Fresh in My Mind! Investigating the Effects of the Order of Presenting Opportunistic and Restrictive Design for Additive Manufacturing Content on Creativity

2020 ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Self Efficacy ◽  
Engineering Students ◽  
Manufacturing Processes ◽  
Design For Additive Manufacturing ◽  
Undergraduate Engineering ◽  
Traditional Manufacturing ◽  
Order Of Presentation ◽  
Am Processes ◽  
Design For Am

Abstract Additive manufacturing (AM) processes present designers with creative freedoms beyond the capabilities of traditional manufacturing processes. However, to successfully leverage AM, designers must balance their creativity against the limitations inherent in these processes to ensure the feasibility of their designs. This feasible adoption of AM can be achieved if designers learn about and apply opportunistic and restrictive design for AM (DfAM) techniques at appropriate stages of the design process. Researchers have demonstrated the effect of the order of presentation of information on the learning and retrieval of said information; however, there is a need to explore this effect within DfAM education. In this paper, we explore this gap through an experimental study involving 195 undergraduate engineering students. Specifically, we compare two variations in DfAM education: (1) opportunistic DfAM followed by restrictive DfAM, and (2) restrictive DfAM followed by opportunistic DfAM, against only opportunistic DFAM and only restrictive DfAM training. These variations are compared through (1) differences in participants’ DfAM self-efficacy, (2) their self-reported DfAM use, and (3) the creativity of their design outcomes. From the results, we see that only students trained in opportunistic DfAM, with or without restrictive DfAM, present a significant increase in their opportunistic DfAM self-efficacy. However, all students trained in DfAM — opportunistic, restrictive, or both — demonstrated an increase in their restrictive DfAM self-efficacy. Further, we see that teaching restrictive DfAM first followed by opportunistic DfAM results in the generation of ideas with greater creativity — a novel research finding. These results highlight the need for educators to account for the effects of the order of presenting content to students, especially when educating students about DfAM.

Teaching Design Freedom: Exploring the Effects of Design for Additive Manufacturing Education on the Cognitive Components of Students’ Creativity

2018 ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Design Process ◽  
Self Efficacy ◽  
Domain Knowledge ◽  
Engineering Students ◽  
Design For Additive Manufacturing ◽  
Task Motivation ◽  
Cognitive Components ◽  
Traditional Manufacturing ◽  
Education Groups

Design for manufacturing provides engineers with a structure for accommodating the limitations of traditional manufacturing processes. However, little emphasis is typically given to the capabilities of processes that enable novel design geometries, which are often a point of focus when designing products to be made with additive manufacturing (AM) technologies. In addition, limited research has been conducted to understand how knowledge of both the capabilities (i.e., opportunistic) and limitations (i.e., restrictive aspects) of AM affects design outcomes. This study aims to address this gap by investigating the effect of no, restrictive, and both, opportunistic and restrictive (dual) design for additive manufacturing (DfAM) education on engineering students’ creative process. Based on the componential model of creativity [1], these effects were measured through changes in (1) motivation and interest in AM, (2) DfAM self-efficacy, and (3) the emphasis given to DfAM in the design process. These metrics were chosen as they represent the cognitive components of ‘task-motivation’ and ‘domain relevant skills’, which in turn influence the learning and usage of domain knowledge in creative production. The results of the study show that while the short (45 minute) DfAM intervention did not significantly change student motivation and interest towards AM, students showed high levels of motivation and interest towards AM, before the intervention. Teaching students different aspects of DfAM also resulted in an increase in their self-efficacy in the respective topics. However, despite showing a greater increase in self-efficacy in their respective areas of training, the students did not show differences in the emphasis they gave to these DfAM concepts, in the design process. Further, students from all three education groups showed higher use of restrictive concepts, in comparison to opportunistic DfAM.

