TOWARD A THEORY OF SYSTEMS ENGINEERING

2021 ◽  
pp. 1-11
Author(s):  
George A. Hazelrigg ◽  
Donald G. Saari
Keyword(s):  
Systems Engineering ◽  
Engineering Community ◽  
Engineering Discipline ◽  
Abstract Approach ◽  
Core Set ◽  
Engineering Practices ◽  
Physical Laws ◽  
Simple Preference ◽  
Sizable Fraction ◽  
Current Systems

Abstract The derivation of a theory of systems engineering has long been complicated by the fact that there is little consensus within the systems engineering community regarding precisely what systems engineering is, what systems engineers do, and what might constitute reasonable systems engineering practices. To date, attempts at theories fail to accommodate even a sizable fraction of the current systems engineering community, and they fail to present a test of validity of systems theories, analytical methods, procedures or practices. This paper presents a more theoretical and more abstract approach to the derivation of a theory of systems engineering that has the potential to accommodate a broad segment of the systems engineering community and present a validity test. It is based on a simple preference statement: “I want the best system I can get.” From this statement, it is argued that a very rich theory can be obtained. Whereas most engineering disciplines are framed around a core set of widely accepted physical laws, to the authors' knowledge, this is the first attempt to frame an engineering discipline around a preference.

Toward a Theory of Systems Engineering

2020 ◽  
Author(s):  
George A. Hazelrigg ◽  
Donald G. Saari
Keyword(s):  
Systems Engineering ◽  
Engineering Community ◽  
Engineering Discipline ◽  
Abstract Approach ◽  
Core Set ◽  
Engineering Practices ◽  
Physical Laws ◽  
Simple Preference ◽  
Sizable Fraction ◽  
Current Systems

Abstract The derivation of a theory of systems engineering has long been complicated by the fact that there is little consensus within the systems engineering community regarding precisely what systems engineering is, what systems engineers do, and what might constitute reasonable systems engineering practices. To date, attempts at theories fail to accommodate even a sizable fraction of the current systems engineering community, and they fail to present a test of validity of systems theories, analytical methods, procedures or practices. This paper presents a more theoretical and more abstract approach to the derivation of a theory of systems engineering that has the potential to accommodate a broad segment of the systems engineering community and present a validity test. It is based on a simple preference statement: “I want the best system I can get.” From this statement, it is argued that a very rich theory can be obtained. Whereas most engineering disciplines are framed around a core set of widely accepted physical laws, to the authors’ knowledge, this is the first attempt to frame an engineering discipline around a preference.

Exploring the Cognitive Foundations of Software Engineering

2012 ◽  
pp. 232-251
Author(s):  
Yingxu Wang ◽  
Shushma Patel
Keyword(s):  
Software Engineering ◽  
Information Science ◽  
Cognitive Capacity ◽  
Cognitive Informatics ◽  
Cognitive Constraints ◽  
Engineering Discipline ◽  
Cognitive Foundations ◽  
Physical Laws ◽  
Engineering Psychology ◽  
Science Information

It is recognized that software is a unique abstract artifact that does not obey any known physical laws. For software engineering to become a matured engineering discipline like others, it must establish its own theoretical framework and laws, which are perceived to be mainly relied on cognitive informatics and denotational mathematics, supplementing to computing science, information science, and formal linguistics. This paper analyzes the basic properties of software and seeks the cognitive informatics foundations of software engineering. The nature of software is characterized by its informatics, behavioral, mathematical, and cognitive properties. The cognitive informatics foundations of software engineering are explored on the basis of the informatics laws of software and software engineering psychology. A set of fundamental cognitive constraints of software engineering, such as intangibility, complexity, indeterminacy, diversity, polymorphism, inexpressiveness, inexplicit embodiment, and unquantifiable quality measures, is identified. The conservative productivity of software is revealed based on the constraints of human cognitive capacity.

Towards a Conceptual Framework for Open Systems Developments

2014 ◽  
Vol 7 (1) ◽  
pp. 41-54 ◽  
Author(s):  
James A. Cowling ◽  
Christopher V. Morgan ◽  
Robert Cloutier
Keyword(s):  
Conceptual Framework ◽  
Open Source ◽  
Systems Engineering ◽  
Open Source Software ◽  
Open Systems ◽  
System Development ◽  
Systems Development ◽  
Software Projects ◽  
Engineering Discipline ◽  
Development Approach

The systems engineering discipline has made great strides in developing a manageable approach to system development. This is predicated on thoroughly articulating the stakeholder requirements. However, in some engineering environments, requirements are changing faster than they can be captured and realized, making this ‘traditional' form of systems engineering less tenable. An iterative system refinement approach, characterized by open systems developments, may be a more appropriate and timely response for fast-changing needs. The open systems development approach has been utilized in a number of domains including open source software, Wikipedia®, and open innovation in manufacturing. However, open systems development appears difficult to recreate successfully, and while domain tradecraft advice is often available, no engineering management methodology has emerged to improve the likelihood of success. The authors discuss the essential features of openness in these three domains and use them to propose a conceptual framework for the further exploration of the effect of governance in determining success in such open endeavors. It is the authors' hope that further research to apply this conceptual framework to open source software projects may reveal some rudimentary elements of a management methodology for environments where requirements are highly uncertain, volatile, or ‘traditional' systems engineering is otherwise sub-optimal.

