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Monitoring 3D Printer Performance using Internet of Things (IoT) Application

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

ETD Internet of Things (IOT)

Tagged Division

Engineering Technology

Page Count

8

DOI

10.18260/1-2--28686

Permanent URL

https://peer.asee.org/28686

Download Count

2090

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Paper Authors

biography

Shuning Li Indiana University-Purdue University Indianapolis

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Education: Ph.D. in Mechanical Engineering
Research Interests:
1. Systems Engineering and Product Lifecycle Management More than 4 years of consulting experiences for different industries to optimized and standardized design and development workflow, and implement enterprise level information systems like PLM.
2. Medical Image Processing
Focusing on medical image processing for dental applications. Involved in several clinical studies and developed a novel surface based image registration program to provide a more reliable and efficient approach to quantify treatment outcomes and possible side effects in orthodontic treatment.

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biography

Elizabeth Freije Indiana University-Purdue University, Indianapolis

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Elizabeth Freije is a Lecturer in the Department of Engineering Technology at Purdue University, Indianapolis. She received her BS in Computer Engineering Technology with a minor in Mathematics. She received her Masters in Technology at Purdue University, Indianapolis. She teaches classes in programming languages, embedded micro-controllers, mobile devices, and programmable logic controllers.

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biography

Paul Yearling P.E. Indiana University-Purdue University, Indianapolis

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Paul Yearling
Education: PhD. Major: Mechanical Engineering, Minor: Applied Mathematics
Professional Engineer License
Certifications: Lean Six Sigma Black Belt
Current Position: Associate Chair Engineering Technology and Mechanical Engineering Technology Program Director

Industrial Experience

Over 20 years of industrial experience initially as a Royal Naval Dockyard indentured craftsman machinist and Design Draftsman and project manager on Leander class Steam Turbine Naval frigates and diesel electric submarines. Most recently includes 12 years in Research and Development and Lean Six Sigma process improvement experience troubleshooting process issues in the Paper, Chemical, and Converting Industries.

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Abstract

Most of the current desktop 3D printers are built based on open-source designs from online communities. The largest group of open-source 3D printers is the Self-Replicating Rapid Prototype (RepRap) 3D printers. A RepRap 3D printer needs to connect to a computer or a microprocessor to feed G Code and provide interface for users to control the 3D printer. However, local computer is a relatively expensive solution comparing to the cost of a RepRap 3D printer; while the microprocessor has much less computing capability comparing to a normal computer, and cannot handle computing-intensive jobs like slicing 3D objects or generating G Code. An alternate solution is to use the internet of things (IoT) application to control and monitor 3D printers. IoT is the network of physical devices, vehicles, buildings and other items, allowing objects to be sensed and controlled remotely across existing network. IoT and 3D printing are two important new technologies, which progressively impact a lot of areas of the industries and also our everyday life. Students need to be introduced to these technologies, and get ready for future career opportunities. A multidisciplinary student project is developed to provide students access to both 3D printer and IoT platform, and also learn to collaborate with engineers from other disciplines to solve complex engineering problems. The objective of the project is to design and develop an IoT application to remote monitor the performance of a RepRap 3D printer including the printing progress and the temperatures of the heated bed and hot end. Major tasks involved in the project are: to inspect and upgrade the current 3D printer to avoid any possible compliance issues between the 3D printer and the hardware components or software tools for the IoT application; to connect the 3D printer to the Raspberry Pi microprocessor; and to design and develop the IoT application. The methods and algorithms of connecting a 3D printer to an IoT application is reported, and the IoT application interface and workflow will be presented in the results section. As a pilot study, this project provides first-hand data on the requirements of time and resources to introduce IoT to undergraduate students. Suggestions on timeline, prerequisites, training materials, hardware, software, and testing plans will also be discussed in the results section.

Li, S., & Freije, E., & Yearling, P. (2017, June), Monitoring 3D Printer Performance using Internet of Things (IoT) Application Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28686

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