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.
Empowering Supply Chain Management with AIBased Tools in the Inspection Machinery Industry / Muñoz, Juan Pablo Fiesco; Del Gallo, Mateo; Minella, Gerardo; Afolaranmi, Samuel Olaiya; Elahi, Mahboob; Rathore, Yasir; Vañó, Marcos Rico; Fernández, Pedro Alfaro; Navarro, Beatriz Andrés; Ciarapica, Filippo Emanuele; Lastra, Jose Luis Martinez. - (2025), pp. 1-10. ( 31st ICE IEEE/ITMC Conference on Engineering, Technology, and Innovation, ICE 2025 esp 2025) [10.1109/ice/itmc65658.2025.11106528].
Empowering Supply Chain Management with AIBased Tools in the Inspection Machinery Industry
Del Gallo, MateoSecondo
;Ciarapica, Filippo Emanuele;
2025-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


