Abstrakti
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 AI-
Procurement Optimizer module supports purchasing decisions by considering supply constraints and cost targets, while AI-Fabrication 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.
Procurement Optimizer module supports purchasing decisions by considering supply constraints and cost targets, while AI-Fabrication 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.
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | 2025 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) |
| Kustantaja | IEEE |
| Sivumäärä | 10 |
| ISBN (elektroninen) | 979-8-3315-8534-1 |
| ISBN (painettu) | 979-8-3315-8535-8 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 13 elok. 2025 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | IEEE international conference on engineering, technology and innovation - Valencia, Espanja Kesto: 16 kesäk. 2025 → 19 kesäk. 2025 |
Julkaisusarja
| Nimi | 2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC) |
|---|---|
| Kustantaja | IEEE |
| ISSN (painettu) | 2334-315X |
| ISSN (elektroninen) | 2693-8855 |
Conference
| Conference | IEEE international conference on engineering, technology and innovation |
|---|---|
| Maa/Alue | Espanja |
| Kaupunki | Valencia |
| Ajanjakso | 16/06/25 → 19/06/25 |
Rahoitus
This research has been partially funded by Horizon Europe Ref. 101057294 "AI-Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability, and Resilience (AIDEAS)"; and the Conselleria de Educación, Investigación, Cultura y Deporte - Generalitat Valenciana for hiring predoctoral research staff with Grant (CIACIF/2023/245)
YK:n kestävän kehityksen tavoitteet
Tämä tuotos edistää seuraavia kestävän kehityksen tavoitteita:
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SDG 8 – Ihmisarvoinen työ ja taloudellinen kasvu
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SDG 9 – Teollisuus, innovaatiot ja infrastruktuuri
Julkaisufoorumi-taso
- Jufo-taso 1
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