This project is supporting and creating innovative curriculum, lab exercises and pathways to increase the number of qualified technicians and engineers in the areas of operation, troubleshooting, design and integration of automated manufacturing systems (industrial automation). The curriculum pathways include a series of courses, lab exercises (hands-on, remote and virtual formats) and learning experiences that equip students for a successful career in automated systems and industrial automation. Innovative instructional technologies including intelligent tutoring systems, simulation, animation, and games will utilized to make industrial automation education more accessible and interesting.
This project, sponsored by NSF, is focusing on understanding how engineers develop expertise in the area of system integration and how to help students develop system integration skills reliably and efficiently. This system will involve knowledge of the characteristics of the various mechanical and electrical devices available to make up the system, including their functions, power requirements, and specific characteristics, and the ability to write PLC programs to orchestrate and synchronize the process being automated.
This project, sponsored by NSF, is to design, develop, evaluate, and disseminate a web-based system called Learning Environment for
Automated System Integration (LearnASI) that will help students and new engineers to learn system integration concepts. LearnASI includes
1)Animations and tutorials on system integration concepts and procedures;
2)Detailed case studies on the design of automated systems;
3)Intelligent problem-solving environments that will allow students to design and test automated systems.
In addition, LearnASI is being leveraged as part of another NSF project called Collaborative Learning Environment for Automated Manufacturing System Integration (CLE-ASI). This work will develop new virtual collaborative learning environments with emphasis on communication and teamwork for engineering students studying automated manufacturing. It will allow students to engage in more realistic collaborative activities with other students and also with working engineers. Input from industry engineers will provide an understanding of current practices, and the results of this research will be of benefit to both engineering students and industry. Advanced automated manufacturing capability is essential to national competitiveness, and effective integration of systems level thinking into the engineering curriculum using this research will better prepare engineering students to work in this area.