization framework utilizing market analysis and systems engineering to support the commercialization process of such high technologies. The article demonstrates the importance and usefulness of utilizing Model-Based Systems Engineering throughout the commercialization process of nanocomposite technologies when combining it with the Lean LaunchPad approach and an engineering analysis. The framework was validated using a qualitative research method with a case study approach. Applying this framework to a nanocomposite, called ZT-CFRP technology, showed tremendous impacts on the commercialization process, such as reduced market and technological uncertainties, which limits the commercialization risk and increases the chance for capital funding. Furthermore, utilizing the framework helped to decrease the commercialization time and cost due to the use of a lean engineering analysis. This framework is intended to assist advanced material-based companies, material scientists, researchers and entrepreneurs in academia and the industry during the commercialization process by minimizing uncertainties and risks, while focusing resources to reduce time-to-market and development costs.
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Wang, Haoqi, Hao Li, Chengtong Tang, Xu Zhang, and Xiaoyu Wen. "Unified design approach for systems engineering by integrating model‐based systems design with axiomatic design." Systems Engineering 23, no. 1 (August 29, 2019): 49–64. http://dx.doi.org/10.1002/sys.21505.

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37

O. Gogo, Kevin. "Software Engineering Approaches for Designing Knowledge based Systems: A Survey." Circulation in Computer Science 1, no. 1 (July 24, 2016): 15–20. http://dx.doi.org/10.22632/ccs-2016-251-15.

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In our daily engagement with technology we interact with software in many aspects, rendering software engineering field a very robust area with a lot of dynamism. In this paper we have comprehensively surveyed on software engineering approaches for designing knowledge based systems. First we looked at knowledge based systems in detail, then at software engineering basics, and finally match the various software engineering approaches that have been used in the field of knowledge based systems in the current research and surveys. Some of the current approaches in knowledge approaches that we surveyed include: case-based approach, software reuse approach, Model driven software engineering approaches, ontology based approach, Open metadata approach, cloud based approach, agile approach, Traditional integration approach, Automatic software generation code approach, process based approach, and the Knowledge based system approach.
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Li, Xin, Zhengkun Mi, and Xudong Meng. "Model-based performance evaluation approach for mobile agent systems." Journal of Electronics (China) 21, no. 2 (March 2004): 145–51. http://dx.doi.org/10.1007/bf02687830.

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39

Li, Yan, Duo Su, and Qi Gong. "Automated Safety Integration Analysis of Complex System Based on Functional Model." Advanced Materials Research 655-657 (January 2013): 1783–86. http://dx.doi.org/10.4028/www.scientific.net/amr.655-657.1783.

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The development of safety critical systems becomes even harder sine the integrity and complexity of system functions and architecture grows continuously, and this kind of process involves cooperative work between safety and system engineerings during the development of products. The article presents a new approach called automated safety integrity analysis for complex system relying on functional model, and the process of safety integrity is studied by linking functional design phase using SysML(System Model Language) and Altarica Data Flow language based on risk engineering, and the given method can be analyzed automatically and iteratively during the whole life in order to unify the process between the system design and safety assessment.At last, the approach is exemplified by fuel system of aircraft to demonstrate the applicability and versatility, which explores the engineering research for the analysis technology for safety of the complex system.
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RAFE, VAHID, and ADEL T. RAHMANI. "A NOVEL APPROACH TO VERIFY GRAPH SCHEMA-BASED SOFTWARE SYSTEMS." International Journal of Software Engineering and Knowledge Engineering 19, no. 06 (September 2009): 857–70. http://dx.doi.org/10.1142/s0218194009004398.

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Graph Grammars have recently become more and more popular as a general formal modeling language. Behavioral modeling of dynamic systems and model to model transformations are a few well-known examples in which graphs have proven their usefulness in software engineering. A special type of graph transformation systems is layered graphs. Layered graphs are a suitable formalism for modeling hierarchical systems. However, most of the research so far concentrated on graph transformation systems as a modeling means, without considering the need for suitable analysis tools. In this paper we concentrate on how to analyze these models. We will describe our approach to show how one can verify the designed graph transformation systems. To verify graph transformation systems we use a novel approach: using Bogor model checker to verify graph transformation systems. The AGG-like graph transformation systems are translated to BIR — the input language of Bogor — and Bogor verifies that model against some properties defined by combining LTL and special purpose graph rules. Supporting schema-based and layered graphs characterize our approach among existing solutions for verification of graph transformation systems.
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Valiente, María-Cruz, Cristina Vicente-Chicote, and Daniel Rodríguez. "An Ontology-Based and Model-Driven Approach for Designing IT Service Management Systems." International Journal of Service Science, Management, Engineering, and Technology 2, no. 2 (April 2011): 65–81. http://dx.doi.org/10.4018/jssmet.2011040104.

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Currently, few projects applying a Model-Driven Engineering (MDE) approach start from high-level requirements models defined exclusively in terms of domain knowledge and business logic. Ontology Engineering (OE) aims to formalize and make explicit the knowledge related to a particular domain. In this vein, this paper presents a modeling approach, formalized in ontological terms, for defining high-level requirements models of software systems that provide support for the implementation of Information Technology Service Management Systems (ITSMSs). This approach allows for: (1) formalizing the knowledge associated to the ITSM processes contained in an ITSMS; (2) modeling the semantics of the activities associated to these processes in terms of workflows; (3) automatically generating the high-level requirements models of the workflow-based software systems needed to support (part of) the ITSM processes; and (4) from the latter, obtaining lower-level models (and eventually code) by means of automated model transformations. A real case study describing the use of this proposal to model an Incident Management System is also included to demonstrate the feasibility and the benefits of the proposed approach.
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42

Filimonov, Maxim, Ilias Oraifige, and Venkatesh Vijay. "A novel graph-based modelling approach for reducing complexity in model-based systems engineering environment." International Journal of System of Systems Engineering 10, no. 2 (2020): 1. http://dx.doi.org/10.1504/ijsse.2020.10029680.

