Semantic Modeling Approach Supporting Process Modeling and Analysis in Aircraft Development
Source abstract
Abstract
With the increasing complexity of aircraft development programs, the development processes of aircraft and their subsystems are continuously becoming complicated, leading to the growing risks of development cost across the entire life cycle. In this study, we proposed a model-based systems engineering approach to support process modeling of aircraft development using a multi-architecture modeling language KARMA. Simultaneously, property verification and hybrid automata simulation were used to implement the static cost analysis of each work task and dynamic cost analysis of the entire development process. Finally, a development process model of aircraft avionics system was created using a case study, in which cost analysis is implemented by the KARMA language. From the result, we found that the KARMA language enables the integration of the process modeling with static and dynamic analyses of the development process in a multi-architecture modeling tool MetaGraph 2.0.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Systems Engineering Methodologies and Applications · Model-Driven Software Engineering Techniques · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
EPFL SCI-STI-DK, Station 9, CH 1015 Lausanne, Switzerland
COMAC BATRI, Beijing 102211, China
School of Economics, Fudan University, Shanghai 200433, China
Funding
CN National Key Research and Development Plan · CN pre-study common technology
References (37)
Show source-provided references
1. BPMN+Ito support decision making in innovation management for automated production systems including technological, multi team and organizational aspects10.1016/j.ifacol.2020.12.2825 ↗
2. A Construction Enterprise’s Readiness Level in Implementing E-Procurement: A System Engineering Assessment Model10.1016/j.sepro.2011.10.016 ↗
3. General Modeling Language Supporting Model Transformations of MBSE (Part 2)10.1002/j.2334-5837.2020.00797.x ↗
4. ISO/IEC/IEEE (2008). Systems and Software Engineering System Life Cycle Processes, ISO. Technical Report.
5. Modelling and managing project complexity10.1016/S0263-7863(01)00068-0 ↗
6. Zheng, X., Lu, J., and Kiritsis, D. (2021). The emergence of cognitive digital twin: Vision, challenges and opportunities. Int. J. Prod. Res., 1–23.
7. Incose, A. (2014). World in Motion: Systems Engineering Vision 2025, International Council on Systems Engineering.
8. Zou, M., Vogel-Heuser, B., Sollfrank, M., and Fischer, J. (2020, January 14–17). A cross-disciplinary model-based systems engineering workflow of automated production systems leveraging socio-technical aspects. Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, Singapore.10.1109/IEEM45057.2020.9309803 ↗
9. Business process improvement using Object-Process Methodology10.1002/sys.21499 ↗
10. Structuring activity diagrams10.3182/20120523-3-RO-2023.00153 ↗
11. Bringing model-based systems engineering capabilities to project management: An application to prince2
12. Study on the feasibility of modelling notations for integrated product-service systems engineering10.1016/j.procir.2019.02.133 ↗
13. Hua, Z., Zhao, J.L., and Storey, V.C. (2010, January 10–12). Exploring a domain ontology based approach to business process design. Proceedings of the ICIS 2010—Thirty First International Conference on Information Systems, St. Louis, MO, USA.
14. Business processes modelling assistance by recommender functionalities: A first evaluation from potential users
15. Applying process mining and semantic reasoning for process model customisation in healthcare10.1080/17517575.2019.1632382 ↗
16. Semantic Integration for Cross-Organizational Manufacturing Business Process10.2174/1874155X01105010131 ↗
17. A Multi-criteria Evaluation Approach for Selecting a Sensitive Business Process Modeling Language for Knowledge Management10.1007/s13740-019-00103-5 ↗
18. Bandara, M., Rabhi, F.A., Meymandpour, R., and Demirors, O. (2019). A Digital Interaction Framework for Managing Knowledge Intensive Business Processes, Springer.10.1007/978-3-030-32242-7_9 ↗
19. Process ontology development using natural language processing: A multiple case study10.1108/BPMJ-05-2018-0144 ↗
20. Semantic technologies for aligning heterogeneous business process models10.1108/BPMJ-07-2013-0085 ↗
21. A survey of model-based system engineering methods to analyse complex supply chains: A case study in semiconductor supply chain10.1016/j.ifacol.2019.11.370 ↗
22. Ayari, S., Hlaoui, Y.B., and Ben Ayed, L.J. (2019, January 26–28). A refinement based verification approach of BPMN models using NuSMV. Proceedings of the ICSOFT 2018—13th International Conference on Software Technologies, Porto, Portugal.10.5220/0006914105630574 ↗
23. A formal approach to modeling and verification of business process collaborations10.1016/j.scico.2018.05.008 ↗
24. BPMN-based business process model feasibility analysis: A petri net approach10.1080/00207540701199677 ↗
25. Shiraki, R., and Shinkawa, Y. (2017, January 9–13). Verification of Business Processes with Time Constraints. Proceedings of the 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017, Hamamatsu, Japan.10.1109/IIAI-AAI.2017.152 ↗
26. El hichami, O., Naoum, M., El Mohajir, B.E., and Lazaar, M. (2019). Visual language for specifying verification properties: A tool for optimisation and verification of business process properties. ACM International Conference Proceeding Series, Association for Computing Machinery.10.1145/3372938.3373013 ↗
27. Wang, H., Wang, G., Lu, J., and Ma, C. (2019). Ontology supporting model-based systems engineering based on a GOPPRR approach. World Conference on Information Systems and Technologies, Springer.10.1007/978-3-030-16181-1_40 ↗
28. Towards a comparative analysis of meta-metamodels
29. De Moura, L., and Bjørner, N. (2009). Satisfiability modulo theories: An appetizer. Brazilian Symposium on Formal Methods, Springer.10.1007/978-3-642-10452-7_3 ↗
30. General Modeling Language to Support Model-based Systems Engineering Formalisms (Part 1)10.1002/j.2334-5837.2020.00725.x ↗
31. Ding, J., Reniers, M., Lu, J., Wang, G., Feng, L., and Kiritsis, D. (2021, January 18). Integration of modeling and verification for system model based on KARMA language. Proceedings of the 18th ACM SIGPLAN International Workshop on Domain-Specific Modeling, Chicago, IL, USA.10.1145/3486603.3486775 ↗
32. Languages and tools for hybrid systems design
33. Choi, B.K., and Kang, D. (2013). Modeling and Simulation of Discrete Event Systems, John Wiley & Sons.10.1002/9781118732793 ↗
34. Raskin, J.F. (2005). An introduction to hybrid automata. Handbook of Networked and Embedded Control Systems, Springer.10.1007/0-8176-4404-0_21 ↗
35. Hendriks, D. (2015). Compositional Interchange Format (CIF) 3.0.0 Metamodel Reference Documentation, Eindhoven University of Technology.
36. An image encryption scheme based on hybridizing digital chaos and finite state machine10.1016/j.sigpro.2019.06.013 ↗
37. Vodenčarević, A., Büning, H.K., Niggemann, O., and Maier, A. (2011, January 27–29). Using behavior models for anomaly detection in hybrid systems. Proceedings of the 2011 XXIII International Symposium on Information, Communication and Automation Technologies, Sarajevo, Bosnia.10.1109/ICAT.2011.6102093 ↗