scholarly journals Incorporating Basic Systems Thinking and Systems Engineering Concepts in a Mechanical Engineering Sophomore Design Course

2018 ◽  
Author(s):  
Karim Muci-Kuchler ◽  
Mark Bedillion ◽  
Shaobo Huang ◽  
Cassandra Degen ◽  
Marius Ellingsen ◽  
...  
Keyword(s):  
Systems Thinking ◽  
Systems Engineering ◽  
Mechanical Engineering

Measuring the Impact of a New Mechanical Engineering Sophomore Design Course on Students’ Systems Thinking Skills

2018 ◽  
Author(s):  
Cassandra M. Degen ◽  
Karim H. Muci-Küchler ◽  
Mark D. Bedillion ◽  
Shaobo Huang ◽  
Marius Ellingsen
Keyword(s):  
Systems Thinking ◽  
Systems Engineering ◽  
Mechanical Engineering ◽  
Thinking Skills ◽  
Target Product ◽  
Concept Generation ◽  
Systems Architecture ◽  
Customer Needs ◽  
Survey Results ◽  
Product Specifications

As the complexity of cutting edge products increases with advances in technology, there is a need to include activities in the undergraduate curriculum that allow students to learn basic systems engineering concepts, that promote the development of their systems thinking skills, and that allow them to practice these skills. To this end, the aim of this work was to impact students’ systems thinking skills at an early stage of their mechanical engineering curriculum, develop assessment tools to measure sophomore-level mechanical engineering students’ system thinking skills, and observe trends in measured systems thinking skills both before and after exposure to a new sophomore design course. This paper provides an overview of the new course, gives details about an Engineering Systems Thinking Survey (ESTS) that was developed to assess systems thinking skills in specific areas, and presents the results of the ESTS from implementation of the course during two separate semesters. The specific areas that were targeted were identification of customer needs, setting target product specifications, concept generation, and systems architecture. The survey results showed that the course was successful in improving students’ self-efficacy on each of the four topics, particularly in setting target specifications and systems architecture. In addition, comparisons of pre- and post-ESTS results showed improvements in student answers on the technical questions related to identification of customer needs, setting target product specifications, and concept generation, with a slight decrease in the area of systems architecture. While the newly developed course was successful in the dissemination of fundamental systems thinking and systems engineering concepts among students, the survey results indicated the need to strengthen students’ awareness of concept implementation. Future work will explore how to improve the course activities to help students learn how to apply the concepts, particularly for the topics of setting target specifications and systems architecture.

Incorporating Basic Systems Thinking and Systems Engineering Concepts in a Sophomore-Level Product Design and Development Course

2016 ◽  
Author(s):  
Karim H. Muci-Küchler ◽  
Mark D. Bedillion ◽  
Cassandra M. Degen ◽  
Marius D. Ellingsen ◽  
Shaobo Huang
Keyword(s):  
Product Development ◽  
Systems Thinking ◽  
Systems Engineering ◽  
Mechanical Engineering ◽  
Undergraduate Curriculum ◽  
Low Complexity ◽  
Thinking Skills ◽  
Design And Development ◽  
Engineering Programs ◽  
Development Course

Although many US undergraduate mechanical engineering programs formally expose students to the basic concepts, methodologies, and tools used for the design and development of new products, the scope is usually limited to products of low complexity. There is a need to include activities in the undergraduate curriculum that allow students to learn basic systems engineering concepts, that promote the development of their systems thinking skills, and that allow them to practice these skills. This paper describes an initial effort at integrating systems engineering concepts in the curriculum focusing on a sophomore-level product development course. The paper discusses the approach that was used to identify topics related to systems thinking and systems engineering, provides the list of topics that were selected, and outlines the approach that will be used to incorporate those topics in the course. In addition, it provides the results of a pilot self-efficacy survey focusing on some of the topics selected that was delivered to junior students who had already taken a formal product development course. Although a specific course was considered, the same approach could be used in the context of the entire mechanical engineering undergraduate curriculum. Also, the results presented in the paper could be easily adapted to similar courses at other institutions.

scholarly journals Incorporating Systems Thinking and Systems Engineering Concepts in a Freshman-Level Mechanical Engineering Course

2020 ◽  
Author(s):  
Karim Muci-Kuchler ◽  
Cassandra Birrenkott ◽  
Mark Bedillion ◽  
Marsha Lovett ◽  
Clifford Whitcomb
Keyword(s):  
Systems Thinking ◽  
Systems Engineering ◽  
Mechanical Engineering

scholarly journals Integration-In-Totality: The 7th System Safety Principle Based on Systems Thinking in Aerospace Safety

Aerospace ◽  
2020 ◽  
Vol 7 (10) ◽  
pp. 149
Author(s):  
Johney Thomas ◽  
Antonio Davis ◽  
Mathews P. Samuel
Keyword(s):  
Systems Thinking ◽  
Vertical Integration ◽  
Systems Engineering ◽  
Safety Concept ◽  
Horizontal Integration ◽  
Continuum Approach ◽  
System Safety ◽  
Seven Principles ◽  
And Performance ◽  
Strategic Quality Management

