Name: Data Analytics for Process Engineers. Prediction, Control and Optimization
Price: 47.42 EUR
Availability: InStock
Author: Daniela Galatro;Stephen Dawe
ISBN: 9783031468681

portada Data Analytics for Process Engineers. Prediction, Control and Optimization

Data Analytics for Process Engineers. Prediction, Control and Optimization

Formato

Libro Físico

Editorial

Springer International Publishing AG

Autor

Daniela Galatro;Stephen Dawe

Colección

Synthesis Lectures on Mechanical Engineering

Año

2024

N° páginas

145

Encuadernación

Tapa Blanda

Dimensiones

24.00 x 16.80 cm

ISBN13

9783031468681

Data Analytics for Process Engineers. Prediction, Control and Optimization

Daniela Galatro;Stephen Dawe (Autor) · Springer International Publishing AG · Tapa Blanda

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Reseña del libro "Data Analytics for Process Engineers. Prediction, Control and Optimization"

This book provides an industry-oriented data analytics approach for process engineers, including data acquisition methods and sources, exploratory data analysis and sensitivity analysis, data-based modelling for prediction, data-based modelling for monitoring and control, and data-based optimization of processes.

This book provides an industry-oriented data analytics approach for process engineers, including data acquisition methods and sources, exploratory data analysis and sensitivity analysis, data-based modelling for prediction, data-based modelling for monitoring and control, and data-based optimization of processes. While many of the current data analytics books target business-related problems, the rationale for this book is a specific need to understand and select applicable data analytics approaches pragmatically to analyze process engineeringrelated problems; this tailored solution for engineers gets amalgamated with governing equations, and in several cases, with the physical understanding of the phenomenon being analyzed. We also consider this book strategically conceived to help map Education 4.0 with Industry 4.0 since it can support undergraduate and graduate students to gain valuable and applicable data analytics stills that can be further used in their workplace. Moreover, itcan be used as a reference book for professionals, a quick reference to data analytics tools that can facilitate and/or optimize their process engineering tasks.