Ideation Variety in Mechanical Design: Examining the Effects of Cognitive Style and Design Heuristics

2015 ◽  
Author(s):  
Kathryn Jablokow ◽  
Wesley Teerlink ◽  
Seda Yilmaz ◽  
Shanna Daly ◽  
Eli Silk ◽  
...  
Keyword(s):  
Cognitive Style ◽  
Student Perceptions ◽  
Engineering Students ◽  
Mechanical Design ◽  
Solution Space ◽  
Cognitive Intervention ◽  
Design Solution ◽  
Design Heuristics ◽  
Self Assessments ◽  
Variety Performance

This paper examines ideation variety as a measure of the extent to which a design solution space has been explored. We investigated one cognitive factor (cognitive style) and one cognitive intervention (Design Heuristics cards) and their relationships with students’ ideation variety, both actual and perceived. Cognitive style was measured using the Kirton Adaption-Innovation inventory (KAI), while variety scores were computed using the metrics of Nelson et al. [18] and Shah et al. [20]; an adapted form of these metrics was also explored. A group of 132 sophomore mechanical engineering students generated ideas for two design problems (one with and one without Design Heuristics cards). They sketched and described their conceptual solutions in words and assessed the variety of their solutions after ideation. Linear statistical techniques were applied to explore the relationships among the variety scores, students’ self-assessments of variety, cognitive style, quantity of ideas, and the presence of the Design Heuristics intervention. Our results show statistically significant correlations between students’ perceived variety and their variety performance, and between cognitive style and both variety performance and student perceptions.

Doing BiE: Lessons Learned From Teaching Bio-Inspired Engineering

2011 ◽  
Author(s):  
Christopher H. Jenkins
Keyword(s):  
Engineering Students ◽  
Da Vinci ◽  
Solution Space ◽  
Engineering Problem ◽  
Lessons Learned ◽  
Design Solution ◽  
State University ◽  
Direct Experience ◽  
Montana State University ◽  
The One

Examples of bio-inspired engineering (BiE) abound: from Da Vinci to Velcro to robotics. Showing students the excitement and utility of BiE is easy — teaching them how to “do” BiE is much more difficult. In teaching ME 455 Bio-Inspired Engineering at Montana State University. A fundamental challenge is to teach engineers BiE without the need for them to be biologists. The nature of design itself is another challenge. The value of BiE is in expanding the engineering design solution space. Today, the usual forward approach and the one most typical for design — an engineering problem in search of a biological solution paradigm — is essentially unavailable. In this paper, we provide rationale for some of the challenges in teaching BiE to engineering students. We then share lessons learned in addressing these challenges from direct experience in the classroom.

A Performance Study of Real Coded Genetic Algorithm on Gear Design Optimization

2012 ◽  
Vol 622-623 ◽  
pp. 64-68 ◽  
Author(s):  
S. Padmanabhan ◽  
M. Chandrasekaran ◽  
P. Asokan ◽  
V. Srinivasa Raman
Keyword(s):  
Genetic Algorithm ◽  
Power Efficiency ◽  
Mechanical Design ◽  
Design Solution ◽  
Functional Requirements ◽  
Performance Study ◽  
Gear Design ◽  
Adverse Result ◽  
Real Coded Genetic Algorithm ◽  
Comparative Results

he major problem that deals with practical engineers is the mechanical design and creativeness. Mechanical design can be defined as the choice of materials and geometry, which satisfies, specified functional requirements of that design. A good design has to minimize the most significant adverse result and to maximize the most significant desirable result. An evolutionary algorithm offers efficient ways of creating and comparing a new design solution in order to complete an optimal design. In this paper a type of Genetic Algorithm, Real Coded Genetic Algorithm (RCGA) is used to optimize the design of helical gear pair and a combined objective function with maximizes the Power, Efficiency and minimizes the overall Weight, Centre distance. The performance of the proposed algorithms is validated through LINGO Software and the comparative results are analyzed.

A Generalized Performance Sensitivity Synthesis Methodology for Four-Bar Mechanisms

1992 ◽  
Author(s):  
Ming-Yih Lee ◽  
Arthur G. Erdman ◽  
Salaheddine Faik
Keyword(s):  
Solution Space ◽  
Design Solution ◽  
Link Length ◽  
Performance Sensitivity ◽  
Closed Chain ◽  
Synthesis Methodology ◽  
Position Synthesis ◽  
The Relationship ◽  
Accuracy Performance ◽  
Sensitivity Maps

Abstract A generalized accuracy performance synthesis methodology for planar closed chain mechanisms is proposed. The relationship between the sensitivity to variations of link lengths and the location of the moving pivots of four-link mechanisms is investigated for the particular objective of three and four position synthesis. In the three design positions case, sensitivity maps with isosensitivity curves plotted in the design solution space allow the designer to synthesize a planar mechanism with desired sensitivity value or to optimize sensitivity from a set of acceptable design solutions. In the case of four design positions, segments of the Burmester design curves that exhibit specified sensitivity to link length tolerance are identified. A performance sensitivity criterion is used as a convenient and a useful way of discriminating between many possible solutions to a given synthesis problem.

