Advances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering
Progress in Application of Intelligent Methods and Systems in Production Engineering
Published on 20. April 2022
Book
Paperback/Softback
XX, 769 pages
978-3-030-90531-6 (ISBN)
Description
This book forms an excellent basis for the development of intelligent manufacturing system for Industry 4.0, digital and distributed manufacturing, and factories for future. This book of new developments and advancement in intelligent control and optimization system for production engineering serves as a good companion to scholars, manufacturing companies, and RTO to improve the efficiency of production systems.
More details
Series
Edition
1st ed. 2022
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
77 s/w Abbildungen, 294 farbige Abbildungen
XX, 769 p. 371 illus., 294 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 43 mm
Weight
1177 gr
ISBN-13
978-3-030-90531-6 (9783030905316)
DOI
10.1007/978-3-030-90532-3
Schweitzer Classification
Other editions
Additional editions
Andre Batako | Anna Burduk | Kanisius Karyono
Advances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering
Progress in Application of Intelligent Methods and Systems in Production Engineering
E-Book
04/2022
Springer
€181.89
Available for download
Content
Total Quality Management with safety conformity: Shaping of working environment by use of the ISO 45001 guidelines.- ANN-FPA Based Modell ng and Optimization of Drilling Burrs Using RSM and GA.- The Complexity of Data-Driven in Engineer-To-Order Enterprise Supply-Chains.- Human-Centred Approach in Industry 4.0: Lighting Comfort in the Workplace.- Advanced risk model for the safety evaluation of food transport logistics.- Advanced Bayesian model to quantify the adequacy of organization for human reliability: A maritime case.- Flexible manufacturing system with uncertainty management using fuzzy logic for machine shop.- Adaptation of methods to improve the e?ciency of business processes using the BPRPM method as a chance to gain a competitive advantage.