Designing of an effective e-learning website using inter-valued fuzzy hybrid MCDM concept: A pedagogical approach

Al-Gerafi, Mohammed Abdulwahab; Goswami, Shankha Shubhra; Khan, Mohammad Amir; Naveed, Quadri Noorulhasan; Lasisi, Ayodele; AlMohimeed, Abdulaziz; Elaraby, Ahmed

doi:10.1016/j.aej.2024.04.012

Cited by 8 publications

(1 citation statement)

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“…iii. Improved performance and efficiency − AI-driven design optimization enables engineers to fine-tune mechanical systems for optimal performance and efficiency [24]. This translates to tangible benefits such as improved fuel efficiency in automotive applications or increased energy conversion rates in turbine systems.…”

Section: Practical Implications Of the Present Researchmentioning

confidence: 99%

Rise of Intelligent Machines: Influence of Artificial Intelligence on Mechanical Engineering Innovation

Mondal,

Goswami

2024

Spec. Eng. Man. Sci.

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The integration of artificial intelligence (AI) into mechanical engineering has precipitated a profound transformation in the way engineers conceive, design, and execute projects. This paper explores the multifaceted impact of AI on mechanical engineering innovation, elucidating the myriad ways in which intelligent machines are revolutionizing traditional practices and catalyzing unprecedented advancements. In the realm of design, AI algorithms are revolutionizing the conceptualization and optimization processes. By leveraging machine learning and optimization techniques, engineers can explore vast design spaces with unparalleled efficiency, uncovering innovative solutions that might otherwise remain elusive. These AI-driven design tools not only expedite the development cycle but also enable the creation of products and systems with enhanced performance characteristics, such as improved energy efficiency, structural integrity, and functional versatility. Moreover, AI's influence extends beyond the design phase and permeates the entire manufacturing ecosystem. AI-driven automation is reshaping production lines, enabling agile and adaptive manufacturing processes that respond dynamically to changing demands and conditions. Through the integration of sensors, actuators, and AI-powered control systems, factories are becoming increasingly intelligent and autonomous, optimizing resource utilization, minimizing waste, and maximizing throughput.

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Section: Practical Implications Of the Present Researchmentioning

confidence: 99%