scholarly journals A Smart Wing Rib Structure Suitable for Design for Additive Manufacturing (DfAM) Process

2021 ◽  
pp. 1-21
Author(s):  
Ramona Dogea ◽  
◽  
Xiu T Yan ◽  
Richard Millar ◽  
◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Performance Monitoring ◽  
Equivalent Stress ◽  
Solution Space ◽  
Design Solution ◽  
Smart Devices ◽  
Design For Additive Manufacturing ◽  
Wing Structures ◽  
Rib Structure ◽  
Stress And Deformation

Additive manufacturing has been adopted widely across various industries for producing parts mainly due to their ability to create complex geometries, eliminate material wastage and enable faster production rate, among others. Additive manufacturing has also increased design solution space by enabling exploration of mechatronic solutions for mechanical structures. This includes the integration of smart devices into wing structures to achieve a datadriven predictive maintenance-based system. For this, there is still the need to continuously explore various ways of integrating sensory capability into a mechanical structure during the manufacturing processes to ensure improvement and reliability of aircraft components. The scope of this paper was to analyse different wing rib geometries and the influence of embedding sensory capability via design for additive manufacturing process. In this work, three wing rib geometries with cut-outs and for sensory placement were designed and analysed to estimate their equivalent stress and deformation when such sensory locations are introduced. The results confirm the idea that it is feasible to introduce holding cavities for structural performance monitoring sensors without compromising the structural design requirements. The results also show that deformation and stress are highly dependent on the rib thickness and the insertion of sensory locations

scholarly journals VIS-HAPT: A Methodology Proposal to Develop Visuo-Haptic Environments in Education 4.0

2021 ◽  
Vol 13 (10) ◽  
pp. 255
Author(s):  
Julieta Noguez ◽  
Luis Neri ◽  
Víctor Robledo-Rella ◽  
Rosa María Guadalupe García-Castelán ◽  
Andres Gonzalez-Nucamendi ◽  
...  
Keyword(s):  
Student Performance ◽  
Student Perceptions ◽  
Digital Literacy ◽  
Engineering Students ◽  
Meaningful Learning ◽  
Physics Concepts ◽  
Haptic Technology ◽  
Sense Of Touch ◽  
Haptic Environments

Education 4.0 demands a flexible combination of digital literacy, critical thinking, and problem-solving in educational settings linked to real-world scenarios. Haptic technology incorporates the sense of touch into a visual simulator to enrich the user’s sensory experience, thus supporting a meaningful learning process. After developing several visuo-haptic simulators, our team identified serious difficulties and important challenges to achieve successful learning environments within the framework of Education 4.0. This paper presents the VIS-HAPT methodology for developing realistic visuo-haptic scenarios to promote the learning of science and physics concepts for engineering students. This methodology consists of four stages that integrate different aspects and processes leading to meaningful learning experiences for students. The different processes that must be carried out through the different stages, the difficulties to overcome and recommendations on how to face them are all described herein. The results are encouraging since a significant decrease (of approximately 40%) in the development and implementation times was obtained as compared with previous efforts. The quality of the visuo-haptic environments was also enhanced. Student perceptions of the benefits of using visuo-haptic simulators to enhance their understanding of physics concepts also improved after using the proposed methodology. The incorporation of haptic technologies in higher education settings will certainly foster better student performance in subsequent real environments related to Industry 4.0

A Comparison of Variety Metrics in Engineering Design

2017 ◽  
Author(s):  
Daniel Henderson ◽  
Kevin Helm ◽  
Kathryn Jablokow ◽  
Seda McKilligan ◽  
Shanna Daly ◽  
...  
Keyword(s):  
Engineering Design ◽  
Design Problem ◽  
Mechanical Engineering ◽  
Engineering Students ◽  
Solution Space ◽  
New Variety ◽  
Early Stages ◽  
Correlation Analyses ◽  
Design Ideas

This paper focuses on comparing and contrasting methods for assessing the variety of a group of design ideas. Variety is an important attribute of design ideas, because it indicates the extent to which the solution space has been explored. There is a greater likelihood of successfully solving a design problem when a more diverse set of ideas is generated in the early stages of design. While there are three existing metrics for variety, it has not been established how well they correlate with each other, so it is unknown whether they provide similar assessments of variety. This uncertainty inspired our investigation of the three existing metrics and, eventually, the development of a new variety metric — all of which we compared statistically and qualitatively. In particular, 104 design ideas collected from 29 sophomore mechanical engineering students were analyzed using the existing and new variety metrics. We conducted correlation analyses to determine if the four metrics were related and to what degree. We also considered the qualitative differences among these metrics, along with where they might be used most effectively. We found varying levels of statistically significant correlations among the four metrics, indicating that they are dependent. Even so, each metric offers a unique perspective on variety and may be useful in different situations.

