1.

Record Nr.

UNINA9910682553603321

Autore

Chen Tin-Chih Toly

Titolo

Explainable Artificial Intelligence (XAI) in Manufacturing : Methodology, Tools, and Applications / / by Tin-Chih Toly Chen

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

9783031279614

9783031279607

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (110 pages) : illustrations

Collana

SpringerBriefs in Applied Sciences and Technology, , 2191-5318

Disciplina

006.3

Soggetti

Industrial engineering

Production engineering

Production management

Artificial intelligence

Industrial and Production Engineering

Production

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Chapter 1: Explainable Artificial Intelligence (XAI) in Manufacturing -- Chapter 2: Applications of XAI for Forecasting in the Manufacturing Domain -- Chapter 3: Applications of XAI for Decision Making in the Manufacturing Domain -- Chapter 4: Applications of XAI to Job Sequencing and Scheduling in Manufacturing.

Sommario/riassunto

This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. It covers the various methods, tools, and technologies that are being used to make AI more understandable and communicable for factory workers. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI. This book addresses this need by providing a systematic review of the latest research and advancements in XAI specifically tailored for the manufacturing industry. The book



includes real-world case studies and examples to illustrate the practical applications of XAI in manufacturing. It is a valuable resource for researchers, engineers, and practitioners working in the field of AI and manufacturing.