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9781032655000: Geometrical Enhancements Based on Data-Driven Design Decisions

Sinopsis

The text presents various design and modelling solutions for effective decision-making that are grounded on the basics of data analytics. It further discusses important topics such as sustainable design and data-driven design synthesis, product analytics and its role in sustainable development, and descriptive models for the geometrical evaluation of product features.

This book:

  • Familiarize the readers with the numerous decision protocols that can be utilized for deducing geometrical qualities using data-driven design analysis
  • Offers a more comprehensive approach to multidisciplinary engineering applications using data-driven modelling and analysis
  • Discusses multi-objective optimization for product design and development through data-driven decision-making
  • Explains information processing and analysis through data visualization and data mining
  • Covers artificial intelligence and machine learning-based decision models and their effective utilization across interdisciplinary applications

It is primarily written for senior undergraduate, graduate students, and academic researchers in fields including industrial engineering, production engineering, manufacturing engineering, mechanical engineering, and aerospace engineering.

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Acerca del autor

Sourabh Mandol is a skilled data analyst and researcher with a PhD. in Product Design & Development from IIT Kharagpur, India. Specializing in data-driven modeling and machine learning applications in engineering, Dr. Mandol has extensive expertise in applying advanced analytical techniques, including statistical analysis, soft computing, and multidisciplinary design optimization. His research focuses on developing innovative methodologies for complex engineering systems, particularly in the areas of eco-design, sustainability, and hybrid electric vehicle optimization. Currently serving as an Assistant Professor, Dr. Mandol brings his industry-relevant expertise to the classroom, teaching courses in data-driven decision making, analytics, and product design. He has a proven track record of implementing machine learning algorithms for quality control and process optimization in manufacturing, as well as developing digital twin concepts for engineering applications. Dr. Mandol's work has been published in reputable journals and presented at international conferences, showcasing his commitment to driving innovation through the integration of data science and engineering principles.

Mohit Hemanth Kumar is an accomplished academic currently serving as Assistant Professor and Associate Director of the AU IPR Cell at Alliance University, Bengaluru. With 5 years of teaching and research experience, he earned his PhD from the National Institute of Technology, Tiruchirappalli, where he specialized in the development and investigation of nano fillers reinforced hybrid polymer composites. His research interests span several critical areas in mechanical engineering and materials science, focusing on inorganic fillers reinforced hybrid polymer composites, nanocomposites, waste-to-innovative products, industrial product design and development, and manufacturing technology. As an educator, he has developed and taught courses in mechanical engineering fundamentals, product development and design, additive manufacturing, smart manufacturing, and materials technology. Dr. Kumar's research contributions have made a significant impact in his field, garnering over 1,400 citations and achieving an h-index of 19. His innovative work has led to 24 granted patents and 21 granted industrial designs, with 5 more patents awaiting approval. He has published extensively, with 43 articles in reputed international journals, authored 27 book chapters, and served as editor for 6 books. As a registered Patent Agent (IN/PA 5341), Dr. Kumar actively contributes to intellectual property development and protection. He maintains strong professional affiliations as a Life Member of several prestigious organizations, including the Indian Society of Technical Education, Institute of Engineer's India, Society for Failure Analysis, International Association of Engineers, and the Powder Metallurgy Association of India. Through his international research collaborations and contributions to curriculum development, Dr. Kumar continues to advance both the academic and practical aspects of mechanical engineering and materials science.

Akarsh Verma is currently an Assistant Professor at the University of Petroleum and Energy Studies (UPES), India. He obtained PhD. in Mechanical Engineering from the Indian Institute of Technology (IIT) Roorkee, India; and did his postdoctoral research work at the Brigham Young University (USA) and was as a JSPS International Research Fellow at the Osaka University (Japan). He serves the research community by acting as a reviewer for various International journals and has reviewed several research articles. In addition, he has published various research articles in high-quality international peer-reviewed journals, many books and book chapters, and also presented many research papers at various international/national conferences. His areas of interests are computational mechanics, computational chemistry, quantum mechanics, molecular dynamics, nanocomposites, etc. He has various international fellowships/awards (Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowship, Japan; J. William Fulbright Doctoral Research Fellowship, USA; Early Career Training Grant award for Early Career Researchers from the Communications Materials (Nature Journal); Researcher Development Grant from the Royal Society of Chemistry (RSC), UK; Excellence in Doctoral Research Award for the Best Ph.D. thesis research work at IIT Roorkee, India; Doctoral Research Scholarship by the Department of Science and Technology (DST), Government of India and Ministry of Human Resource Development (MHRD), Government of India; PG Scholarship by the All India Council for Technical Education (AICTE), India; Young Researcher Award ICMR2022, Japan) to his credit. He has also been recognized by Stanford University’s list of the world’s Top 2% of the Most-Cited Scientists in Single Year Citation Impact (2023, 2022, 2021 and 2020).

V. K. Singh is currently a professor in the Department of Mechanical Engineering at Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, India. Prof. Singh has over 20 years of teaching and research experience. He has contributed to over 100 papers in various international and national journals and conferences. He has also handled several research projects and also guided a number of M.Tech and Ph.D. theses. His current research interests are in the areas of polymers, composite materials, and fracture mechanics. He is also a member of several engineering societies and serves the research community by reviewing research papers. He has also organized over 10 international and national conferences. He has also served in administrative-level positions at the university and state level.

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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Sourabh Mandol is a skilled data analyst and researcher with a PhD. in Product Design &amp Development from IIT Kharagpur, India. Specializing in data-driven modeling and machine learning applications in engineering, Dr. Mandol has extensive expertise i. Nº de ref. del artículo: 2019746147

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Mandol, Sourabh (EDT); Kumar, Mohit Hemanth (EDT); Verma, Akarsh (EDT); Singh, V. K. (EDT)
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Mandol, Sourabh (EDT); Kumar, Mohit Hemanth (EDT); Verma, Akarsh (EDT); Singh, V. K. (EDT)
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Hardcover. Condición: new. Hardcover. The text presents various design and modelling solutions for effective decision-making that are grounded on the basics of data analytics. It further discusses important topics such as sustainable design and data-driven design synthesis, product analytics and its role in sustainable development, and descriptive models for the geometrical evaluation of product features.This book:Familiarize the readers with the numerous decision protocols that can be utilized for deducing geometrical qualities using data-driven design analysisOffers a more comprehensive approach to multidisciplinary engineering applications using data-driven modelling and analysisDiscusses multi-objective optimization for product design and development through data-driven decision-makingExplains information processing and analysis through data visualization and data miningCovers artificial intelligence and machine learning-based decision models and their effective utilization across interdisciplinary applicationsIt is primarily written for senior undergraduate, graduate students, and academic researchers in fields including industrial engineering, production engineering, manufacturing engineering, mechanical engineering, and aerospace engineering. The text presents various design and modelling solutions for effective decision-making that are grounded on the basics of data analytics. It also discusses topics such as sustainable design and data-driven design synthesis, product analytics and its role in sustainable development, amongst many others. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9781032655000

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