Complex Solutions for Complex Problems? Exploring the Role of Design Task Choice on Learning, Design for Additive Manufacturing Use, and Creativity

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Self Efficacy ◽  
Engineering Students ◽  
Educational Interventions ◽  
Problem Statement ◽  
Design Task ◽  
Complex Solutions ◽  
Future Work ◽  
Am Processes

Abstract The integration of additive manufacturing (AM) processes in many industries has led to the need for AM education and training, particularly on design for AM (DfAM). To meet this growing need, several academic institutions have implemented educational interventions, especially project- and problem-based, for AM education; however, limited research has explored how the choice of the problem statement influences the design outcomes of a task-based AM/DfAM intervention. This research explores this gap in the literature through an experimental study with 175 undergraduate engineering students. Specifically, the study compared the effects of restrictive and dual (restrictive and opportunistic) DfAM education, when introduced through design tasks that differed in the explicit use of design objectives and functional and manufacturing constraints in defining them. The effects of the intervention were measured through (1) changes in participant DfAM self-efficacy, (2) participants' self-reported emphasis on DfAM, and (3) the creativity of participants' design outcomes. The results show that the choice of the design task has a significant effect on the participants' self-efficacy with, and their self-reported emphasis on, certain DfAM concepts. The results also show that the design task containing explicit constraints and objectives results in participants generating ideas with greater uniqueness compared with the design task with fewer explicit constraints and objectives. These findings highlight the importance of the chosen problem statement on the outcomes of a DfAM educational intervention, and future work is also discussed.

Consideration of the Manufacturing Trajectories in a Global Design for Additive Manufacturing Methodology

2012 ◽  
Author(s):  
R. Ponche ◽  
O. Kerbrat ◽  
P. Mognol ◽  
J. Y. Hascoet
Keyword(s):  
Additive Manufacturing ◽  
Cost Reduction ◽  
Design Problem ◽  
Manufacturing Processes ◽  
Strong Impact ◽  
Direct Impact ◽  
Design For Additive Manufacturing ◽  
Physical Phenomena ◽  
Am Processes

Additive Manufacturing (AM) is a new way of part production which opens up new perspectives of conception as mass and cost reduction and increase of functionalities. However these processes have their own characteristics which as for all the manufacturing processes have a direct impact on the manufactured parts quality. Especially, because the manufacturing trajectories have a influence on the physical phenomena during the process, they have also a strong impact on the quality of the produced parts in terms of geometry. In this paper, the choice of manufacturing trajectories and their impacts on the final shape and quality of the parts is integrated into a global Design For Additive Manufacturing (DFAM) methodology which allows to move from functional specifications of a design problem to a proposition of an adapted part for AM processes.

The Earlier the Better? Investigating the Importance of Timing on Effectiveness of Design for Additive Manufacturing Education

2018 ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Self Efficacy ◽  
Educational Interventions ◽  
Layer By Layer ◽  
Design For Additive Manufacturing ◽  
Layer Deposition ◽  
Subtractive Manufacturing ◽  
The Impact ◽  
Design Ideas ◽  
Am Processes

Additive Manufacturing (AM) is a novel process that enables the manufacturing of complex geometries through layer-by-layer deposition of material. AM processes provide a stark contrast to traditional, subtractive manufacturing processes, which has resulted in the emergence of design for additive manufacturing (DfAM) to capitalize on AM’s capabilities. In order to support the increasing use of AM in engineering, it is important to shift from the traditional design for manufacturing and assembly mindset, towards integrating DfAM. To facilitate this, DfAM must be included in the engineering design curriculum in a manner that has the highest impact. While previous research has systematically organized DfAM concepts into process capability-based (opportunistic) and limitation-based (restrictive) considerations, limited research has been conducted on the impact of teaching DfAM on the student’s design process. This study investigates this interaction by comparing two DfAM educational interventions conducted at different points in the academic semester. The two versions are compared by evaluating the students’ perceived utility, change in self-efficacy, and the use of DfAM concepts in design. The results show that introducing DfAM early in the semester when students have little previous experience in AM resulted in the largest gains in students perceiving utility in learning about DfAM concepts and DfAM self-efficacy gains. Further, we see that this increase relates to greater application of opportunistic DfAM concepts in student design ideas in a DfAM challenge. However, no difference was seen in the application of restrictive DfAM concepts between the two interventions. These results can be used to guide the design and implementation of DfAM education.

