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Artificial Intelligence: Prospect in Mechanical Engineering Field—A Review

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Data Science and Intelligent Applications

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 52))

Abstract

With the continuous progress of science and technology, the mechanical field is also constantly upgrading from traditional mechanical engineering to the mechatronics engineering and artificial intelligence (AI) is one of them. AI deals with a computer program that possesses own decision-making capability to solve a problem of interest with imitates the intelligent behavior of expertise which finally turns into higher productivity with better quality output. From the inception, various developments have been done on AI system which nowadays widely implemented in the mechanical and/or manufacturing industries with broaden area of application such as pattern recognition, automation, computer vision, virtual reality, diagnosis, image processing, nonlinear control, robotics, automated reasoning, data mining and process control systems. In this study, review attempt has been made for AI technologies used in various mechanical fields such as thermal, manufacturing, design, quality control and various connected fields of mechanical engineering. The study shows the blend mixed of AI technologies like deep convolutional neural network (DCNN), convolutional neural network (CNN), artificial neural network (ANN), fuzzy logic and many more to control the process parameters, process planning, machining, quality control and optimization in the mechanical era for smooth development of product or system. With the implementation of AI in mechanical engineering applications, the error, rejection of components can be minimized or eliminated and system optimization can be achieved effectively turn in economical better quality products.

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Authors and Affiliations

  1. Chandubhai S Patel Institute of Technology, Charotar University of Science and Technology, Changa, 388421, India

    Amit R. Patel

  2. Mechanical Engineering Department, Gandhinagar Institute of Technology, Gandhinagar, 382721, India

    Kashyap K. Ramaiya & Chandrakant V. Bhatia

  3. Gandhinagar Institute of Technology, Gandhinagar, 382721, India

    Hetalkumar N. Shah

  4. Mechatronics Engineering Department, G H Patel College of Engineering and Technology, Vallabh Vidyanagar, 388120, India

    Sanket N. Bhavsar

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  1. Amit R. Patel
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  2. Kashyap K. Ramaiya
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  3. Chandrakant V. Bhatia
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  5. Sanket N. Bhavsar
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Correspondence to Amit R. Patel .

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Editors and Affiliations

  1. Faculty of Engineering, Symbiosis Institute of Technology, Pune, India

    Ketan Kotecha

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Italy

    Vincenzo Piuri

  3. Gandhinagar Institute of Technology, Gandhinagar, Gujarat, India

    Hetalkumar N. Shah

  4. Department of Computer Engineering, Gandhinagar Institute of Technology, Gandhinagar, Gujarat, India

    Rajan Patel

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Patel, A.R., Ramaiya, K.K., Bhatia, C.V., Shah, H.N., Bhavsar, S.N. (2021). Artificial Intelligence: Prospect in Mechanical Engineering Field—A Review. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_31

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