Semantic Scholar Open Access 2025

Empowering Supply Chain Management with AIBased Tools in the Inspection Machinery Industry

J. Muñoz Mateo Del Gallo Gerardo Minella Samuel Olaiya Afolaranmi M. Elahi +6 lainnya

Abstrak

The manufacturing industry is increasingly adopting Artificial Intelligence (AI)-based solutions to improve production planning and operational efficiency. This article reflects the work carried out in the context of the AIDEAS project. AIDEAS aims to develop AI solutions for the lifecycle of industrial equipment, within the manufacturing phase focusing on three of the key processes within the Supply Chain Management of procurement, fabrication and delivery. The AIProcurement Optimizer module supports purchasing decisions by considering supply constraints and cost targets, while AIFabrication Optimizer module improve production planning and scheduling through a combined approach of mathematical optimization and reinforcement learning. Finally, AI-Delivery Optimizer optimizes delivery logistics to reduce delays and transport costs. A holistic framework, AIDEAS Manufacturing Framework, is proposed that integrates all solutions, showing the connections between them and their workflow. The proposed framework undergoes testing in a real company from the inspection machinery industry through a structured implementation plan, highlighting both the benefits and challenges of adopting AI in small and medium enterprises. The findings underscore the role of AI in driving greater agility, sustainability, and resilience across manufacturing operations.

Penulis (11)

J

J. Muñoz

M

Mateo Del Gallo

G

Gerardo Minella

S

Samuel Olaiya Afolaranmi

M

M. Elahi

Y

Yasir Rathore

M

Marcos Rico Vañó

P

Pedro Alfaro Fernández

B

Beatriz Andrés Navarro

F

F. Ciarapica

J

J. L. M. Lastra

Format Sitasi

Muñoz, J., Gallo, M.D., Minella, G., Afolaranmi, S.O., Elahi, M., Rathore, Y. et al. (2025). Empowering Supply Chain Management with AIBased Tools in the Inspection Machinery Industry. https://doi.org/10.1109/ICE/ITMC65658.2025.11106528

Akses Cepat

Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
Semantic Scholar
DOI
10.1109/ICE/ITMC65658.2025.11106528
Akses
Open Access ✓