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43

Filimonov, Maxim, Ilias Oraifige, and Venkatesh Vijay. "A novel graph-based modelling approach for reducing complexity in model-based systems engineering environment." International Journal of System of Systems Engineering 10, no. 2 (2020): 143. http://dx.doi.org/10.1504/ijsse.2020.109142.

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44

Salado, Alejandro, and Paul Wach. "Constructing True Model-Based Requirements in SysML." Systems 7, no. 2 (March 28, 2019): 19. http://dx.doi.org/10.3390/systems7020019.

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Some authors suggest that transitioning requirements engineering from the traditional statements in natural language with shall clauses to model-based requirements within a Model-Based Systems Engineering (MBSE) environment could improve communication, requirements traceability, and system decomposition, among others. Requirement elements in the Systems Modeling Language (SysML) fail to fulfill this objective, as they are really a textual requirement in natural language as a model element. Current efforts to directly leverage behavioral and structural models of the system lack an overarching theoretical framework with which to assess the adequacy of how those models are used to capture requirements. This paper presents an approach to construct true model-based requirements in SysML. The presented approach leverages some of SysML’s behavioral and structural models and diagrams, with specific construction rules derived from Wymore’s mathematical framework for MBSE and taxonomies of requirements and interfaces. The central proposition of the approach is that every requirement can be modeled as an input/output transformation. Examples are used to show how attributes traditionally thought of as non-functional requirements can be captured, with higher precision, as functional transformations.
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45

Doughty, D. W. "Book Review: Computer Interface Engineering for Real-Time Systems: A Model-Based Approach." International Journal of Electrical Engineering & Education 25, no. 4 (October 1988): 374–75. http://dx.doi.org/10.1177/002072098802500426.

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46

MacCalman, Alex, Gene Lesinski, and Simon Goerger. "Integrating External Simulations Within the Model-Based Systems Engineering Approach Using Statistical Metamodels." Procedia Computer Science 95 (2016): 436–41. http://dx.doi.org/10.1016/j.procs.2016.09.309.

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47

Osvaldo, S. Sousa, Denivaldo Lopes, Aristófanes C. Silva, and Zair Abdelouahab. "Developing software systems to Big Data platform based on MapReduce model: An approach based on Model Driven Engineering." Information and Software Technology 92 (December 2017): 30–48. http://dx.doi.org/10.1016/j.infsof.2017.07.006.

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48

Duncan, Kerron R., and Ralph Etienne-Cummings. "A Model-Based Systems Engineering Approach to Trade Space Exploration of Implanted Wireless Biotelemetry Communication Systems." IEEE Systems Journal 13, no. 2 (June 2019): 1669–77. http://dx.doi.org/10.1109/jsyst.2018.2874102.

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49

Husung, Stephan, Christian Weber, Atif Mahboob, and Sven Kleiner. "USING MODEL-BASED SYSTEMS ENGINEERING FOR NEED-BASED AND CONSISTENT SUPPORT OF THE DESIGN PROCESS." Proceedings of the Design Society 1 (July 27, 2021): 3369–78. http://dx.doi.org/10.1017/pds.2021.598.

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AbstractModel-Based Systems Engineering (MBSE) is an efficient approach to support product development in order to meet today's challenges. The MBSE approach includes methods and, above all, modelling approaches of the technical system with the aim of continuous use in development. The objective of this paper is to use the potential of the MBSE models and to show the added value of such models on the system level when used as a single source. With this objective, this paper presents a three-step approach to systematically identify and apply meaningful modelling approaches within MBSE, based on the needs during the development process. Furthermore, an FMEA example is included in this paper to elaborate the use of MBSE in the system failure analysis.
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50

Souza Andrade, Herlandí, and Geilson Loureiro. "A Comparative Analysis of Strategic Planning Based on a Systems Engineering Approach." Business Ethics and Leadership 4, no. 2 (2020): 86–95. http://dx.doi.org/10.21272/bel.4(2).86-95.2020.

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Strategic planning is an organizational process, the purpose of which is to conceive, formulate and manage the strategies implementation in the enterprise. The implementation of strategic planning involves the implementation of a set of actions aimed at taking the organization from a known position to a more desirable position, creating sustainable competitive advantages. This study deals with substantiating the role and importance of organizational strategic planning in the development of the organization using a systems approach. Systems engineering consists of a multidisciplinary and collaborative engineering approach, the purpose of which is to derive, develop and verify the effectiveness of decisions or the functioning of the system throughout its life cycle to satisfy the needs, expectations and desires of stakeholders. The purpose of this article is critically to analyze the Andrade method by comparing the processes and tools used in this method with those obtained as a result of traditional strategic planning. The methods were compared by developing a case study conducted in a science, technology and innovation institution operating in Brazil and annually conducting strategic planning cycles, using traditional methodologies for managing and analyzing the effectiveness of the organization and defining strategies for its development. The paper using the engineering system, carries out the comparison of the applied phases and tools with the offers in the model. The obtained results prove disadvantages of the traditional strategic planning process in comparison with the model proposed by Andrade. The application of the proposed model would allow to obtain indicators, different from the results of traditional strategic planning, in terms of forming another set of strategies and tools to manage the organization’s development. The paper concludes that the model proposed by Andrade is more complex than the traditional one. It indicates the expediency of organizations using other tools to analyze and formulate company development strategies in the context of strengthening their competitive advantages and achieving strategic goals. Keywords: Strategy, Strategic Planning, Strategic Planning Model, Strategic Management, Systems Engineering.
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