Break It Down: Comparing the Effects of Lecture- and Module-Style Design for Additive Manufacturing Educational Interventions on Students’ Learning and Creativity

2021 ◽  
Author(s):  
Rohan Prabhu ◽  
Timothy W. Simpson ◽  
Scarlett R. Miller ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Educational Intervention ◽  
Self Efficacy ◽  
Educational Interventions ◽  
Evaluation Metrics ◽  
Single Session ◽  
Information Retention ◽  
Design Creativity ◽  
Am Processes ◽  
Design For Am

Abstract Given the growing presence of additive manufacturing (AM) processes in engineering design and manufacturing, there has emerged an increased interest in introducing AM and design for AM (DfAM) educational interventions in engineering education. Several researchers have proposed AM and DfAM educational interventions; however, some argue that these efforts might not be sufficient to develop higher-level skills among engineers (e.g., identifying design opportunities that leverage AM capabilities). Prior work has shown that longer, distributed educational interventions are more effective in encouraging learning and information retention; however, these interventions could also be time-consuming and expensive to implement. Therefore, there is a need to test the effectiveness of longer, distributed DfAM educational interventions compared to shorter, lecture-style interventions. Our aim in this research is to explore this research gap through an experimental study. Specifically, we compared two variations of a DfAM educational intervention: (1) a module-style intervention spread over two sessions with the introduction of DfAM evaluation metrics, and (2) a lecture-style intervention completed in a single session with no evaluation metrics introduced. From our results, we see that students who received the module-style intervention reported a greater increase in their DfAM self-efficacy. Additionally, students who received the module-style intervention reported having given a greater emphasis on part consolidation and feature size. Finally, we observe that the structure of the educational intervention did not influence the creativity of ideas generated by the participants. These findings highlight the utility of module-style DfAM educational interventions towards increasing DfAM self-efficacy, but not necessarily design creativity. Moreover, these findings highlight the need to formulate educational interventions that are effective and efficient.

scholarly journals Additive Manufacturing and Big Data

2016 ◽  
Vol 1 (3) ◽  
pp. 107-121 ◽  
Author(s):  
Lidong Lidong ◽  
Cheryl Ann Alexander
Keyword(s):  
Big Data ◽  
Additive Manufacturing ◽  
Supply Chains ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Manufacturing Processes ◽  
Geometric Shapes ◽  
Traditional Manufacturing ◽  
Am Processes

Additive manufacturing (AM) can produce parts with complex geometric shapes and reduce material use and weight. However, there are limited materials available for AM processes; the speed of production is slower compared with traditional manufacturing processes. Big Data analytics helps analyze AM processes and facilitate AM in impacting supply chains. This paper introduces advantages, applications, and technology progress of AM. Cybersecurity in AM and barriers to broad adoption of AM are discussed. Big data in AM and Big Data analytics for AM are also presented.

Development of a Design for Additive Manufacturing Worksheet for Medical Casts

2021 ◽  
Author(s):  
Heena Noh ◽  
Kijung Park ◽  
Kiwon Park ◽  
Gül E. Okudan Kremer
Keyword(s):  
Additive Manufacturing ◽  
High Strength ◽  
Design Guidelines ◽  
Operational Performance ◽  
Design For Additive Manufacturing ◽  
Trade Offs ◽  
Novice Designers ◽  
Criteria Importance ◽  
Design For Am

Abstract Traditional plaster casts often cause dermatitis due to disadvantages in usability and wearability. Additive manufacturing (AM) can fabricate customized casts to have light-weight, high strength, and better air permeability. Although existing studies have provided design for additive manufacturing (DfAM) guidelines to facilitate design applications for AM, most relevant studies focused on the mechanical properties of outputs and too general/specific design guidelines; novice designers may still have difficulty understanding trade-offs between functional and operational performance of various DfAM aspects for medical casts. As a response, this study proposes a DfAM worksheet for medical casts to effectively guide novice designers. First, important DfAM criteria and their possible solutions for medical casts are examined through a literature review to construct a basic DfAM framework for medical casts. Next, a scoring system that considers relative criteria importance and criteria evaluation from both functional and operational perspectives is developed to identify the overall suitability of a medical cast design for AM. A case study of finger cast designs was performed to identify the DfAM performance of the sample designs along with redesign requirements suggested by the worksheet. The proposed worksheet would be used to achieve rapid medical cast design by objectively assessing its suitability for AM.

