AI Based Solutions for Manufacturing Mass Customization

Luis Usatorre; Paula Morella; Iñigo Sedano; Sergio Clavijo; Asier Aguayo

doi:10.1007/978-3-031-86489-6_19

AI Based Solutions for Manufacturing Mass Customization

Luis Usatorre^*
, Paula Morella
, Iñigo Sedano
, Sergio Clavijo
, Asier Aguayo

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Downloads (Pure)

Abstract

This paper analyses how to solve the challenges in the implementation of Mass Customization in manufacturing using Artificial Intelligence agents/services/tools. Considering that humans alone cannot cope with mass customization due to the huge amount of information, it is required AI based solutions that help humans to take decisions. We consider that those AI based solutions must communicate with other AI based solutions in order to obtain a holistic improvement (this is the Multi Agent System concept). More in detail, this paper addresses how to solve the challenges identified when AI based agents use external data coming from outside the company, so a Data Space to guaranteeing a secure data transaction and data ownership and sovereignty is required. This paper presents the solutions implemented in several projects to address the challenges created by the requirements on a-the implementation and scalability of AI based solutions in Manufacturing, b-for the implementation of multi-Agent AI-based systems and for c-implementing Data Spaces.

Original language	English
Title of host publication	Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024
Editors	Kosmas Alexopoulos, Sotiris Makris, Panagiotis Stavropoulos
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	180-193
Number of pages	14
ISBN (Print)	9783031864889
DOIs	https://doi.org/10.1007/978-3-031-86489-6_19
Publication status	Published - 2025
Event	2nd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2024 - Athens, Greece Duration: 16 Oct 2024 → 16 Oct 2024

Publication series

Name	Lecture Notes in Mechanical Engineering
ISSN (Print)	2195-4356
ISSN (Electronic)	2195-4364

Conference

Conference	2nd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2024
Country/Territory	Greece
City	Athens
Period	16/10/24 → 16/10/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Artificial Intelligence
Data Spaces
Manufacturing
Multi Agent System (MAS)
Value Chain (VC)

Access to Document

10.1007/978-3-031-86489-6_19

AI Based Solutions for Manufacturing Mass CustomizationFinal published version, 37.4 MBLicence: CC BY

Cite this

Usatorre, L., Morella, P., Sedano, I., Clavijo, S., & Aguayo, A. (2025). AI Based Solutions for Manufacturing Mass Customization. In K. Alexopoulos, S. Makris, & P. Stavropoulos (Eds.), Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024 (pp. 180-193). (Lecture Notes in Mechanical Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-86489-6_19

Usatorre, Luis ; Morella, Paula ; Sedano, Iñigo et al. / AI Based Solutions for Manufacturing Mass Customization. Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024. editor / Kosmas Alexopoulos ; Sotiris Makris ; Panagiotis Stavropoulos. Springer Science and Business Media Deutschland GmbH, 2025. pp. 180-193 (Lecture Notes in Mechanical Engineering).

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title = "AI Based Solutions for Manufacturing Mass Customization",

abstract = "This paper analyses how to solve the challenges in the implementation of Mass Customization in manufacturing using Artificial Intelligence agents/services/tools. Considering that humans alone cannot cope with mass customization due to the huge amount of information, it is required AI based solutions that help humans to take decisions. We consider that those AI based solutions must communicate with other AI based solutions in order to obtain a holistic improvement (this is the Multi Agent System concept). More in detail, this paper addresses how to solve the challenges identified when AI based agents use external data coming from outside the company, so a Data Space to guaranteeing a secure data transaction and data ownership and sovereignty is required. This paper presents the solutions implemented in several projects to address the challenges created by the requirements on a-the implementation and scalability of AI based solutions in Manufacturing, b-for the implementation of multi-Agent AI-based systems and for c-implementing Data Spaces.",

keywords = "Artificial Intelligence, Data Spaces, Manufacturing, Multi Agent System (MAS), Value Chain (VC)",

author = "Luis Usatorre and Paula Morella and I{\~n}igo Sedano and Sergio Clavijo and Asier Aguayo",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.; 2nd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2024 ; Conference date: 16-10-2024 Through 16-10-2024",

year = "2025",

doi = "10.1007/978-3-031-86489-6\_19",

language = "English",

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Usatorre, L , Morella, P , Sedano, I , Clavijo, S & Aguayo, A 2025, AI Based Solutions for Manufacturing Mass Customization. in K Alexopoulos, S Makris & P Stavropoulos (eds), Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024. Lecture Notes in Mechanical Engineering, Springer Science and Business Media Deutschland GmbH, pp. 180-193, 2nd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2024, Athens, Greece, 16/10/24. https://doi.org/10.1007/978-3-031-86489-6_19

