Using SysML to Elicit a Value Model in Multi-Stakeholder Value-Driven System Design

2014 ◽  
Author(s):  
Douglas Broadwell ◽  
Christiaan J. J. Paredis
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Essential Elements ◽  
Value Network ◽  
Domain Specific ◽  
Model Based ◽  
A Value ◽  
System Properties ◽  
Multi Stakeholder ◽  
Value Model

In recent years, a formal, mathematically rigorous, value-based approach to system design has been proposed within the systems engineering community. This approach stands in contrast to the traditional requirements based approach to system design because of its foundations in decision theory. One of the crucial first steps in the value-based approach is the elicitation of information about all the elements that influence a design or acquisition decisions, namely, all actors, system properties and behavior, preferences, and concerns. This elicitation step requires a formalized, model-based method for capturing these elements of the value network, the basis of the decision maker’s value function. In this paper, we examine previous work in the area of elicitation in system design and define a set of elements necessary to effectively elicit a meaningful value network. We then consider a domain-specific profile as an extension of SysML to formally capture the essential elements of a value network. To illustrate the modeling approach, the profile is applied to a case study of the design of a heads-up display system (iHUD) in order to test the depth of the profile as well as to show the value of the model-based approach in the elicitation process.

Frameworks for Model-Based Design of Enterprise Information Systems

2009 ◽  
pp. 326-356 ◽  
Author(s):  
Mara Nikolaidou ◽  
Nancy Alexopoulou
Keyword(s):  
Information Systems ◽  
System Design ◽  
Systems Engineering ◽  
System Architecture ◽  
Enterprise Architecture ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Model Based ◽  
Modern Enterprise ◽  
Design Tradeoffs

System design is an important phase of system engineering, determining system architecture to satisfy specific requirements. System design focuses on analyzing performance requirements, system modeling and prototyping, defining and optimizing system architecture, and studying system design tradeoffs and risks. Modern enterprise information systems (EIS) are distributed systems usually built on multitiered client server architectures, which can be modeled using well-known frameworks, such as Zachman enterprise architecture or open distributed processing reference model (RM-ODP). Both frameworks identify different system models, named views, corresponding to discrete stakeholder’s perspectives, specific viewpoints, and could serve as a basis for model-based system design. The main focus of this chapter is to explore the potential of model-based design for enterprise information systems (EIS). To this end, the basic requirements for model-based EIS design are identified, while three alternative approaches are discussed based on the above requirements, namely, rational unified process for systems engineering (RUP SE), UML4ODP and EIS design framework.

Automatic Integration of System-Level Design and System Optimization Based on SysML

2012 ◽  
Vol 249-250 ◽  
pp. 1154-1159
Author(s):  
Yu Sheng Liu ◽  
Wen Qiang Yuan
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Optimization Model ◽  
System Modeling ◽  
System Optimization ◽  
System Level ◽  
Design Parameters ◽  
System Level Design ◽  
Model Based ◽  
Level Design

Model based systems engineering (MBSE) is becoming a promising approach for the system-level design of complex mechatronics. And several MBSE tools are developed to conduct system modeling. However, the system design cannot be optimized in current MBSE tools. In this study, an approach is presented to conduct the task. A set of optimization stereotype is defined at first which is used to formalize the optimization model based on the system design model. Then the design parameters and their relationships applied optimization stereotypes are extracted and transferred to construct the tool-dependent optimization model. Finally, the optimization model is solved and the results are given back and then modify the corresponding system model automatically. In this paper, MagicDraw is used to model the whole system whereas Matlab optimizer is used for optimization. The combustion engine is chosen as the example to illustrate the proposed approach.

