Advanced processing of 3D printed biocomposite materials using artificial intelligence

Verma, Deepak; Dong, Yu; Sharma, Mohit; Chaudhary, Arun Kumar

doi:10.1080/10426914.2021.1945090

Cited by 25 publications

(8 citation statements)

References 120 publications

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“…Fuzzy logic and artificial intelligence optimization techniques and approaches are extensively applied [18,20,21,28,29]. These fuzzy models have been enhanced and adjusted here with the assistance of specialists.…”

Section: Simulation Resultsmentioning

confidence: 99%

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A Study of Load Demand Forecasting Models in Electricity using Artificial Neural Networks and Fuzzy Logic Model

2022

IJE

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Since load time series are very changeable, demand forecasting of the short-term load is challenging based on hourly, daily, weekly, and monthly load forecast demand. As a result, the Turkish Electricity Transmission Company (TEA) load forecasting is proposed in this paper using artificial neural networks (ANN) and fuzzy logic (FL). Load forecasting enables utilities to purchase and generate electricity, load shift, and build infrastructure. A load forecast was classified into three sorts (hourly, weekly and monthly). Over time, forecasting power loads with artificial neural networks and fuzzy logic reveals a massive decrease in ANN and a progressive increase in FL from 24 to 168 hours. As illustrated, fuzzy logic and artificial neural networks outperform regression algorithms. This study has the highest growth and means absolute percentage error (MAPE) rates compared to FL and ANN. Although regression has the highest prediction growth rate, it is less precise than FL and ANN due to their lower MAPE percentage. Artificial Neural Networks and Fuzzy Logic are emerging technologies capable of forecasting and mitigating demand volatility. Future research can forecast various Turkish states using the same approach.

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Section: Simulation Resultsmentioning

confidence: 99%

“…The figures demonstrate that the more recent fuzzy logic, ANN, and FNN algorithms surpass the previous MLR strategy. We have rephrased this for clarity, but the relationship between preceding one-week and two-day time-lag loading is likely more substantial [21,29,31,33,[37][38][39].…”

Section: Simulation Resultsmentioning

confidence: 99%

A Study of Load Demand Forecasting Models in Electricity using Artificial Neural Networks and Fuzzy Logic Model

2022

IJE

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“…Advancements in composite materials have replaced metals in various applications due to their lightweight characteristics. [ 109–111 ]…”

Section: Smart Materials For 4d Printingmentioning

confidence: 99%

Additive manufacturing of smart polymeric composites: Literature review and future perspectives

2022

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The latest developments in smart systems for improved human lives with advanced biomedical devices have evolved out of multi‐disciplinary scientific studies, including medicine, biology, material sciences, design, manufacturing, artificial intelligence, microelectronics, and so forth. The growth of such intelligent systems is primarily possible with innovative materials, which demonstrate the response to various external stimuli like temperature, heat, moisture, light, electromagnetic field, and chemical alteration. Such materials have been recently fabricated using different additive manufacturing techniques to devise personalized unique, complex, and novel structures that can adjust to external conditions over time and are specifically attributed to 4D printing. Novel materials that can further improve such systems continued to be explored and employed. This review paper investigates the additive manufacturing of functional polymer nanocomposites, which offer compliant structures with flexible manufacturing processes with high strength, low cost, and long‐term stability. This study aims to deliver a comprehensive and deep understanding of the latest developments in materials, design, manufacturing, fundamental mechanisms involved, and future possibilities in this area of research.

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“…Three-dimensional (3D) printing is one of the most promising technologies to realise minimised or zero waste of production materials. It allows the potential to utilise state-of-the-art environmentally friendly materials, such as biodegradable, biocompatible, and natural polymers, and to produce sophisticated structures and architectural models with a lower cost and higher efficiency [18]. As a supplementary technology, 3D printing's function and effectiveness should rely on the degree of integration with computational modelling or algorithmic design, so that a good combination and coordination of technologies, such as BIM and AI, will be critical to actualise its potential [19,20].…”

Section: Minimising Waste and Negative Environmental Impactsmentioning

confidence: 99%

Technology Innovation for Sustainability in the Building Construction Industry: An Analysis of Patents from the Yangtze River Delta, China

Wang

Zhang

2022

Buildings

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Advances in technology provides the potential to innovate sustainability in the building construction industry. Drawing on the literature and expert reviews, this research discloses the potential of 14 specific technologies in waste minimisation, energy saving, and efficiency improvement for sustainable building construction and develops a conceptual framework engaging the building life cycle (the planning, construction, use and operation, and demolition phases) and the actors for assessing technological innovation at a local level. This framework is used to identify how technologies were innovated for sustainable building construction through the selected 3017 patent invention applications from the Yangtze River Delta (YRD), one of the fastest urbanising areas and the largest market for the building industry in China. Findings unveiled that innovation is uneven amongst the 14 technologies and the degree of mixing was relatively low in the YRD. The contribution of the technological innovation to sustainability is mainly actualised through efficiency improvements in building construction (2265) and through directly reducing waste (1094) and energy consumption (642). Some general-purpose technologies (e.g., blockchain, cloud computing), which assume to fundamentally innovate the industry, are mostly absent with less than 10 records each, leaving the potential for future adaptive technological innovation. Furthermore, state-owned enterprises as the main sources of patent inventions amongst applicants in the YRD may suggest the dissimilar path of China towards technology innovation compared to its Anglo-American counterparts.

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Advanced processing of 3D printed biocomposite materials using artificial intelligence

Cited by 25 publications

References 120 publications

A Study of Load Demand Forecasting Models in Electricity using Artificial Neural Networks and Fuzzy Logic Model

A Study of Load Demand Forecasting Models in Electricity using Artificial Neural Networks and Fuzzy Logic Model

Additive manufacturing of smart polymeric composites: Literature review and future perspectives

Technology Innovation for Sustainability in the Building Construction Industry: An Analysis of Patents from the Yangtze River Delta, China

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