Design for Additive Manufacturing in the Cloud Platform

2017 ◽  
Author(s):  
Yuanbin Wang ◽  
Robert Blache ◽  
Xun Xu
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Additive Manufacturing ◽  
Full Advantage ◽  
New Technologies ◽  
Design Stage ◽  
Design For Additive Manufacturing ◽  
Cloud Platform ◽  
Am Processes

Additive manufacturing (AM) has experienced a phenomenal expansion in recent years and new technologies and materials rapidly emerge in the market. Design for Additive Manufacturing (DfAM) becomes more and more important to take full advantage of the capabilities provided by AM. However, most people still have limited knowledge to make informed decisions in the design stage. Therefore, an interactive DfAM system in the cloud platform is proposed to enable people sharing the knowledge in this field and guide the designers to utilize AM efficiently. There are two major modules in the system, decision support module and knowledge management module. A case study is presented to illustrate how this system can help the designers understand the capabilities of AM processes and make rational decisions.

scholarly journals Technopreneurial Intentions: The Effect of Innate Innovativeness and Academic Self-Efficacy

2021 ◽  
Vol 14 (1) ◽  
pp. 238
Author(s):  
Sa’Ed M. Salhieh ◽  
Yousef Al-Abdallat
Keyword(s):  
Indirect Effect ◽  
Self Efficacy ◽  
Structural Equation ◽  
Engineering Students ◽  
New Technology ◽  
Equation Modeling ◽  
Undergraduate Engineering ◽  
Academic Self Efficacy ◽  
Self Administered Questionnaire ◽  
Positive Effect

Several factors can affect students’ intention to start a new technology-based venture (technopreneurial intentions). Understanding these factors is important when developing technical educational programs. This study investigates the effect of innate innovativeness and academic self-efficacy on technopreneurial self-efficacy and the forming of technopreneurial intentions. It does this by developing a conceptual model that relates technopreneurial intentions, technopreneurial self-efficacy, academic self-efficacy, and innate innovativeness. The data was collected from 378 undergraduate engineering students enrolled in a Jordanian university with a self-administered questionnaire survey. The results of the structural equation modeling (SEM) using AMOS showed that technopreneurial self-efficacy had a positive and significant impact on technopreneurial intentions. Academic self-efficacy had both a direct and indirect positive effect on technopreneurial intention. The indirect effect occurred through increased technopreneurial self-efficacy. Innate innovativeness had a direct effect on technopreneurial intentions, but it did not have a significant indirect effect through technopreneurship self-efficacy as was initially hypothesized. The findings suggest that those who show interest in starting a new technology-based venture have a strong belief in their abilities to perform the technological and entrepreneurial tasks needed, are confident about their ability to acquire the academic technical skills required, and have the inner motivation to seek what is technologically new and different.

scholarly journals Investigation of microstructure and hardness of a rib geometry produced by metal forming and wire-arc additive manufacturing

2018 ◽  
Vol 190 ◽  
pp. 02005 ◽  
Author(s):  
Markus Hirtler ◽  
Angelika Jedynak ◽  
Benjamin Sydow ◽  
Alexander Sviridov ◽  
Markus Bambach
Keyword(s):  
Additive Manufacturing ◽  
Metal Forming ◽  
Batch Size ◽  
Unit Costs ◽  
Batch Sizes ◽  
Traditional Manufacturing ◽  
Manufacturing Technologies ◽  
Forming Tools ◽  
Wire Arc Additive Manufacturing ◽  
Am Processes

Within the scope of consumer-oriented production, individuality and cost-effectiveness are two essential aspects, which can barely be met by traditional manufacturing technologies. Conventional metal forming techniques are suitable for large batch sizes. If variants or individualized components have to be formed, the unit costs rise due to the inevitable tooling costs. For such applications, additive manufacturing (AM) processes, which do not require tooling, are more suitable. Due to the low production rates and limited build space of AM machines, the manufacturing costs are highly dependent on part size and batch size. Hence, a combination of both manufacturing technologies i.e. conventional metal forming and additive manufacturing seems expedient for a number of applications. The current study develops a process chain combining forming and additive manufacturing. First, a semi-finished product is formed with forming tools of reduced complexity and then finished by additive manufacturing. This research investigates the addition of features using AlSi12 created by Wire Arc Additive Manufacturing (WAAM) on formed EN-AW 6082 preforms. By forming, the strength of the material was increased, while this effect was partly reduced by the heat input of the WAAM process.

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