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One of the characteristic features of the next-generation of Industry 4.0 is human-centricity, which in turn includes two technological advancements: Artificial Intelligence and the Industrial Metaverse. In this work, we assess the impact that AI played on the advancement of three technologies that emerged to be cornerstones in the fourth generation of industry: intelligent industrial robotics, unmanned aerial vehicles, and additive manufacturing. Despite the significant improvement that AI and the industrial metaverse can offer, the incorporation of many AI-enabled and Metaverse-based technologies remains under the expectations. Safety continues to be a strong factor that limits the expansion of intelligent industrial robotics and drones, whilst Cybersecurity is effectively a major limiting factor for the advance of the industrial metaverse and the integration of blockchains. However, most research works agree that the lack of the skilled workforce will no-arguably be the decisive factor that limits the incorporation of these technologies in industry. Therefore, long-term planning and training programs are needed to counter the upcoming shortage in the skilled workforce.

 

Mechatronics for Technologists and Technicians was recognized as an occupation by the U.S. Department of Labor in 2019 and was given the code 49-2094.00. In 2022 the occupation was migrated to the code 17-3024.00 and titled "Electro-Mechanical and Mechatronics Technologists and Technicians". Several organizations offer certifications in the mechatronics occupation that we list here. The major challenge that faces mechatronics education is the decline in the job market that is projected to stand at -2 % over the next decade for holders of bachelor’s or lower degrees. This is attributed to the post-pandemic remote work trend and the hard-hit manufacturing industry during the pandemic. This decline is coupled with an aggressive growth in the job market for holders of graduate degrees (standing at over 11% growth) due to the growing demand in research and innovation and engineering training. 

Recently, drones have become a useful tool in training and practicing the core of industry 4.0 for applications ranging from machine diagnostics to surveillance and detection of air leaks. In this work, train-the-trainer workshops were organized to train primarily STEM educators from Two-year higher education and secondary education institutions on Smart Manufacturing (SM) technologies. The hands-on activities during these workshops included assembling and coding drones. Four workshops were held between 2019 and 2021 with 114 participants from 20 states across the United States. The workshops included research, industry speakers, and hands-on activities with assembling and coding drones with Arduino, Python, or Blockly. The effectiveness of using drones for training in SM workshops was evaluated using retrospective surveys. Most participants reported that their knowledge of coding and smart manufacturing increased and that the knowledge gained from the workshops is applicable to their work. In addition, using statistical tools, 7,182 students ± 1,903 were exposed to the smart manufacturing concepts using drones six months after the workshops with a confidence level of 90%. 

In this work, we analyze the lessons learned from the CoVid-19 pandemic and the prospects of the science education that evolved as a result of the pandemic. The two primary shortcomings that arose during the pandemic include: the poor presence of cross-boundary and interdisciplinary research as evidenced by the urgency in establishing cross-boundary research groups in the early days of the pandemic, and the lack of understanding of the scientific method in the general public as evidenced, for example, by the worldwide Hydroxychloroquine events of 2020. An effective approach to solving these shortcomings is increasing innovative research at the two-year tertiary education level. The focus of continuing technical education will shift towards technologies that provide self-sufficiency, such as artificial intelligence, intelligent robotics, augmented reality, digital twins, and additive manufacturing. These features likely constitute the cornerstone of the upcoming science education paradigm, which we denominate “STEM 3.0”. 

This paper reports on how institutions collaborating on Additive Manufacturing (AM) and Smart Manufacturing (SM) have been able to adapt to the COVID-19 pandemic and be able to modify their planned activities in 2020 in an effort to continue delivering quality training and education to educators across the country. The pandemic made it impossible to offer the usual on-ground workshops to STEM educators and industrial practitioners. As a workaround, the project teams offered instructional delivery via Zoom and Microsoft Teams while also providing distance learning tools online. The best practices of the delivery and pros/cons of the operations will be presented with the feedback received from the participants. 

Today, the current trends of manufacturing are towards the adaptation and implementation of smart manufacturing, which is a new initiative to turn the traditional factories into profitable innovation facilities. However, the concept and technologies are still in a state of infancy, since many manufacturers around the world are not fully knowledgeable about the benefits of smart manufacturing compared to their current practices. This article reviews several aspects of smart manufacturing and introduces its advantages in terms of energy-saving and production efficiency. This article also points out that some areas need further research so that smart manufacturing can be shaped better. 

In this paper we present recent advances, current and future market trends in industrial robotics. Artificial Intelligence has evolved as the main feature to characterize Industry 4.0, Next-generation robotics utilize this feature to perform tasks collaboratively, as opposed to the currently deployed industrial robots, which were designed mainly for automation, isolated in cages, and highly-controlled environments. Current data show that China takes the lead in the industrial robotics market with 48% of the top-ten market in 2019. The electronics sector took the lead in robot-deployment in East Asia, and is continuously increasing in deploying industrial robotics in other parts of the world. Studies on the challenges associated with this technology, show that the main concern is the lack of trained labor to handle the technologies in next generation industrial robotics. 

In this project, the following products were produced as a result of this project: Smart Manufacturing training workshops Online Educational modules on Smart Manufacturing Industrial speaker short talks that present the State-of-the-art Industrial Applications Peer-reviewed articles were produced. High school and Middle School visits In the hands-on training, we demonstrated the use of code-programmed drones in technical education and Smart Manufacturing (SM). Unmanned aerial and ground vehicle technologies are increasingly finding applications in industrial settings. Training on SM is achieved by using coded drones, with educational modules and a database of technologies and their applications. 

Over the years, the ability of production plants to operate in a faster and more efficient manner has consistently grown and expanded as technology has further developed. This growth is a result of the constantly steady advances of industrial robotics. In 2016, for the first time, the electronics industry exceeded the automotive industry in demand for industrial robotics in the Asian markets of China, Japan, and Korea. Worldwide, the electronics sector’s share of the robotics market rose steadily to 32% in 2017, almost equal to the automotive sector (33%) [1]. This change indicates that sectors that have not been historical markets for industrial robotics, are now adapting to this robotics revolution. Improvements in Industrial robotics for Energy Efficiency [2]: 1) Improvements in Hardware Selection: such as an improved selection of the robotic systems, new mechanical components that reduce energy use, being able to be more compact, and finding different usages of a robot’s movement. 2) Improvements in Software 3) Improvements in both hardware and Software.