Learning environments should reflect the realities of Industry 4.0--transforming traditional classroom labs into simulated smart factories.

Reimagining manufacturing engineering labs for the age of AI and IoT

Learning environments should reflect the realities of Industry 4.0--transforming traditional classroom labs into simulated smart factories is necessary for workforce success

Key points:

Investing in simulation technology ensures manufacturing engineering programs are aligned with industry needs.         

Drop the wrench and grab the VR headset. Emerging tech is changing the way we do business in the manufacturing sector. In fact, the technologies manufacturers are most likely to employ in the coming year are: artificial intelligence (AI), augmented, virtual, and mixed reality (XR), and data analytics, according to a 2024 predictions survey.   

Working in a dynamic and complex Industry 4.0 environment requires individuals to wear many hats. For example, systems engineers must adapt to frequent technological advancements and disruptions, navigate a changing supply chain, proactively address cybersecurity concerns, operate with sustainability in mind, and collaborate with diverse and often international teams, while embracing continuous learning and upskilling.    

Emerging tech is not only transforming the way we work, it’s transforming the way we teach and how we learn. When assessing manufacturing education, it is essential to ask: How well are we equipping students with the technical expertise needed to navigate a smart factory? This can present a significant challenge for educators.    

A simulated smart factory in the classroom

Equipping modern learning spaces with interconnected machines, data visualization tools, and collaborative software platforms provides students with a realistic taste of life on the factory floor. The learning environment should reflect the realities of Industry 4.0, therefore, transforming traditional classroom labs into simulated smart factories is a necessity for success upon entering the workforce.

Cyber-physical lab considerations for the classroom include:

  • IoT (Internet of Things): In a smart factory, everything is connected digitally. Sensors on factory floors, robots, and other industrial equipment allow data to be collected and analyzed. Investing in cloud-based platforms to store and analyze data is a great first step for the classroom.
  • Robotics and automation: Robots and cobots speed up the production process and reduce costs for manufacturers. Consider investing in a cobot for the classroom for early exposure to working alongside a robot coworker.
  • Machine learning and AI: Machine learning and AI are powered by algorithms. This technology can make valuable decisions and predictions that are improved over time with experience. In industry, AI is leveraged for predictive maintenance, sorting complex custom orders, and lends to overall process optimization with improved data analysis and decision-making. 
  • Digital twins: Digital twins provide data and insights to help inform how their physical counterparts should operate. Industries including manufacturing, aviation, maritime, and agriculture use digital twin technology to optimize operations and ensure systems are running as efficiently as possible. 
  • Augmented reality and virtual reality: AR/VR can help students grasp abstract concepts more intuitively. Beyond the engaging elements of gamification, AR can be used for safety training in manufacturing environments by providing warnings and alerts regarding potential hazards.

Integrating simulated smart factories in the classroom requires significant time and investment, but the ROI can be substantial. By familiarizing students with the technologies and processes of Industry 4.0, we can bridge the gap between theoretical knowledge and practical application. 

A pedagogical shift 

Investing in new technology alone isn’t enough. Comprehensive Industry 4.0 education and training requires an evolution in curriculum and modern facilities as well. As Kevin Craig, a professor of engineering explained, “Engineering content must be broken apart, updated, and rebundled with a balance between fundamentals and industry best practice.”   

The Department of Manufacturing Engineering at Brigham Young University, for example, has taken thoughtful measures towards scaling its laboratory innovation since 2016. Today, the university is powering a state-of-the-art cyber-physical lab with data-rich AR that resonates with students and employers in terms of fostering the right qualifications and skill sets to hit the ground running.

The Community College of Allegheny County is another institution making smart investments in innovation. CCAC recently celebrated the grand opening of its 60,000-square-foot Center for Education, Innovation & Training (CEIT). The center was built with specialized facilities to accommodate Industry 4.0, including 3D printing, computer numerical control (CNC) machining, machine learning, and robotics and automation.  

A collaborative future

Undoubtedly, emerging technologies and pedagogical approaches present a paradigm shift for manufacturing education–one that requires thoughtful collaboration among educators, industry experts, and technology providers. Automation shouldn’t be feared as a replacement for human workers. Instead, our focus should be on properly educating and training highly skilled humans and machines to work in tandem. By adapting training methods and simulating smart factories in the classroom, we can equip learners with the technical skills, analytical prowess, and problem-solving abilities required to lead a collaborative digital future.

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