Intended Participants
Manufacturing executives, industrial engineers, production managers, and digital factory teams
Learning Objectives
Evaluate practical industrial AI use cases, data readiness, and implementation tradeoffs while maintaining human oversight and operational safety.
Delivery Format
Instructor-led seminars, industry case workshops, guided exercises, and an applied capstone; online, hybrid, or in-person by arrangement.
Curriculum · Six Instructional Units
- Industry 4.0, smart manufacturing maturity, and priority use cases
- Production data, sensors, MES/ERP integration, and data quality
- Machine learning for production forecasting and process optimization
- Human-machine workflows, safety, cybersecurity, and model governance
- Pilot design, KPIs, ROI, workforce skills, and change management
- Capstone: smart manufacturing pilot and measurement plan
Applied Program Outcome
Industrial AI use-case portfolio and pilot implementation roadmap
Assessment
Participation and case exercises (30%); applied project (40%); final presentation and reflection (30%).
Institutional Customization
Industry datasets, case studies, schedule, and organizational objectives may be customized after needs assessment.
Important: This is a proposed Beyond Academic curriculum, not a confirmed university or hospital offering. Any certificate or continuing education credit requires separate written confirmation; none is guaranteed. AI content is educational; clinical decisions remain with qualified professionals and authorized institutions.