Empowering Supply Chain Management with AIBased Tools in the Inspection Machinery Industry
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. Muñoz
Mateo Del Gallo
Gerardo Minella
Samuel Olaiya Afolaranmi
M. Elahi
Yasir Rathore
Marcos Rico Vañó
Pedro Alfaro Fernández
Beatriz Andrés Navarro
F. Ciarapica
J. L. M. Lastra
Akses Cepat
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Cek di sumber asli →- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- Semantic Scholar
- DOI
- 10.1109/ICE/ITMC65658.2025.11106528
- Akses
- Open Access ✓