Cyberspace is a new frontier, not just for hackers, but for engineers. It is a digital ecosystem, the next generation of Internet and network applications, promising a whole new world of distributed and open systems that can interact, self-organize, evolve, and adapt. These ecosystems transcend traditional collaborative environments, such as client-server, peer-to-peer, or hybrid models (e.g., web services), to become a self-organized, evolving, interactive environment. Understanding cyberspace as a system is critical if we are to properly design systems to exist within it. Considering it to be a digital ecosystem, where systems can adapt and evolve, will enable systems engineering to become more effective in the future of networks and the Internet. While most systems engineers have only anecdotal experience with large segments of this ecosystem, in today’s world all of them must come to understand it. Engineering any system, or portion of a system, begins with an understanding of the system. This paper presents two interrelated yet distinct foundational models of the ecosystem of cyberspace: a Systemigram to narrate the cyclical nature of cyber warfare, and a modified predator–prey model, as a mathematical model. Systems engineers can utilize these models to design digital “species” that function and adapt within this ecosystem.

Due to the fourth industrial revolution, manufacturing companies are looking to implement digital twins in their factories to be more competitive. However, the implementation of digital twins in manufacturing systems is a complex task. Factories need a framework that can guide them in the development of digital twins. Hence, this article proposes a small-scale digital twin implementation framework for manufacturing systems. To build this framework, the authors gathered several concepts from the literature and designed a digital twin subsystem model using a model-based systems engineering (MBSE) approach and the systems engineering “Vee” model. The systems modelling defines the digital twin components, functionalities, and structure. The authors distribute most of these concepts throughout the framework configuration and some concepts next to this general configuration. This configuration presents three spaces: physical, virtual, and information. The physical space presents a physical layer and a perception layer. The information space has a single layer called middleware. Finally, the virtual space presents two layers: application and model. In addition to these layers, this framework includes other concepts such as digital thread, data, ontology, and enabling technologies. This framework could help researchers and practitioners to learn more about digital twins and apply it to different domains.

While innovation from the systems engineer is desirable at every step in all phases of systems engineering, there must be a methodology to evaluate alternatives. A formal methodology, complete with verification and validation of the results, was developed in 1946 by Soviet engineer Genrikh Saulovich Altshuller and is known as "The theory of inventor's problem solving", or TRIZ. This approach improves the way a systems engineer's thinking progresses about a problem's solution from "what is" towards "what will be" in the innovative development of a solution. The original distinguishing features of systems used in TRIZ were derived from innovations addressing physical, mechanical system, and few of them apply to digital systems. This paper presents additional characteristics that should be considered in the Reduction phase when applying TRIZ to innovation in digital systems engineering and a redefinition of the principles. With the additions of these distinguishing features for digital systems, TRIZ will become an invaluable tool for the digital systems engineer. Systems 2019, 7, 39 2 of 23with the "what is" of the problem space and move towards the "what will be" of the solution space [5]. Application of the TRIZ methodology provides the bridge between these two; it is the problem space which is characterized and resolved. TRIZ has the reputation as the only systematic problem solving and innovation tool-kit available [6].The TRIZ tool-kit is comprised of several tools. Each is most effective when applied against a particular type of problem [6] but they can all be used in conjunction with each other. The tools that comprise this methodology include inventive principles, evolution laws, smart little people, ideality, substance-field analysis, flow analysis, feature transfer, standard solutions, separation principles, multiscreen (9-windows), trimming, and contradictions. This work focuses on the tool that used most often: contradictions. This process is very powerful for breaking out of existing design paradigms and entering into new and exciting ones [7].TRIZ can be considered as a set of all methods necessary for solving an inventive problem from the beginning to the end, and many approaches have been developed combining TRIZ with other methods: Design for Six Sigma (DFSS) [7,8]; the philosophies of Robust Design [9] and Quality Function Deployment [10,11]; Suh's Axiomatic Design [12]; Design Structure Matrices [13]; and Synectics [14]. Recently, a study was made of over 200 case studies where TRIZ had been used throughout industry [15]. TRIZ has become a powerful tool in the industrial world, helping companies innovate solutions their customers have not yet specified. At Samsung, for example, "TRIZ is now an obligatory skill set if you want to advance within Samsung" [16].The generic solution triggers resulting from TRIZ help structure problems and suggest directions for specific solutions. It is important to note that there exists a considerable gap between the generic solution triggers which have been develope...

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