Nov 5, 2018, 09:09 AM
INSIGHT is published in cooperation with John Wiley & Sons as a magazine for systems engineering practitioners. Read more...
INSIGHT is published in cooperation with John Wiley & Sons as a magazine for systems engineering practitioners. INSIGHT’s mission is to provide informative articles on advancing the state of the practice of systems engineering. The intent is to accelerate the dissemination of knowledge to close the gap between the state of practice and the state of the art as captured in Systems Engineering, the Journal of INCOSE, also published by Wiley.
The current mold for systems engineering has roots in engineering the systems of increased complexity in the 1930s through the 1960s. We are now transforming from document centric to model-based artifacts. The recent March 2018 INSIGHT focused on the origins, alternatives, evolutions, and challenges in model-based systems engineering (MBSE). Previous issues focused on MBSE in December 2009 (Volume 12, Issue 4) and August 2015 (Volume 18, Issue 2), and model-based conceptual design (MBCD) in December 2014 (Volume 18, Issue 4).
Your editor asserts that our legacy methods and tools, and perhaps the emerging model-based approaches, are not fit for purpose to engineer the systems now demanded of us. Systems engineering is increasingly challenged by the exponentially rising complexity of systems that have hidden interactions and are much more non-deterministic and volatile in their behaviors, with negative unintended consequences. We must underpin systems engineering with principles from both the physical and soft sciences. The focus of this October issue of INSIGHT is the challenges to the engineering of systems driven by technology advances that impact their contextual ecosystems and our social constructs. Technology advances in materials, energy, and electronics enable advances in computing, communications, and software that further advance the development of much more complicated and complex networked, cyber-physical systems at scale, that leverage artificial intelligence, deep/machine learning, and autonomy. These systems self adapt in operation, which begets the question of how to verify and validate them.
“A Framework for Understanding Systems Principles and Methods” by David Rousseau argues that that our ability to improve systems engineering’s methods depends on making the principles of systemology, of which systems engineering is a part, more diverse and more scientific. David introduces an architecture for systemology which shows how the its principles arise from interdependent processes spanning multiple disciplinary fields, and on this basis a typology is introduced, which can be used to classify systems principles and systems methods.
“Systems Engineering, Data Analytics, and Systems Thinking: Moving Ahead to New and More Complex Challenges” by Ron Kenett, Avigdor Zonnenshain, and Robert Swarz addresses the Fourth Industrial Revolution or Industry 4.0 and is based on advanced manufacturing and engineering technologies, such as massive digitization, big data analytics, advanced robotics and adaptive automation, additive and precisions manufacturing (such as 3-D printing), modeling and simulation, artificial intelligence, and the nano-engineering of materials. This revolution presents challenges and opportunities to the systems engineering discipline. For example, virtually all systems will have porous and ill-defined boundaries and requirements.
“Informing the Delineation of Input Uncertainty Space in Exploratory Modelling Using a Heuristic Approach” by Enayat Moallemi, Sondoss Elsawah, and Michael Ryan show the statistical significance of the implication of the size of an input uncertainty space on the resulted output solution space. They propose a heuristic approach which informs the delineation of input uncertainties by screening the relevant model behaviour in the solution space.
“Extending Formal Modeling for Resilient Systems Design” by Azad Madni, Michael Sievers, Ayesha Madni, Edwin Ordoukhanian, and Parisa Pouya presents a flexible contract-based approach that employs a combination of formal methods for verification and testing and flexible assertions and probabilistic modeling to handle uncertainty during mission execution. A flexible contract (FC) is a hybrid-modeling construct that facilitates system verification and testing while offering the requisite flexibility to cope with non-determinism.
“A Fresh Look at Systems Engineering – What is it, How Should it Work?” by Hillary Sillitto, James Martin, Regina Griego, Dorothy McKinney, Eileen Arnold, Patrick Godfrey, Dov Dori, Daniel Krob, and Scott Jackson offers a revised strawman definition of systems engineering to account for the challenges in the engineering of 21st century systems in contrast to 20th century systems: from nearly deterministic to increasingly non-deterministic, adaptive or evolutionary; from a command and control paradigm to a collaborative leadership paradigm; from single systems to networked systems.
“Envisioning Systems Engineering as a Transdisciplinary Venture” by Hillary Sillitto, James Martin, Regina Griego, Dorothy McKinney, Eileen Arnold, Patrick Godfrey, Dov Dori, Daniel Krob, and Scott Jackson envisions that systems engineering can be transformed into a truly transdisciplinary discipline – a foundational meta-discipline that supports and enables collaboration between all the disciplines that should be involved in conceiving, building, using, and evolving a system so that it will continue to be successful and fit for purpose as time passes.
“INCOSE Working Group Addresses System and Software Interfaces” by Sarah Sheard, Rita Creel, John Cadigan, Joseph Marvin, Leung Chin, and Michael Pafford addresses the need to improve the systems engineering-software engineering interface. Their article documents the interface issues elicited, grouped into seven categories, along with system-software interface use cases identified by working group members. The interface issues and use cases expose questions for the working group to prioritize and respond to. The paper concludes with a summary of the working group’s plan to respond to these questions and strengthen the interface between the systems engineering and software engineering disciplines.
“A Framework for Testability Analysis from System Architecture Perspective” by Mahmoud Efatmaneshnik, Michael Ryan, and Shraga Shoval presents a probabilistic model of testability that enables us to study the relationships between system architecture and testability. A Markov Chain model is used to obtain the quality of system after test as a function of its quality before test and the test quality. Choosing the appropriate testing architecture through careful modularization can greatly enhance efficiency and effectiveness of system testing. The model is based on repetitive testing that means the test will be repeated after a failed test outcome.
“Perspectives on Managing Emergent Risk due to Rising Complexity in Aerospace Systems” by Dianne DeTurris and Andrew Palmer highlights commonalities between complexity management methods, systems design models, and elements of systems thinking that can be used to predict and prepare for emergent behavior in the system. Using new points-of-view in design gives practicing engineers more information with which to view and manipulate system properties. Ultimately, the solution for managing complexity lies in multidisciplinary collaboration in order to solve problems that span multiple academic domains.
“Adaptive Cyber-Physical-Human Systems: Exploiting Cognitive Modeling and Machine Learning in the Control Loop” by Azad Madni, Michael Sievers, and Carla Conaway Madni presents key challenges in realizing adaptive cyber-physical-human (CPH) systems. Their article discusses learning and adaptation, as well as human and cyber-physical systems roles in adaptive CPH systems. It offers a functional (reference) architecture to inform and guide the development of adaptive CPH systems.
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