CL4-INDUSTRY | ADV_MANU | TWIN-TRANSITION-02: Physical and cognitive augmentation in advanced manufacturing

Project Title:
AUGMENT4COST – Cognitive augmentation and AI-based automation for cost estimation in advanced manufacturing

Objective:
The project aims to develop and validate an AI-driven system for the automation of cost estimation in discrete manufacturing. By integrating machine learning (ML), technical drawing analysis, and user-centric interfaces for technologists, the project supports decision automation, enhances flexibility, and increases the cognitive capabilities of workers in cost-sensitive industrial contexts.

Challenge Addressed:
Manual cost quotation processes in manufacturing are slow, prone to errors, and rely heavily on experience. This leads to lost business opportunities and poor use of historical data. Our system will transform this through AI-based prediction, standardised data pipelines (ETL), and intuitive interfaces for human–machine interaction.

Alignment with the call (TWIN-TRANSITION-02):

• Cognitive augmentation of human workers in manufacturing through AI and ML

• Integration of smart data pipelines from technical drawings and historical quotations

• Human-centric design, supporting technologists and operators with intuitive interface

• Validation in real industrial environments (MECASYS factory)

• Use of real production data, living lab settings, and potential impact on workforce roles

Consortium Status:

• MECASYS s.r.o. (SK): Industrial partner, pilot site, data provider

• Pulsar Solutions s.r.o. (CZ): AI/ML system development, software integration

Coordinator sought: Experienced research institution with proven track record in EU projects (preferably from CZ/DE/AT) with expertise in manufacturing systems, HMI, and cognitive ergonomics.