Dissertation
Digital technologies for mechanical engineering training
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Digital technologies for mechanical engineering trainingWith the introduction of new digital technologies in engineering, digital skills have become an extremely important skill for engineering students of all disciplines. The use of digital technology by mechanical engineers is acknowledged as essential for boosting employee and industry efficiency (Koretsky & Magana, 2019). Mechanical Engineering practical are based on using conventional methods and paper-based technology. However, Digital technologies are making their way into mechanical engineering education. They offer opportunities to modernise many practises and eliminate many inefficiencies that have dogged an inherently complex and dangerous training process over the years in terms of skill acquisition for the industry (Bacotti et al., 2022): (W. Si et al., 2021). According to the literature, the following digital technologies for engineering training have been identified: big data, Internet of Things (IoT), sensor-based technology, additive manufacturing (AM), augmented reality (AR), and mobile technology (Rouf et al., 2022; Fu et al., 2022) Wu & Ghariban, (2015), a digital laboratory engineering training must have computer software tools such as Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD), 3D models with computer-aided design (CAD) software etc. These digital technologies were combined to improve the training of mechanical engineering students (Qureshi et al., 2021). Big data refers to a significant volume of data acquired by software tools from a variety of sources with a diverse growth rate (Moral-Muñoz et al., 2020). These data originate from a variety of sources, including the Internet, social media platforms, and phone records, among others. Furthermore, big data does not gather and analyze data using random analysis, which is derived from the sample survey approach. Massive data, fast processing speed, diversity, low value density, and authenticity are the five characteristics of big data (Z. Yang & Ge, 2022). Massive data may be mined and analyzed using big data technologies. Furthermore, new technologies such as IoT, and AI are enhancing the value of Big Data. Also, the value of Big Data is enhanced by emerging technologies such as additive manufacturing, and AR, which gives techniques for storing, computing, processing, analyzing, and visualizing data from mechanical engineering projects (Qi et al., 2021). According to Mantravadi, (2022), the Internet of Things has the potential to deliver several benefits to engineering training by enabling a higher degree of communication and information exchange across the project and product lifecycle, from project inception to design, manufacturing, handover, and final disposal. Another big data technology is augmented reality (AR), which is a state- of-the-art technology that allows users to superimpose information on the real world (Zhan et al., 2020). Download 2.1 Mb. Share with your friends:
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