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In this work we evaluate the state of the semiconductor manufacturing industry and its challenges and trends. Future trends in the industry are analyzed from three perspectives: the evolution of Industry 4.0, the advances in semiconductor materials, and the impact of the Covid-19 Pandemic. The semiconductor manufacturing industry witnessed an acute decline in the United States and other regions in the two decades prior to the CoVid-19 pandemic. The decline was only uncovered after the chip shortage of 2021 that resulted from the severe supply chain disruption. Trends in the industry were analyzed from three perspectives: Industry 4.0, advances in materials, and the Post-pandemic era. As a result of the evolution of the fourth generation of industry (Industry 4.0), trends in semiconductor manufacturing include robotization, which caused the industry to become the largest market for industrial robotics since 2020, and an all-time peak globalization. The semiconductor industry is a very globalized industry with corporates from different parts of the world taking part in the production of the final product. Although some materials such as carbon and Gallium Nitride show promising trends to replace silicon as the material of choice. It will likely not be before two or three decades when a semiconductor material will be able to replace silicon. Challenges for the industry include the shortage of the trained-workforce, and the added inter-country restrictions that may hinder the globalization of the industry. 

In this paper, we present the results of the evaluation conducted for six train-the-trainer workshops on intelligent industrial robotics that were organized over three years from 2021 to 2023. The workshops targeted STEM faculty of community and technical colleges and high schools. The workshops included factory tours, industry speakers, and hands-on activities on industrial robots and vision system programming. Evaluation of the effectiveness of the workshops was measured using surveys at the end of the workshops, as well as pre-and post-intervention assessments. A six-month follow-up survey was conducted to assess the impact of the workshops on students. Results show that most participants reported that their knowledge of intelligent industrial robotics increased and that the knowledge gained from the workshops is applicable to their work. In addition to that, statistical calculations show that 3,572 ± 1,286  students were impacted by the workshops six months after the workshop completion with a confidence level of 90%. 

Abstract 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. 

In this work we investigate the effectiveness of two train-the-trainer workshops on intelligent industrial robotics. The two workshops, which took place in summer 2021 in Tennessee and Alabama, were the first of a series of six workshops. A total of 32 persons applied to the two summer workshops from 10 states, of whom 15 attended and successfully completed the workshops. Evaluation results show that the participants’ knowledge on industrial robotics significantly improved after the workshops, and the vast majority indicated that the training will be used in their home institutions. The major challenge faced during the workshops was the spread of the delta variant of CoVid-19 at the time the workshops were scheduled to take place, and the wide diversity of the educational background of participants. 

In this work we investigate the electrical properties of phospholipid bilayer membranes (LBMs) formed from phosphatidylserine by analyzing two experimental setups. The Electrochemical Impedance Spectra (EIS) of phosphatidylserine show that a lipid bilayer membrane formed from this phospholipid has an average specific electrical resistance of 3.466 k Ω.cm 2 and an average capacitance of 0.385 µF/cm 2 . Some of the major factors that affect the LBM resistance include electroporation, the method of deposition, and the surface tension in microchannels for supported LBMs. Therefore, wide apertures remain the most accurate method for supporting LBMs. 

Contact angle measurement is a commonly used technique to measure the wettability of a solid surface The technique is highly susceptible to error when conducted by a human operator In this project, the experiment is robotized to increase accuracy, in which the Denso COBOTTA robot is used to dispense pure liquid drops onto a variety of surfaces in order to measure the contact angle for each surface. The experiment is currently being expanded for robotized deposition of lipid bilayer membranes. 

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. 

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. 

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.