Safety is of paramount concern in aerospace and aviation. Safety has evolved over the years, from the technical era to the human-factors era and organizational era, and finally to the present era of systems-thinking. Building upon three foundational concepts of systems-thinking, a new safety concept called “integration-in-totality principle” is propounded in this article as part of a “seven-principles-framework of system safety”, to act as an integrated framework to visualize and model system safety. The integration-in-totality principle concept addresses the need to have a holistic ‘vertical and horizontal integration’, which is a key tenet of systems thinking. The integration-in-totality principle is illustrated and elucidated with the help of a simple “Rubik’s cube model of integration-in-totality principle” with three orthogonal axes, the ‘axis of perspective’ of vertical integration, and the two ‘axes of perception and performance’ of horizontal integration. Safety analysis along the three axes with a ‘bidirectional synthesis’ and ‘continuum approach’ is further elaborated with relevant case studies, one among them related to the Boeing 737 MAX aircraft twin disasters. Safety is directly linked to quality, reliability and risk, through a self-reinforcing reflexive paradigm, and airworthiness assurance is the process through which safety concepts are embedded in a multidisciplinary aviation environment where the system of systems is seamlessly operating. The article explains how the system safety principle of integration-in-totality is related to reliability and airworthiness of an aerospace system with the help of the ‘V-model of systems engineering’. The article also establishes the linkage between integration-in-totality principle and strategic quality management, thus bridging the gap between two parallel fields of knowledge.

scholarly journals What is Systems Thinking? Expert Perspectives from the WPI Systems Thinking Colloquium of 2 October 2019

Systems ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 6 ◽  
Author(s):  
Matthew Amissah ◽  
Thomas Gannon ◽  
Jamie Monat
Keyword(s):  
Systems Thinking ◽  
Systems Engineering ◽  
Real World ◽  
Systems Science ◽  
Systems Dynamics ◽  
Research And Practice ◽  
Fundamental Notion ◽  
Real World Problems

Systems thinking is an approach to reasoning and treatment of real-world problems based on the fundamental notion of ‘system.’ System here refers to a purposeful assembly of components. Thus, systems thinking is aimed at understanding relationships between components and their overall impact on system outcomes (i.e., intended and unintended) and how a system similarly fits in the broader context of its environment. There are currently several distinct flavors of systems thinking, both in practice and scholarship; most notably in the disciplines of systems science, systems engineering, and systems dynamics. Each of these, while similar in purpose, has a distinct history and a rich set of methods and tools for various application contexts. The WPI Systems Thinking Colloquium held on 2 October 2019 was aimed at exploring the diversity of perspectives on systems thinking from these disciplines. The colloquium brought together world-renowned experts from both industry and academia to share insights from their research and practice. This paper offers a compilation of summaries of the presentations given.

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 Modelling COVID-19 Pandemic Dynamics Using Transparent, Interpretable, Parsimonious and Simulatable (TIPS) Machine Learning Models: A Case Study from Systems Thinking and System Identification Perspectives

2021 ◽  
Author(s):  
Hua-Liang Wei ◽  
Stephen A Billings
Keyword(s):  
Machine Learning ◽  
System Identification ◽  
Systems Thinking ◽  
Systems Engineering ◽  
Moving Average ◽  
A Priori ◽  
Learning Models ◽  
New Findings ◽  
Machine Learning Models

Since the outbreak of COVID-19, an astronomical number of publications on the pandemic dynamics appeared in the literature, of which many use the susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) models, or their variants, to simulate and study the spread of the coronavirus. SIR and SEIR are continuous-time models which are a class of initial value problems (IVPs) of ordinary differential equations (ODEs). Discrete-time models such as regression and machine learning have also been applied to analyze COVID-19 pandemic data (e.g. predicting infection cases), but most of these methods use simplified models involving a small number of input variables pre-selected based on a priori knowledge, or use very complicated models (e.g. deep learning), purely focusing on certain prediction purposes and paying little attention to the model interpretability. There have been relatively fewer studies focusing on the investigations of the inherent time-lagged or time-delayed relationships e.g. between the reproduction number (R number), infection cases, and deaths, analyzing the pandemic spread from a systems thinking and dynamic perspective. The present study, for the first time, proposes using systems engineering and system identification approach to build transparent, interpretable, parsimonious and simulatable (TIPS) dynamic machine learning models, establishing links between the R number, the infection cases and deaths caused by COVID-19. The TIPS models are developed based on the well-known NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous inputs) model, which can help better understand the COVID-19 pandemic dynamics. A case study on the UK COVID-19 data is carried out, and new findings are detailed. The proposed method and the associated new findings are useful for better understanding the spread dynamics of the COVID-19 pandemic.

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