The unconventional machining is an essential role in metal forming process. The dimensional accuracy and super finish are the main features of modern machining methods. Electric discharge machining is a competent proc...
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Robotics program at many Colleges has continued to become more and more popular. However, the students of the Bachelor of technology (***.) program of robotics in the mechanicalengineeringtechnology (MET) are facing...
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It is very strong and solid to work with Pterocarpus marsupium and Cochlospermumgossypium, two tropical hardwoods. In this study, these two types of wood were used as support materials to make a polyester composite. I...
The coatings are utilised on any materials as a protective layer. The coating characteristics are dependent on their composition, phase structure and surface morphology. In this current investigation, the coated speci...
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This paper investigates the vibration and acoustic characteristics of an aluminium-silicon carbide (Al-SiC) simply supported composite plate under thermal loads. The vibrational response induced by the temperature ris...
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The borohydride reduced binary (Ni–B), ternary (Ni–B–W, Ni–B–Mo) and quaternary (Ni–B–Mo) alloy coatings are deposited by chemical deposition method. The same coatings are used to study the variation in corrosi...
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Additive manufacturing (AM) is a technological advancement gaining colossal popularity due to its advantages and simplified fabrication. AM facilitates the manufacturing of complex, light, and strong products from dig...
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Additive manufacturing (AM) is a technological advancement gaining colossal popularity due to its advantages and simplified fabrication. AM facilitates the manufacturing of complex, light, and strong products from digitized designs. With recent advancements, AM can bring digital flexibility and improved efficiency to industrial operations. Despite the various advantages, there is continuous variation in the qualities of AM products, which remains the main challenge in the wide application of AM. The performance of printed parts is directly influenced by processing parameters, and adjusting the parameters in the AM process can be quite challenging. The barrier can be minimized by proper monitoring of the AM process and precise measurement of AM materials and components, which is difficult to achieve through analytical and numerical models. Current research demonstrates machine learning (ML) and its techniques as a novel way to reduce costs. It also helps achieve optimal process design and part quality using the fundamentals of the AM process. ML is a subcategory of artificial intelligence (AI) that enables systems to learn and improve from measured data and past experiences. The present paper is focused on presenting a broad understanding of the current applications of ML in AM and thus provides a solid background for practitioners and researchers to apply ML in AM. Very few earlier reviews were presented before, but their studies mostly focus on artificial neural network technology and other irrelevant papers. In addition, most papers were published in 2021 and 2022 and were not discussed in earlier reviews. This state-of-the-art review is based on the latest database collected from Web of Science (WoS), Publons, Scopus, and Google Scholar using machine learning and additive manufacturing as the keywords. Extensive information collected on the possible applications of ML in AM shows that ML can be effectively applied to improve AM part quality and process reliabilit
In this work, glass fiber and basalt composites modified with hybrid nanofillers, such as silicon dioxide (SiO2) nanoparticles and multi-walled carbon nanotubes (MWCNTs), are examined for their shape and mechanical ch...
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The depletion in non-renewable energy sources and a fast-growing population in Bangladesh are exacerbating the already existing energy scarcity,highlighting the need for an efficient and robust renewable-energy supply...
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The depletion in non-renewable energy sources and a fast-growing population in Bangladesh are exacerbating the already existing energy scarcity,highlighting the need for an efficient and robust renewable-energy supply *** primary goal of this study is to evaluate the most optimized renewable-energy supply chain based on natural resource availability and government policies of *** the present study,four renewable energy resources,including solar,biomass,wind and hydropower,are studied and nine subcriteria are defined under four primary criteria for each supply *** for Order Preference by Similarity to Ideal Solution(TOPSIS)and VIseKriterijumska Optimizacija I Kompromisno Resenje(VIKOR)are multicriteria decision-making approaches used in this study to compare and choose the best renewable-energy supply *** relative significance of four supply-chain criteria for primary renewable energy in this study,namely energy procurement,production,operations and maintenance costs,and social and environmental impact,is gathered via a *** results of this research,supported by a comprehensive sensitivity analysis,indicate that hydropower is the best renewable-energy supply chain,followed by wind as a compromise solution,biomass and *** study also demonstrates that no energy source can satisfy all supply-chain criteria alone;each resource is better for a specific criterion-solar is better for procurement,hydropower is significant for production and wind is remarkable for operations and social ***,to maximize output,renewable energy sources must be *** Bangladesh’s perspective,for the first time,by using TOPSIS and VIKOR together,this study offers significant insights to establish an efficient and sustainable renewable-energy supply chain for practitioners,academics and policymakers.
When two or more components with various qualities are combined, a composite material is created. Although composites have already demonstrated that they are effective weight-saving materials, cutting their price is n...
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