Key Terms, Descriptions, and Definitions

We have used a few terms in our postings with which you may not be familiar. This posting contains key terms, descriptions, and definitions. 

Big Data Analytics and Artificial Intelligence allow factories to analyze the data derived from the digital connections between virtual and physical worlds and quickly optimize their operations.  

Cloud Computing and 5G allows smart factories to store, process, and share data with greater flexibility at a lower cost than traditional on-premises alternatives. Interconnected devices and machines can quickly upload large amounts of data that can be processed to provide feedback and make decisions in near real-time.

Cyber-Physical Systems (CPS) are collections of physical and computer components that are integrated with each other and controlled or monitored by computer-based algorithms. The most advanced of these systems are Intelligent Products. For example, fully autonomous manufacturing robots can produce patterns, reason, learn, anticipate events, and link with larger networks.

Digital Twin (DT) technology creates in virtual spaces, high-fidelity, parallel, 3-D virtual digital images of physically existing environments, processes, or individual objects. It simulates the behaviors of the objects in the real world and provides feedback. By quickly and accurately detecting and predicting physical issues with CPS systems, it contributes to the optimization of manufacturing processes.

Human-Machine Interface (HMI) is the user interface that allows operators to connect the controller for an industrial system. The controllers are integrated software designed to monitor and control the operation of machinery and associated devices in industrial environments.

Industrial Internet of Things (IIoTs). These are interconnected sensors, instruments, devices, machines, and/or processes that are linked by data communication systems to enable the exchange and use of data between people and machines. They allow higher levels of automation and production optimization by collecting and storing data on a cloud for tracking, data exchange, and analysis.

 

5. Digital Disruptions of Work and Skills Needed During Industry 4.0

 

This episode focuses on identifying who is most affected by Industry 4.0. It explores the concept of Smart Factories and how digital innovations are disrupting the manufacturing jobs of workers. It concludes by examining Learning Factories as an example of collaborative work-learning opportunities for current and future workers.

• What sectors of our population do you believe is (or will be) most affected by Industry 4.0?
• What are your experiences with Smart Factories? What impact will they have on the future nature of work?
• What are your experiences with Learning Factories? To what extent should they be adopted for the preparation of learners for jobs during Industry 4.0?
• What populations of adult learners will be most challenged to obtain quality employment opportunities in an era of Smart Factories and Learning Factories?
  

 Listen to Podcast

 AHE FutureTech Episode 5 Transcript

References

Burghardt, A., Szybicki, D., Gierlak, P., Kurc, K., Pietruś, P., & Cygan, R. (2020). Programming of industrial robots using virtual reality and digital twins. Applied Sciences, 10(2), 486.

 

Elbestawi, M., Centea, D., Singh, I., & Wanyama, T. (2018). SEPT learning factory for industry 4.0 education and applied research. Procedia manufacturing, 23, 249-254.

 

Mohammed, S. &  Fiaidhi, J. (2019). Cyber physical systems: A new frontier of artificial intelligence: Summary paper pp.23-30. http//dx.doi.org/10.14257/ijca.2019.12.1.03

 

Morgan, J. (2019). Will we work in twenty-first century capitalism? A critique of the fourth industrial revolution literature. Economy and Society, 48(3), 371-398.

 

Muro, M., Liu, S., Whiton, J., & Kulkarni, S. (2017). Digitalization and the American workforce. Organisation for Economic Co‐operation and Development. (2019). Preparing for the changing nature of work in the digital era.

 

Prinz, C., Morlock, F., Freith, S., Kreggenfeld, N., Kreimeier, D., & Kuhlenkötter, B. (2016). Learning factory modules for smart factories in industrie 4.0. Procedia CiRp, 54, 113-118.

 

Raff, S., Wentzel, D., & Obwegeser, N. (2020). Smart products: conceptual review, synthesis, and research directions. Journal of Product Innovation Management, 37(5), 379-404.

 

Tao, F., Qi, Q., Wang, L., & Nee, A. Y. C. (2019). Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Engineering, 5(4), 653-661.

4. Implications of Workplace Changes to Adult and Higher Education

Web 3.0 inspired Industry 4.0 changes in the workplace have affected adult and higher education practices. Listen to our podcast to learn about the intersection between adult and higher education and workplace changes, what upskilling and reskilling mean in today’s workplace, how adult and higher education can partner with the workplace in upskilling and reskilling employees, and why the new digital skills are needed today.

What are your experiences with Web 3.0 changes in your workplace that have affected adult and higher education practices?

Podcast Link

AHE FutureTech Episode 4 Transcript

References

Caselli, F. (1999). Technological revolutions. American Economic Review, 89(1), 78-102.

Muro, M., Liu, S., Whiton, J., & Kulkarni, S. (2017). Digitalization and the American workforce. 

Organisation for Economic Co‐operation and Development. (2019). Preparing for the changing nature of work in the digital era.

3. Implications of Digital Innovation for Adult and Higher Education

 

Technology is everywhere, but we rarely take the time to deeply consider how profoundly these technologies impact the interconnected systems in which we work. Listen to our podcast to learn more how the digital technologies have impacted and will continue to have implications on the position of adult and higher education.

Listen to Podcast

AHE FutureTech Episode 3 Transcript

How have you experienced spatial web technologies disruptions in adult and higher education? 

2. Current and Projected Use of the Spatial Web in Adult and Higher Education

 

The Spatial Web is the next evolutionary stage of development for the World Wide Web, and it simultaneously connects to and integrates four emerging computing technologies: spatial technologies, physical technologies, cognitive technologies, and distributed technologies. Listen to our podcast to learn more about these innovative digital technologies, how they are currently used in adult and higher education, and how they are projected to be used in the near and distant future.

 

Listen to the Podcast

 

 AHE FutureTech Episode 2 Transcript

How have you used spatial web technology in adult and higher education?

 

 

References

 

Pates, D. (2020). The holographic academic: Rethinking telepresence in higher education. In Emerging technologies and pedagogies in the curriculum (pp. 215-230). Springer, Singapore.

Picciano, A. G. (2012). The evolution of big data and learning analytics in American higher education. Journal of asynchronous learning networks, 16(3), 9-20. 

René, G. Mapes D. (2019). The Spatial Web: How web 3.0 will connect humans, machines and AI to transform the world‖ Paperback.

Riel, J. (2021). Essential features and critical issues with educational chatbots: Toward personalized learning via digital agents. In Handbook of Research on Modern Educational Technologies, Applications, and Management (pp. 246-262). IGI Global.