A Structured, Model-Based Systems Engineering Methodology for Operations System Design

2016 ◽  
Author(s):  
Duane L. Bindschadler ◽  
Charlene P. Valerio ◽  
Robert R. Smith ◽  
Kathryn A. Schimmels
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Structured Model ◽  
Model Based ◽  
Model Based Systems Engineering

Using Domain Specific Languages to Capture Design Synthesis Knowledge for Model-Based Systems Engineering

2009 ◽  
Author(s):  
Aleksandr A. Kerzhner ◽  
Christiaan J. J. Paredis
Keyword(s):  
Systems Engineering ◽  
Design Synthesis ◽  
System Architectures ◽  
Computer Tools ◽  
Domain Specific ◽  
Model Based ◽  
Functional Specification ◽  
Management Group ◽  
Computational Synthesis ◽  
Model Based Systems Engineering

Design synthesis is a fundamental engineering task that involves the generation of a structural specification from a desired functional specification. Although the use of computer tools is common throughout the design process, design synthesis is often a task left to the designer. Formally capturing design synthesis knowledge in models and applying computational synthesis may result in better exploration of the design space and eliminate repetitive design tasks. In this paper, a graph-based framework for capturing and combining design synthesis knowledge is presented for scenarios involving the composition of well defined components into larger systems. This approach fits in the context of Model-Based Systems Engineering where a variety of formal models are used to represent knowledge about a system. This approach uses the Systems Modeling Language developed by The Object Management Group (OMG SysML™) to define both models of possible components and possible system architectures. The framework is illustrated by combining it with an evolutionary algorithm and applying it to an example problem of hydraulic circuit synthesis.

scholarly journals Towards a Domain-Specific Approach Enabling Tool-Supported Model-Based Systems Engineering of Complex Industrial Internet-of-Things Applications

Systems ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 21
Author(s):  
Christoph Binder ◽  
Christian Neureiter ◽  
Arndt Lüder
Keyword(s):  
Internet Of Things ◽  
Systems Engineering ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Major Change ◽  
Reference Architecture ◽  
Architecture Model ◽  
Domain Specific ◽  
Model Based ◽  
Model Based Systems Engineering

Contemporary manufacturing systems are undergoing a major change promoted by emerging technologies such as Cyber-physical Systems (CPS) or the Internet of Things (IoT). This trend, nowadays widely known by the term “Industry 4.0”, leads to a new kind of automated production. However, the rising number of dynamically interconnected elements in industrial production lines results in such a system being transformed into a complex System of Systems (SoS). Due to the increasing complexity and the challenges accompanied by this change, conventional engineering methods using generic principles reach their limits when developing this type of systems. With varying approaches only trying to find a solution for small-scaled areas of this problem statement, the need for a holistic methodology becomes more and more obvious. Having recognized this issue, one of the most promising approaches has been introduced with the Reference Architecture Model Industry 4.0 (RAMI 4.0). However, in the current point of view, this domain-specific architecture framework is missing specifications to address all aspects of such a critical infrastructure. Thus, this paper introduces a comprehensive modeling approach utilizing methods applied in Model-Based Systems Engineering (MBSE) and including domain-specific particularities as well as architectural concepts with the goal to enable mutual engineering of current and future industrial systems. The resulting artifacts, a domain-specific language (DSL), an architecture definition and a development process, are thereby consolidated in a ready to use software framework, whose applicability was evaluated by a real-world case study.

scholarly journals Early Stage Model Based System Design under Uncertainties

2019 ◽  
Vol 1 (1) ◽  
pp. 3621-3630
Author(s):  
Kazuya Oizumi ◽  
Akio Ito ◽  
Kazuhiro Aoyama
Keyword(s):  
Complex System ◽  
System Design ◽  
Systems Engineering ◽  
Process Model ◽  
Early Stage ◽  
Design Team ◽  
Support Design ◽  
Model Based ◽  
Design Process Model ◽  
High Level

AbstractSystem design at the early stage of design plays an important role in design process. Model based systems engineering is seen as a prominent approach for this challenge. System design can be explored by means of system simulation. However, as the system is a complex system, system model tends to have high level of abstraction. Therefore, the models cannot depict every details of the system, which makes optimization unreasonable.Furthermore, at the early stage of design, there are many uncertainties such as success of technological developments. By properly incorporating uncertain factors in system design, the system can be tolerant. Currently system design is conducted by experienced experts. However, for more complex system, it would be difficult to continue the current practice. Therefore, a method to support design team to make decision in system design is needed.This paper proposes a computational support for the system design. Design constraints, which seems the core information that design team wants at system design, are modeled. By visualizing constraints quantitatively and intuitively, the proposed method can support design team to conduct system design and design study.

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