Incorporating Rapid Prototyping Machine in Teaching Mechanical Engineering Design

Author(s):  
Mohamed B. Trabia ◽  
Kevin Nelson

There is a trend toward increasing exposure of students to hands-on experience in mechanical engineering design courses as these courses are usually limited to generating calculations and drawings of mechanical designs. Students in these courses may lack the ability to visualize and create the physical objects that correspond to their calculations. This limitation may negatively affect students, especially those with limited hands-on experience. To address this issue, the Department of Mechanical Engineering, University of Nevada, Las Vegas (UNLV) started requiring students to create their design using a rapid prototyping machine as a part of the Mechanical Engineering Design Course (ME 440). Students in this course work in teams to create projects starting from abstract statements. They are required to use their calculations as a means to create solid models of the components of their designs and print them on the rapid prototyping machine. Such an approach results in a better understanding of the functionalities of components as well as fit and tolerance issues. Student feedback is used as well as future venues for improving the course.

Author(s):  
Mahmoud Dinar ◽  
Jami J. Shah

Problem formulation is an essential design skill for which assessment methods have been less commonly developed. In order to evaluate the progress of a group of graduate students in mechanical engineering design in regard with the problem formulation skill, they were asked to work on three design problems using the Problem Formulator web tool during their course work. Changes in a set of measures elicited from this data were examined in addition to sketches, simulations, and working prototypes. Inventories of requirements and issues, as well as concepts derived from morphological charts were created to assess designers’ skills and outcomes.


Author(s):  
Daniel Koutny´ ◽  
David Palousˇek ◽  
Jan Brandejs

The article explains a newly utilized project-oriented curriculum at the Institute of Machine and Industrial Design. In addition to digital technologies, the curriculum focuses on practical tasks with the utilization of advanced technologies in the area of mechanical design processes, such as Rapid Prototyping, Vacuum Casting etc. The paper describes a new approach to teamwork, where groups of students manage project tasks from the design phase up to the manufacturing of the real product.


2013 ◽  
Vol 8 (1) ◽  
pp. 65-80 ◽  
Author(s):  
Tom Joyce ◽  
Iain Evans ◽  
William Pallan ◽  
Clare Hopkins

2020 ◽  
Author(s):  
Martin Biermann ◽  
Salim Kanoun ◽  
Trond Davidsen ◽  
Robert Gray

Abstract Aims Since 2017, medical students at the University of Bergen were taught PET/CT “hands-on” by viewing PET/CT cases in native format on diagnostic workstations in the hospital. Due to the COVID-19 pandemic, students were barred access. This prompted us to launch and evaluate a new freeware PET/CT viewing system hosted in the university network. Methods We asked our students to install the multiplatform Fiji viewer with Beth Israel PET/CT plugin (http://petctviewer.org) on their personal computers and connect to a central image database in the university network based on the public domain orthanc server (https://orthanc-server.com). At the end of course, we conducted an anonymous student survey. Results The new system was online within eight days, including regulatory approval. All 76 students (100 %) in the fifth year completed their course work, reading five anonymized PET/CT cases as planned. 41 (53 %) students answered the survey. Fiji was challenging to install with a mean score of 1.8 on a 5-point Likert scale (5 = easy, 1 = difficult). Fiji was more difficult to use (score 3.0) than the previously used diagnostic workstations in the hospital (score 4.1; p < 0.001, paired t-test). Despite the technical challenge, 47 % of students reported having learnt much (scores 4 and 5); only 11 % were negative (scores 1 and 2). 51 % found the PET/CT tasks engaging (scores 4 and 5) while 20 % and 5 % returned scores 2 and 1, respectively. Conclusion Despite the initial technical challenge, “hands-on” learning of PET/CT based on the freeware Fiji/orthanc PET/CT-viewer was associated with a high degree of student satisfaction. We plan to continue running the system to give students permanent access to PET/CT cases in native format regardless of time or location.


Author(s):  
Marvin Drewel ◽  
Leon Özcan ◽  
Jürgen Gausemeier ◽  
Roman Dumitrescu

AbstractHardly any other area has as much disruptive potential as digital platforms in the course of digitalization. After serious changes have already taken place in the B2C sector with platforms such as Amazon and Airbnb, the B2B sector is on the threshold to the so-called platform economy. In mechanical engineering, pioneers like GE (PREDIX) and Claas (365FarmNet) are trying to get their hands on the act. This is hardly a promising option for small and medium-sized companies, as only a few large companies will survive. Small and medium-sized enterprises (SMEs) are already facing the threat of losing direct consumer contact and becoming exchangeable executers. In order to prevent this, it is important to anticipate at an early stage which strategic options exist for the future platform economy and which adjustments to the product program should already be initiated today. Basically, medium-sized companies in particular lack a strategy for an advantageous entry into the future platform economy.The paper presents different approaches to master the challenges of participating in the platform economy by using platform patterns. Platform patterns represent proven principles of already existing platforms. We show how we derived a catalogue with 37 identified platform patterns. The catalogue has a generic design and can be customized for a specific use case. The versatility of the catalogue is underlined by three possible applications: (1) platform ideation, (2) platform development, and (3) platform characterization.


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