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Geometrical Enhancements Based On Datadriven Design Decisions 1st Edition Sourabh Mandol Mohit Hemanth Kumar Akarsh Verma V K Singh

  • SKU: BELL-236871260
Geometrical Enhancements Based On Datadriven Design Decisions 1st Edition Sourabh Mandol Mohit Hemanth Kumar Akarsh Verma V K Singh
$ 35.00 $ 45.00 (-22%)

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Geometrical Enhancements Based On Datadriven Design Decisions 1st Edition Sourabh Mandol Mohit Hemanth Kumar Akarsh Verma V K Singh instant download after payment.

Publisher: CRC Press -Taylor & Francis Group
File Extension: EPUB
File size: 12.96 MB
Author: Sourabh Mandol & Mohit Hemanth Kumar & Akarsh Verma & V. K. Singh
ISBN: 9781040350867, 9781041028253, 9781032655000, 9781003621102, 1040350860, 1041028253, 1032655003, 1003621104
Language: English
Year: 2025
Edition: 1st Edition

Product desciption

Geometrical Enhancements Based On Datadriven Design Decisions 1st Edition Sourabh Mandol Mohit Hemanth Kumar Akarsh Verma V K Singh by Sourabh Mandol & Mohit Hemanth Kumar & Akarsh Verma & V. K. Singh 9781040350867, 9781041028253, 9781032655000, 9781003621102, 1040350860, 1041028253, 1032655003, 1003621104 instant download after payment.

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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