INTEGRATION OF VERIFICATION AND VALIDATION WITH SYSTEMS ENGINEERING: STAYING AHEAD OF THE POWER CURVE?

Insight ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 8-10
Author(s):  
Jonathan M. Weaver ◽  
Darrell K. Kleinke

Engineering students spend the majority of their academic careers learning tools to enable tasks related to detailed design. For example, a mechanical engineer may learn to size a heat exchanger so that an engine would not overheat, an electrical engineer may learn to specify gains in a control system to provide desired performance, and a civil engineer may learn to size columns to avoid buckling. While these analytical capabilities are essential to the execution of engineered systems, there are tools and perspectives related to systems and their design that are historically absent in an undergraduate engineering education. Through the Kern Entrepreneurship Education Network (KEEN) and the University of New Haven, the authors have developed a flipped classroom module that provides a basis in systems thinking as related to the conception and execution of complex engineered systems. The module could be useful in several areas of the curriculum, but is primarily intended to develop perspectives and skills necessary to ensure a successful capstone design experience. The module is broken into five lessons: (1) Foundational Concepts, (2) Key Systems Principles, (3) Architecture Development, (4) Multiple Views of a System, and (5) System Verification and Validation. Lesson 1 begins with the importance of the problem statement, and then proceeds to introduce form and function, function mapping, and many key definitions (system, interface, architecture, systems engineering, and complexity). Lesson 2 introduces key systems principles, including systems thinking, systems of systems, and system decomposition. Lesson 3 overviews the systems architecting process and summarizes the four most typical methods used to develop a system architecture. Lesson 4 discusses viewing a system from six different perspectives. Lesson 5 presents the systems engineering V model, requirements cascading, and verification and validation. The module includes several interactive activities and built in knowledge checkpoints. There is also a final challenge wherein the students must apply what they’ve learned about systems thinking and systems engineering to a hypothetical problem. This paper will further describe the module content and format. The paper will also make the case that the content included in the module is essential to an efficient, effective, and rewarding capstone design experience. This is achieved by summarizing common pitfalls that occur in a capstone design project and how good systems thinking can avert them. The pitfalls covered include failure to fully understand all key stakeholders’ most important needs, failure to understand desired system function in a solution-neutral way and failure to follow a robust process to map function to form, poor choice of how to decompose the system into subsystems, errors/inefficiencies in interface definition and management, and poor (if any) planning for design verification and validation.


Systems ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 39
Author(s):  
Kari Lippert ◽  
Robert Cloutier

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.


Author(s):  
Mourad Debbabi ◽  
Fawzi Hassaïne ◽  
Yosr Jarraya ◽  
Andrei Soeanu ◽  
Luay Alawneh

2021 ◽  
Vol 69 (5) ◽  
pp. 460-465
Author(s):  
J. Wang

Verification and validation represent an important procedure for model-based systems engineering design processes. One of the crucial tasks for verification and validation is to test whether the control system has reached performance limit. This is challenging since complicated theories and complex steps are often involved to achieve such an objective; meanwhile, the state of the art for testing performance limit requires iterative procedures. A simple and one-off experimental design for telling whether a control system reaches its performance limit is thus necessitated. This article introduces a remarkable test criterion for fulfilling the requirement. Both theoretical foundation and experiment design procedures are presented. Numerical examples are illustrated for the proposed method, where it is also shown that the simple method can be generalized to determining performance limit maps over both frequencies and physical parameters.


Author(s):  
Udo Kannengiesser ◽  
John S. Gero

AbstractThis paper investigates how the core technical processes of the INCOSE model of systems engineering differ from other models of designing used in the domains of mechanical engineering, software engineering and service design. The study is based on fine-grained datasets produced using mappings of the different models onto the function-behaviour-structure (FBS) ontology. By representing every model uniformly, the same statistical analyses can be carried out independently of the domain of the model. Results of correspondence analysis, cumulative occurrence analysis and Markov model analysis show that the INCOSE model differs from the other models in its increased emphasis on requirements and on behaviours derived from structure, in the uniqueness of its verification and validation phases, and in some patterns related to the temporal development and frequency distributions of FBS design issues.


2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.


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