scholarly journals Leveraging Digital Twin Technology in Model-Based Systems Engineering

Systems ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 7 ◽  
Author(s):  
Azad Madni ◽  
Carla Madni ◽  
Scott Lucero
Keyword(s):  
Systems Engineering ◽  
Physical System ◽  
System Simulation ◽  
Virtual Prototype ◽  
Digital Representation ◽  
Digital Twin ◽  
Model Based ◽  
Digital Twins ◽  
Status Data ◽  
Model Based Systems Engineering

Digital twin, a concept introduced in 2002, is becoming increasingly relevant to systems engineering and, more specifically, to model-based system engineering (MBSE). A digital twin, like a virtual prototype, is a dynamic digital representation of a physical system. However, unlike a virtual prototype, a digital twin is a virtual instance of a physical system (twin) that is continually updated with the latter’s performance, maintenance, and health status data throughout the physical system’s life cycle. This paper presents an overall vision and rationale for incorporating digital twin technology into MBSE. The paper discusses the benefits of integrating digital twins with system simulation and Internet of Things (IoT) in support of MBSE and provides specific examples of the use and benefits of digital twin technology in different industries. It concludes with a recommendation to make digital twin technology an integral part of MBSE methodology and experimentation testbeds.

scholarly journals Digital Twin-Driven Process and Equipment FMECA Generation for Smart Manufacturing Applications

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jay Meyer ◽  
Venkat Malepati ◽  
Caleb Hudson ◽  
Somnath Deb ◽  
...  
Keyword(s):  
Systems Engineering ◽  
Failure Modes ◽  
Fault Management ◽  
Automatic Generation ◽  
Smart Manufacturing ◽  
Digital Twin ◽  
Model Based ◽  
Manufacturing Applications ◽  
Criticality Analysis ◽  
Model Based Systems Engineering

Qualtech Systems, Inc. (QSI)’s integrated tool set, consisting of TEAMS-Designer® and TEAMS-RDS® provides a comprehensive digital twin-driven and model-based systems engineering approach that can be deployed for fault management throughout the equipment life-cycle – from its design for fault management to condition-based maintenance of the deployed equipment. In this paper, we present QSI’s approach towards adapting and enhancing their existing model-based systems engineering (MBSE) approach towards a comprehensive digital twin that incorporates constructs necessary for development of a Process Failure Modes and Criticality Analysis (P-FMECA) and integrates that with an Equipment FMECA. The paper will discuss the various levels of automation towards incorporation of these model constructs and their reuse towards automation of the development of the different digital twins and subsequently the automatic generation of the combined Process and Equipment FMECA. This automated ability to develop the integrated FMECA that incorporates both Process-level Failure Modes and Equipment-level Failure Modes allows the system designer and operators to correlate and identify process failures down to their root causes at the equipment-level and thereby producing a comprehensive actionable systems-level view of the entire Smart Manufacturing facility from a fault management design and operations perspective. The paper will present the application of this novel technology for the Advanced Metal Finishing Facility (AMFF) at the Warner-Robins Air Logistics Complex (WR-ALC) in Robins Air Force Base, Georgia, as part of WR-ALC’s initiative towards model-based enterprise (MBE) and smart manufacturing.

Operationalizing digital twins through model‐based systems engineering methods

2020 ◽  
Vol 23 (6) ◽  
pp. 724-750
Author(s):  
Jason Bickford ◽  
Douglas L. Van Bossuyt ◽  
Paul Beery ◽  
Anthony Pollman
Keyword(s):  
Systems Engineering ◽  
Model Based ◽  
Digital Twins ◽  
Model Based Systems Engineering

scholarly journals Application of Model Based Systems Engineering for the Conceptual Design of a Hybrid-Electric ATR 42-500: From System Architecting to System Simulation

2020 ◽  
Author(s):  
Federico Cappuzzo ◽  
Olivier Broca ◽  
Stavros Vouros ◽  
Ioannis Roumeliotis ◽  
Calum Scullion
Keyword(s):  
Product Development ◽  
Systems Engineering ◽  
System Simulation ◽  
Integrated Systems ◽  
Turbine Engine ◽  
Model Based ◽  
Systems Model ◽  
Development Cycle ◽  
Hybrid Electric ◽  
Model Based Systems Engineering

