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3D printing (3DP) has been becoming more and more popular throughout the education system from Kindergarten to University. High school is a critical period for students to decide their imminent university major selection which in turn will impact their future career choices. High school students are usually intrigued by hands-on tool such as 3DP which is also an important contributor to other courses such as robotics. The recent years have seen more investment and availability of 3DP in high schools, especially Career and Technical Education (CTE) programs. However, mere availability of 3DP is not enough for teachers to fully utilize its potential in their classrooms. While basic 3DP skills can be obtained through a few hours of training, the basic training is insufficient to ensure effective teaching Engineering Design Process (EDP) at the high school level. To address this problem, this project develops an EDP course tightly integrated with 3DP for preservice teachers (PST) who are going to enter the workforce in high schools. Engineering design process (EDP) has become an essential part for preservice teachers (PST), especially for high school STEM. 3DP brought transformative change to EDP which is an iterative process that needs virtual/physical prototyping. The new PST course on EDP will be purposefully integrated with an in-depth discussion of 3DP. The approach is to dissect a 3D printer’s hardware, explain each component’s function, introduce each component’s manufacturing methods, describe possible defects, and elucidate what works and what does not. This has at least four benefits: 1) PSTs will know what is possibly wrong when a printer or printing process fails, 2) PSTs will learn more manufacturing processes besides 3DP that can be used to support engineering design prototyping, 3) PSTs will know how to design something that can meet the manufacturing constraints, i.e., can be actually fabricated, and 4) reduce errors and frustrations caused by failed design and failed prints which happen frequently to novices in 3DP. After graduation, PSTs will bring the knowledge to their future high schools and will be more confident in teaching engineering design, reverse engineering, prototype development, manufacturing, and technology. The developed course will be implemented and assessed in a future semester.
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Machine learning enabled integrated formulation and process design framework for a pharmaceutical 3D printing platform
Abstract The pharmaceutical manufacturing sector needs to rapidly evolve to absorb the next wave of disruptive industrial innovations—Industry 4.0. This involves incorporating technologies like artificial intelligence and 3D printing (3DP) to automate and personalize the drug production processes. This study aims to build a formulation and process design (FPD) framework for a pharmaceutical 3DP platform that recommends operating (formulation and process) conditions at which consistent drop printing can be obtained. The platform used in this study is a displacement‐based drop‐on‐demand 3D printer that manufactures dosages by additively depositing the drug formulation as droplets on a substrate. The FPD framework is built in two parts: the first part involves building a machine learning model to simulate the forward problem—predicting printer operation for given operating conditions and the second part seeks to solve and experimentally validate the inverse problem—predicting operating conditions that can yield desired printer operation.
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- Award ID(s):
- 2132142
- PAR ID:
- 10443358
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- AIChE Journal
- Volume:
- 69
- Issue:
- 4
- ISSN:
- 0001-1541
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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