A Blackboard Architecture to Support Case-Based Reasoning in Mechanical Design

1992 ◽  
Author(s):  
Theodore Bardsz ◽  
Ibrahim Zeid
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Mechanical Design ◽  
Maximum Amount ◽  
Design Solution ◽  
Case Based Reasoning ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Design Plan ◽  
Case Based

Abstract One of the most significant issues in applying case-based reasoning (CBR) to mechanical design is to integrate previously unrelated design plans towards the solution of a new design problem. The total design solution (the design plan structure) can be composed of both retrieved and dynamically generated design plans. The retrieved design plans must be mapped to fit the new design context, and the entire design plan structure must be evaluated. An architecture utilizing opportunistic problem solving in a blackboard environment is used to map and evaluate the design plan structure effectively and successfuly. The architecture has several assets when integrated into a CBR environment. First, the maximum amount of information related to the design is generated before any of the mapping problems are addressed. Second, mapping is preformed as just another action toward the evaluation of the design plan. Lastly, the architecture supports the inclusion of memory elements from the knowledge base in the design plan structure. The architecture is implemented using the GBB system. The architecture is part of a newly developed CBR System called DEJAVU. The paper describes DEJAVU and the architecture. An example is also included to illustrate the use of DEJAVU to solve engineering design problems.

Students' Perceptions Toward an International Telecollaboration Project Through an Engineering-Themed Online Simulation in a Language-Learning Setting

2020 ◽  
pp. 179-202
Author(s):  
Juan Francisco Coll-García
Keyword(s):  
Language Learning ◽  
Student Perceptions ◽  
Undergraduate Students ◽  
Engineering Students ◽  
The United States ◽  
Online Simulation ◽  
Electronic Collaboration ◽  
Efl Students ◽  
Computer Based ◽  
Role Play Simulation

This chapter investigates student perceptions toward an international collaboration that involved an online role-play simulation, Engineers Without Borders (EWB). Forty-two undergraduate students enrolled in an engineering course at a university in the United States were paired with 56 engineering students based at a university in Spain. The simulation was designed and developed not only to foster problem-solving skills, but also to provide opportunities for participants to develop communication skills, teamwork, and professionalism. The simulation also provided opportunities for EFL students to communicate in English and develop their intercultural skills through the use of a variety of electronic collaboration tools. This chapter reports on participant feedback and highlights the benefits of the computer-based nature of the telecollaboration.

scholarly journals Additive Manufacturing as an Essential Element in the Teaching of Robotics

Robotics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 73 ◽  
Author(s):  
Kevin Castelli ◽  
Hermes Giberti
Keyword(s):  
Additive Manufacturing ◽  
System Design ◽  
Mechanical Engineering ◽  
Engineering Students ◽  
Mechanical Design ◽  
Essential Element ◽  
Robotic System ◽  
Master Of Science ◽  
Technology In Teaching ◽  
The Subject

This paper aims to describe how additive manufacturing can be useful in enhancing a robotic course, allowing students to focus on all aspects of the multidisciplinary components of this subject. A three-year experience of the course of “robotic system design” is presented to support the validity of the use of this technology in teaching. This course is specifically aimed at Master of Science (MSc) Mechanical Engineering students and therefore requires one to view the subject in all its aspects including those which are not conventionally taken into consideration such as mechanical design, prototyping and the final realization.

Function Modeling: A Study of Sequential Model Completion Based on Count and Chaining of Functions

2016 ◽  
Author(s):  
Apurva Patel ◽  
William Kramer ◽  
Joshua D. Summers ◽  
Marissa Shuffler-Porter
Keyword(s):  
Engineering Design ◽  
Mechanical Engineering ◽  
Engineering Students ◽  
Solution Space ◽  
Backward Chaining ◽  
Forward Chaining ◽  
Engineering Design Problems ◽  
Initial Seed ◽  
Function Models ◽  
Model Completion

Function models are widely recognized as a useful tool in mechanical engineering conceptual design as a bridge between problem and solution space. Unlike many other engineering design tools that are collaborative allowing many designers to contribute to the design task, function modeling has not been historically presented as a collaborative tool. This paper presents a controlled experimental study that explores the how different initial function models are completed by novice engineers influence the number of functions added to the model. Eighty-eight senior mechanical engineering students were given partial function models to two similarly complex engineering design problems. Each student was asked to complete the function model to best address the problem presented. The number of added functions was compared considering two variables: percent completed of initial seed model (10%, 40%, and 80%), initial chaining of functions (forward, backward, and nucleation). It was found that models for Backward Chaining and Nucleation at 10% initial seed resulted in the greatest addition of functions by the students. Further, Backward Chaining and Nucleation yielded more added functions than Forward Chaining in all seed configurations. Recognizing that there is a difference between Forward Chaining and Backward Chaining or Nucleation, further study is warranted to understand how individuals create function models and which approach yields more useful models to either understand the problem presented or to explore solution options.

Sign in / Sign up

Export Citation Format

Share Document