Abstract The progress in aerospace technology over the recent years led to the development of more sophisticated and integrated systems. To cope with this complexity, the aerospace industry is seeing a progressive trend towards adopting Model-Based Systems Engineering (MBSE) in various stages of the product development cycle. The ability to capture emerging behavior, mitigation of risk and improved communication among different stakeholders are some key benefits that MBSE provides over traditional methods for complex systems and processes. This paper attempts to bridge the gap between system architecting and system simulation activities by proposing a methodology to facilitate seamless flow of information between the two development aspects. This methodology was applied to the development of a parallel hybrid-electric version of the ATR 42–500. The use case was designed for a regional mission of 400 nautical miles with the ability to meet regulation requirement of carrying enough reserves for landing at an alternate airport. An integrated systems model, consisting of gas turbine engine, electric powertrain, and flight dynamics, was developed with Simcenter Amesim to analyze the dynamics performance of the aircraft throughout the whole mission. The key metrics evaluated were fuel consumption, take-off weight and the Energy Specific Air Range (ESAR) of the aircraft. As environmental regulations are becoming more stringent, pollutant and noise emissions were considered in the study. The most promising hybrid configurations are recognized, the potential benefits are quantified highlighting the strong potential of System Architecting and System Simulation to provide valuable insights early in the development cycle, reducing the time and cost of product development.

Informationsqualität in der Produktentwicklung: Modellbasiertes Systems Engineering mit expliziter Berücksichtigung von Unsicherheit/Information Quality in Product Engineering: Model-Based Systems Engineering in Explicit Consideration of Uncertainty

Konstruktion ◽  
2020 ◽  
Vol 72 (11-12) ◽  
pp. 76-83
Author(s):  
Jens Pottebaum ◽  
Iris Gräßler
Keyword(s):  
Systems Engineering ◽  
Information Quality ◽  
Engineering Model ◽  
Model Based ◽  
Product Engineering ◽  
Explicit Consideration ◽  
Model Based Systems Engineering

Inhalt Unscharfe Anforderungen, verschiedene Lösungs-alternativen oder eingeschränkt gültige Simulationsmodelle sind Beispiele für inhärente Unsicherheit in der Produktentwicklung. Im vorliegenden Beitrag wird ein modellbasierter Ansatz vorgestellt, der das industriell etablierte Denken in Sicherheitsfaktoren um qualitative Aspekte ergänzt. Modelle der Informationsqualität helfen, die Unsicherheit von Ent- wicklungsartefakten beschreibend zu charakterisieren. Mittels semantischer Technologien wird Unsicherheit so wirklich handhabbar – nicht im Sinne einer Berechnung, sondern im Sinne einer qualitativen Interpretation. Dadurch entsteht wertvolles Wissen für die iterative Anforderungsanalyse, die Bewertung alternativer System-Architekturen oder für die Rekonfiguration von Simulationen.

scholarly journals An Approach to Complement Model-Based Vehicle Development by Implementing Future Scenarios

2021 ◽  
Vol 12 (3) ◽  
pp. 97
Author(s):  
Christian Raulf ◽  
Moritz Proff ◽  
Tobias Huth ◽  
Thomas Vietor
Keyword(s):  
Systems Engineering ◽  
Holistic Approach ◽  
Future Scenarios ◽  
Worst Case ◽  
System Architectures ◽  
Vehicle Development ◽  
Model Based ◽  
Scenario Technique ◽  
Stakeholder Needs ◽  
Model Based Systems Engineering

Today, vehicle development is already in a process of substantial transformation. Mobility trends can be derived from global megatrends and have a significant influence on the requirements of the developed vehicles. The sociological, technological, economic, ecological, and political developments can be determined by using the scenario technique. The results are recorded in the form of differently shaped scenarios; however, they are mainly document-based. In order to ensure a holistic approach in the sense of model-based systems engineering and to be able to trace the interrelationships of the fast-changing trends and requirements, it is necessary to implement future scenarios in the system model. For this purpose, a method is proposed that enables the consideration of future scenarios in model-based vehicle development. The procedure of the method is presented, and the location of the future scenarios within the system architectures is named. The method is applied and the resulting system views are derived based on the application example of an autonomous people mover. With the help of the described method, it is possible to show the effects of a change of scenario (e.g., best-case and worst-case) and the connections with the highest level of requirements: stakeholder needs.

Sign in / Sign up

Export Citation Format

Share Document