Knowledge Systems Engineering: A Complex System View

2016 ◽  
pp. 107-149
Author(s):  
Zhongtuo Wang ◽  
Jiangning Wu
Keyword(s):  
Complex System ◽  
Systems Engineering ◽  
Knowledge Systems ◽  
System View

scholarly journals Assessing Cyber-Worthiness of Complex System Capabilities using MBSE: A new rigorous engineering methodology

2021 ◽  
Author(s):  
Stuart Fowler ◽  
Keith Joiner ◽  
Elena Sitnikova
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Systems Engineering ◽  
Cyber Attacks ◽  
Simulation Methods ◽  
Assessment Methodology ◽  
Cyber Attack ◽  
Cyber Threats ◽  
Attack Surface ◽  
Model Based Systems Engineering

<div>Cyber-worthiness as it is termed in Australian Defence, or cyber-maturity more broadly, is a necessary feature of modern complex systems which are required to operate in a hostile cyber environment. To evaluate the cyber-worthiness of complex systems, an assessment methodology is required to examine a complex system’s or system-of-system’s vulnerability to and risk of cyber-attacks that can compromise such systems. This assessment methodology should address the cyber-attack surface and threat kill chains, including supply chains and supporting infrastructure. A cyber-worthiness capability assessment methodology has been developed based on model-based systems engineering concepts to analyse the cyber-worthiness of complex systems and present a risk assessment of various cyber threats to the complex system. This methodology incorporates modelling and simulation methods that provide organisations greater visibility and consistency across diverse systems, especially to drive cybersecurity controls, investment and operational decisions involving aggregated systems. In this paper, the developed methodology will be presented in detail and hypothesised outcomes will be discussed.</div>

Industry 4.0 From the Systems Engineering Perspective

2020 ◽  
pp. 575-599
Author(s):  
Vladimír Bureš
Keyword(s):  
Complex System ◽  
Physical Activity ◽  
Complex Systems ◽  
Frequency Analysis ◽  
Systems Engineering ◽  
Industry 4.0 ◽  
Control Level ◽  
Design Development ◽  
Starting Point ◽  
And Control

Systems engineering focuses on design, development, and implementation of complex systems. Not only does the Industry 4.0 concept consist of various technical components that need to be properly set and interconnected, but it is also tied to various managerial aspects. Thus, systems engineering approach can be used for its successful deployment. Overemphasis of technological aspects of Industry 4.0 represents the main starting point of this chapter. Then, collocation analysis, word clusters identification, selection and exemplification of selected domain in the business management realm, and frequency analysis are used in order to develop a holistic framework of Industry 4.0. This framework comprises six levels – physical, activity, outcome, content, triggers, and context. Moreover, the information and control level is integrated. The new holistic framework helps to consider Industry 4.0 from the complex systems engineering perspective – design and deployment of a complex system with required parameters and functionality.

The Sociological Study of Science and Religion in Context

2019 ◽  
pp. 3-24
Author(s):  
Fern Elsdon-Baker ◽  
Will Mason-Wilkes
Keyword(s):  
Complex System ◽  
Social Science ◽  
Scientific Research ◽  
Science And Religion ◽  
Social Contexts ◽  
Knowledge Systems ◽  
Sociological Study ◽  
Popular Discourse ◽  
Fundamental Difficulty ◽  
Insight Into

In this chapter,Elsdon-Baker and Mason-Wilkes review recent debates on science and belief, problematising the philosophicaltenor of current academic and popular discourse and highlighting the limitations of current research. The chapter begins by highlighting the fundamental difficulty with multi- or cross- disciplinary research into science, belief and society – which in part relates to the lack of social science researchers who can adequately provide open minded insight into both ‘science’ and ‘religion’. The authors contend that the nuance and complexity of how these two knowledge systems interact in diverse social contexts can be lost due to implicit disciplinary biases. Too often in academic discourse, they argue, scholars lose sight of the multi-layered and relational ways in which members of a variety of ‘publics’ relate to ‘science’. Rather than assuming that ‘publics’ negative responses to scientific research simply transect various epistemological, ontological, ethical narratives, the authors maintain that we need to situate people’s positions within a complex system of geopolitical, cultural and social contexts that lead to individuals’ positions on scientific issues acting as an identity marker across a spectrum of religious, spiritual, non-religious and atheistic publics.

The Basic Problems about Fully-Mechanized Top-Coal Caving System

2012 ◽  
Vol 256-259 ◽  
pp. 518-521
Author(s):  
Xin Jia Leng ◽  
Er Qiang Li ◽  
Jia Wei Liu ◽  
Wen Guo Li
Keyword(s):  
Complex System ◽  
Structure Function ◽  
Systems Engineering ◽  
Large Scale ◽  
Basic Theory ◽  
Equipment Selection ◽  
Complex Problems ◽  
Boundary Parameter ◽  
The Stability ◽  
Outer Environment

The fully mechanized top-coal caving System is a large scale complex system. The conception of system and its basic problems, such as structure, function, inner-outer environment, boundary, parameter and so on, are defined in this paper. Through the thorough research, the basic theory of fully mechanized top-coal caving will be consummated, the stability and reliability of the system will be worked over by systems engineering, and the complex problems of equipment-selection and surround rock-displace which involved of many factors will be resolved.

Development of the Reliability-Risk Modeling Framework for Ranking Conceptual Designs

2016 ◽  
Author(s):  
Anthony D’Angelo
Keyword(s):  
Complex System ◽  
Supply Chain ◽  
Systems Engineering ◽  
Hybrid Approach ◽  
Risk Modeling ◽  
Modeling Framework ◽  
Reliability Design ◽  
Conceptual Designs ◽  
Design Integration ◽  
Federal Information Processing Standard

A critical component of Systems Engineering (SE) is to conduct a thorough Risk Analysis. This paper introduces a novel hybrid approach to develop a Reliability-Risk modeling technique that will be able to rank Conceptual Designs as a function of Reliability. A traditional SE approach is used to identify all success modes associated with the development of a complex system. Also, the Advanced Development, Design, Integration & Evaluation, Production, and Operation & Support that make up the major phases of a Systems Engineering model will define the Holographic Reliability Design Space. Requirements of the System under development are captured through the implementation of the Integration Definition Function Modeling (IDEF0) technique. The IDEF0 method is defined in Federal Information Processing Standard Publications (FIPS PUBS 183) [1]. Using the developed IDEF0 model allows the function of each component to be identified, the proper reliability model to be chosen, and completion of a reliability-based analysis. Upon completion of calculating the reliability, for each criterion, the use of a Multi-Criteria Decision System (MCDS) is required to rank the conceptual designs in terms of reliability. A MCDS was developed to analyze the conflicting objects inherent during the design and integration of any complex system. The model developed herein was used to analyze 5 Packaging Conceptual designs being considered to become part of the military Supply Chain. After completion of the analysis, the new and innovative Packaging Designs were ranked based on reliabilities associated with design, test, integration, manufacturing, and incorporation into the existing Supply Chain. The results of the rankings were then presented to the ultimate decision makers for final approval.

A novel complex-system-view-based method for system effectiveness analysis: Monotonic indexes space

2006 ◽  
Vol 49 (1) ◽  
pp. 90-102 ◽  
Author(s):  
Jianwen Hu ◽  
Weiming Zhang ◽  
Zhong Liu ◽  
Xiaofeng Hu ◽  
Guangya Si
Keyword(s):  
Complex System ◽  
System View ◽  
Effectiveness Analysis ◽  
Novel Complex ◽  
System Effectiveness

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.

Sign in / Sign up

Export Citation Format

Share Document