Artificial Neural Network-Based Springback Prediction in Sheet Metal Bending for Industry 4.0 Applications

Weidher Possidonio Cardoso, William Regone and Rodrigo Furlan de Assis ()
Additional contact information
Weidher Possidonio Cardoso: Centro Universit’ario das Faculdades Associadas de Ensino – UNIFAE
William Regone: Centro Universit’ario das Faculdades Associadas de Ensino – UNIFAE
Rodrigo Furlan de Assis: Ecole de Technologie Supérieure, Department of Systems Engineering

A chapter in Technology Management for Intelligent, Open and Responsible Organizations and Ecosystems, 2026, pp 268-277 from Springer

Abstract: Abstract Springback is a major challenge in sheet metal forming, affecting the dimensional accuracy of bent components. This study proposes an Artificial Neural Network (ANN) to predict springback angles from material properties and bending parameters, trained on an industrial dataset including sheet thickness, internal radius, yield strength, elastic modulus, and applied force. The model achieved high predictive accuracy, generalized across materials and conditions, and reduced output variability while slightly underestimating extreme cases. Validation tests confirmed its ability to capture nonlinear elastic recovery, highlighting its potential for integration into Industry 4.0 manufacturing environments.

Keywords: Springback; Artificial Neural Networks; Sheet Metal Bending; Predictive Modelling (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-032-23282-3_33

Ordering information: This item can be ordered from
http://www.springer.com/9783032232823

DOI: 10.1007/978-3-032-23282-3_33

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().