Develop AI technologies in Industrial Plants
LEAD BY
 |
 |
FINANCED AND SUBSIDIZED BY
 |
 |
 |
Developing AI solutions
for industry 4.0
AppliediT is proud to be part of the IA4Q consortium, an innovative project led by Stellantis and ITA (Instituto Tecnológico de Aragón) that aims to develop Artificial Intelligence (AI) technologies for quality improvement and inspection in industrial plants, and has an investment of more than 10 million euros thanks to the joint financing of funds obtained through the TransMisiones program convened by the Ministry of Science, Innovation and Universities of Spain, through the Center for Technological Development and Innovation (CDTI ) and the State Investigation Agency (AEI).
We are committed to the development of innovative technologies that help companies improve their productivity and competitiveness. Participation in the IA4Q consortium is a unique opportunity to contribute to the advancement of AI in the industry and to collaborate with leading companies in the sector.
OUR MISSION
Provide our knowledge and experience in the following areas related to Artificial Intelligence
01
Machine vision for automatic inspection of parts and components
High-resolution cameras capture images, which are analyzed to detect defects and classify parts. This technology provides high precision, consistency, speed and profitability, improving production efficiency and safety.
02
Natural language processing (NPL) for data analysis and report generation
It uses AI to interpret textual data, extract information and create coherent reports. Techniques such as sentiment analysis and entity recognition transform unstructured data into meaningful information, improving decision making. NLP automates these processes, improving efficiency, reducing errors and providing timely business intelligence.
03
Machine learning for failure prediction and process optimization
AI is used to analyze data, identify patterns and predict equipment failures. By processing historical data, you anticipate problems before they occur, reducing downtime and maintenance costs. Additionally, machine learning optimizes processes by identifying inefficiencies and suggesting improvements, improving productivity and operational efficiency. This technology leads to more reliable operations and significant cost savings.
BENEFITS
The IA4Q consortium will work for 3 years on the development of AI solutions for quality improvement
01
Automate the inspection of parts and components to ensure the quality of the final product
By using this technology we can detect defects, maintain consistency and increase efficiency, reducing the risk of defective products reaching customers.
02
Predict equipment failures and perform more efficient preventative maintenance
It involves using technology to analyze data, foresee potential problems and schedule timely maintenance, reducing downtime and extending the useful life of equipment.
03
Optimize production processes and reduce operating costs
It involves using technology to identify inefficiencies, streamline operations, and minimize waste, leading to increased productivity and lower expenses.
At AppliediT we are very committed to the iA4Q project and its future results, which we are sure will revolutionize the way manufacturing plants in the automotive industry operate today, ensuring maximum sustainability and energy efficiency and promoting industrial digitalization.
At AppliediT we are very committed to the iA4Q project and its future results, which we are sure will revolutionize the way manufacturing plants in the automotive industry operate today, ensuring maximum sustainability and energy efficiency and promoting industrial digitalization.