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

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.

Authors

Institutions

Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/ice/itmc65658.2025.11106528
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Pedro L. Sánchez, Samuel Olaiya Afolaranmi, Mahboob Elahi, Filippo Emanuele Ciarapica et al.
Digital Transformation in Industry
article

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

Pedro L. Sánchez, Samuel Olaiya Afolaranmi, Mahboob Elahi, Filippo Emanuele Ciarapica, José L. Martínez Lastra, Mateo Del Gallo, Gerardo Minella, Juan‐Guillermo Muñoz, Beatriz Andrés Navarro, Yasir Rathore, Marcos Rico Vañó
article en

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.

Marche Polytechnic University (IT), University of Alicante (ES), Tampere University of Applied Sciences (FI), Tampere University (FI), Centro Tecnológico de Investigación, Desarrollo e Innovación en tecnologías de la Información y las Comunicaciones (TIC) (ES), Universitat Politècnica de València (ES)
Openalex Percentile: Top 72%
Digital Transformation in Industry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.