Bachelor of Applied Science in Integrated Digital Manufacturing Engineering Technology

Integrated Digital Manufacturing Technology (IDM), often referred to as Smart or Data-Driven Manufacturing, is an engineering field dedicated to improving manufacturing productivity, quality, safety, uptime, and optimization.  IDM achieves improved manufacturing by controlling, analyzing, and implementing new sensor technologies designed to enhance all aspects of production through gathering data, analyzing data, and providing solutions based on information modeling.  Integrated Digital Manufacturing Technology seeks to solve manufacturing issues by implementing data-driven decision-making. 

Students completing this degree will gain a comprehensive knowledge of manufacturing and automated systems, mechanical devices, electrical issues, industrial information technology and networking.  This program will guide students to gain an operational knowledge base to complement acquired information technology skills.  This is accomplished thorugh a combination of learning skills in Human Data Input (HDI), robotics, programmable logic controllers (PLC), smart and wireless sensors and devices, utilizing the Industrial Internet of Things (IIoT), and supervisory control and data acquisition (SCADA) software and hardware.  Graduates will design or use a system of software and hardware elements that allow industrial organizations to control industrial processes locally or at remote locations as well as monitor, gather, and use real-time process data while directly interacting with devices from anywhere in the world.  Students in the IDM program will acquire knowledge of electrical, mechanical, networking engineering, cybersecurity, cloud security, enterprise security, and design knowledge as essential parts of this program. 

Program Contact:  Learn More.

Related Programs/Training

Smart Manufacturing - Mechatronics, Associate of Applied Science

Program Learning Outcomes

This program is designed to prepare students to demonstrate the following learning outcomes:

1. Demonstrate knowledge of manufacturing processes, technologies, and operations.
2. Ability to perform rapid prototyping, complex part manufacturing, and spare part creation.
3. Ability to perform troubleshooting activities and aid manufacturing in future machine learning activities when combined with big data initiatives
4. Demonstrate ability to enable IIoT applications with edge computing such as predictive analytics and maintenance, digital twin, and machine learning and optimization.
5. Demonstrate knowledge of connectivity for IACS devices, including sensors, actuators, and controllers and assets such as robots.
6. Ability to use plant-wide applications such as manufacturing execution systems, supervisory control and data acquisition (SCADA), historians, and asset managers.
7. Implement, evaluate, and provide securely integrated to IIoT, enterprise, and cloud services.

Suggested Semester Sequence

¹

Highly Recommend PHYS-1210 College Physics I.

MATH-1140, MATH-1141, MATH-1200, MATH-1270, and MATH-1280 can no longer count towards fulfilling the college-level mathematics requirement.  These courses were re-classified as developmental mathematics by the state of Ohio in 2016.  Tri-C established a 5-year transitioning window for students who had completed these courses prior to 2016 to apply them towards meeting graduation requirements, which expired in Summer 2021. It is highly recommended to see a counselor to determine the appropriate math required for your current major.