AI Based Solutions for Manufacturing Mass Customization. / Usatorre, Luis ; Morella, Paula ; Sedano, Iñigo et al.
Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024. ed. / Kosmas Alexopoulos; Sotiris Makris; Panagiotis Stavropoulos. Springer Science and Business Media Deutschland GmbH, 2025. p. 180-193 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - AI Based Solutions for Manufacturing Mass Customization

AU - Usatorre, Luis

AU - Morella, Paula

AU - Sedano, Iñigo

AU - Clavijo, Sergio

AU - Aguayo, Asier

N1 - Publisher Copyright: © The Author(s) 2025.

PY - 2025

Y1 - 2025

N2 - This paper analyses how to solve the challenges in the implementation of Mass Customization in manufacturing using Artificial Intelligence agents/services/tools. Considering that humans alone cannot cope with mass customization due to the huge amount of information, it is required AI based solutions that help humans to take decisions. We consider that those AI based solutions must communicate with other AI based solutions in order to obtain a holistic improvement (this is the Multi Agent System concept). More in detail, this paper addresses how to solve the challenges identified when AI based agents use external data coming from outside the company, so a Data Space to guaranteeing a secure data transaction and data ownership and sovereignty is required. This paper presents the solutions implemented in several projects to address the challenges created by the requirements on a-the implementation and scalability of AI based solutions in Manufacturing, b-for the implementation of multi-Agent AI-based systems and for c-implementing Data Spaces.

AB - This paper analyses how to solve the challenges in the implementation of Mass Customization in manufacturing using Artificial Intelligence agents/services/tools. Considering that humans alone cannot cope with mass customization due to the huge amount of information, it is required AI based solutions that help humans to take decisions. We consider that those AI based solutions must communicate with other AI based solutions in order to obtain a holistic improvement (this is the Multi Agent System concept). More in detail, this paper addresses how to solve the challenges identified when AI based agents use external data coming from outside the company, so a Data Space to guaranteeing a secure data transaction and data ownership and sovereignty is required. This paper presents the solutions implemented in several projects to address the challenges created by the requirements on a-the implementation and scalability of AI based solutions in Manufacturing, b-for the implementation of multi-Agent AI-based systems and for c-implementing Data Spaces.

KW - Artificial Intelligence

KW - Data Spaces

KW - Manufacturing

KW - Multi Agent System (MAS)

KW - Value Chain (VC)

UR - https://www.scopus.com/pages/publications/105001226979

U2 - 10.1007/978-3-031-86489-6_19

DO - 10.1007/978-3-031-86489-6_19

M3 - Conference contribution

AN - SCOPUS:105001226979

SN - 9783031864889

T3 - Lecture Notes in Mechanical Engineering

SP - 180

EP - 193

BT - Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024

A2 - Alexopoulos, Kosmas

A2 - Makris, Sotiris

A2 - Stavropoulos, Panagiotis

PB - Springer Science and Business Media Deutschland GmbH

T2 - 2nd European Symposium on Artificial Intelligence in Manufacturing, ESAIM 2024

Y2 - 16 October 2024 through 16 October 2024

ER -

Usatorre L , Morella P , Sedano I , Clavijo S , Aguayo A. AI Based Solutions for Manufacturing Mass Customization. In Alexopoulos K, Makris S, Stavropoulos P, editors, Advances in Artificial Intelligence in Manufacturing II - Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, 2024. Springer Science and Business Media Deutschland GmbH. 2025. p. 180-193. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-031-86489-6_19

AI Based Solutions for Manufacturing Mass Customization

Abstract

Publication series

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UN SDGs

Keywords

Access to Document

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