Sourabh Mandol – författare

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 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.