THE INCOSE NATURAL SYSTEMS WORKING GROUP - HELPING THE SYSTEMS ENGINEERING COMMUNITY LOOK TO THE GENIUS OF NATURE

Insight ◽  
2016 ◽  
Vol 19 (1) ◽  
pp. 12-15
Author(s):  
Curt McNamara ◽  
George M. Studor ◽  
Lawrence D. Pohlmann
Keyword(s):  
Systems Engineering ◽  
Working Group ◽  
Natural Systems ◽  
Engineering Community

Supply Chain Engineering in China’s Retailing Industry: A Case of Meiyijia

2017 ◽  
Vol 5 (5) ◽  
pp. 395-410
Author(s):  
Xin Tian ◽  
Chunlin Luo ◽  
Shouyang Wang ◽  
Yuzhang Ding
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Systems Engineering ◽  
Supply Chain System ◽  
Service Platform ◽  
Chain Management ◽  
Chain System ◽  
The Core ◽  
Management Technology ◽  
Engineering Practices

Abstract This paper addresses the supply chain engineering and its application in China’s retailing industry. Based on the approaches of systems engineering, we propose the concept of supply chain engineering, which applies the idea of supply chain management to the engineering practices through the advanced information and management technology, to integrate the supply chain system and optimize its operations. We then illustrate the application of the supply chain engineering in China’s retailing industry. In such practices, we developed the virtual retailing enterprise mode and the FROM-SCM system, and designed the sales assistant etc. Such theory and practices are successfully applied in Meiyijia, which has transformed Meiyijia from a traditional retailer to a modern service enterprise, and the profits are resulted from the service fees rather than the traditional surplus between buying and selling prices. Now Meiyijia has built an ecosystem with the retailer in the core, the headquarter as the service platform. The success of Meiyijia in recent years shows the effectiveness of the supply chain engineering.

7.2.3 On enabling a model-based systems engineering discipline

2008 ◽  
Vol 18 (1) ◽  
pp. 827-845 ◽  
Author(s):  
Peter Denno ◽  
Thomas Thurman ◽  
John Mettenburg ◽  
Dwayne Hardy
Keyword(s):  
Systems Engineering ◽  
Model Based ◽  
Engineering Discipline ◽  
Model Based Systems Engineering

scholarly journals A Systems Approach to Establishing an Advanced Manufacturing Innovation Institute

Systems ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 41
Author(s):  
Gregory Harris ◽  
Lauren Caudle
Keyword(s):  
Systems Thinking ◽  
Systems Engineering ◽  
Systems Approach ◽  
Interdisciplinary Approach ◽  
Advanced Manufacturing ◽  
Physical Systems ◽  
National Network ◽  
Engineering Discipline ◽  
Manufacturing Innovation ◽  
Engineering Effort

Systems engineering is a methodology where an interdisciplinary approach is applied, using systems thinking, to the development of a system of interest. The systems engineering discipline has emerged as an effective way to guide the engineering of complex systems, but has been applied most readily in the realm of cyber physical systems. In some circles of the Federal Government, the mention of systems engineering processes immediately leads people to think of a long, inefficient effort due to an often applied bureaucratic approach, where the focus is on documentation rather than the development of the system of interest, which comes from a view that the product of the systems engineering effort is the document, not the system itself. In this paper, the authors describe the application of systems thinking and the systems engineering process to the design and creation of an Advanced Manufacturing Innovation Institute (MII, part of the National Network for Manufacturing Innovation) established under Department of Defense (DoD) authority for the Office of the President, that was swift, efficient, and implemented without formality.

scholarly journals A Generic Software Architecture for Prognostics (GSAP)

2020 ◽  
Vol 8 (2) ◽  
Author(s):  
Christopher Teubert ◽  
Matthew J. Daigle ◽  
Shankar Sankararaman ◽  
Kai Goebel ◽  
Jason Watkins
Keyword(s):  
Software Architecture ◽  
Systems Engineering ◽  
Object Oriented ◽  
Software Framework ◽  
Software Frameworks ◽  
Engineering Discipline ◽  
Adoption And Implementation ◽  
Cross Platform ◽  
Design And Testing

Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a large hurdle in developing the models, algorithms, architecture, and integration pieces. Similarly, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use.

Towards Knowledge-Based Spatial Planning

2019 ◽  
pp. 1-15
Author(s):  
Robert Laurini
Keyword(s):  
Big Data ◽  
Spatial Planning ◽  
Knowledge Engineering ◽  
Big Data Analytics ◽  
Human Knowledge ◽  
Collective Knowledge ◽  
Knowledge Based ◽  
Engineering Practices ◽  
Physical Laws

For millennia, spatial planning has been based on human knowledge about the context and its environment together with some objectives of development. Now, with artificial intelligence and especially knowledge engineering, practices of spatial planning can be renovated. Presently, novel practices can be designed. In addition to human collective knowledge, some new chunks of knowledge can be introduced, coming from physical laws, administrative regulations, standards, data mining, and best practices. By big data analytics, some regularities and patterns can be discovered, which again will lead to new actions towards cities: in other words, there is a virtuous circle linking smart territories and big data that can be the basis for novel spatial planning. The role of this chapter will be to analyze those new chunks of knowledge and to explain how human knowledge, possibly coming from different stakeholders, can be harmonized with machine-processable knowledge as to be the basis for territorial intelligence.

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