ORDOPTIM is a feasibility study focused on an SLB machining workshop combining automated cell and manual operations. The project objectified the limits of the current scheduling and defined a realistic functional target for more anticipative, more reactive planning and better aligned with field constraints.
COPILIO evaluates how generative AI and language models can become operational assistants in industrial environments, with a focus on reliability, sovereignty and scaling. The project results in concrete scenarios, architecture choices and cost benchmarks for launching proofs of value.
The SustainableProdScore project has developed a methodology for assessing social and environmental impacts applicable to production equipment, to test the relevance and feasibility of carrying out a social life cycle analysis related to an industrial process and to obtain through environmental life cycle analyses the main contributors for the studied processes. A tool for modeling environmental and ultimately also social impacts is being finalized and tested.
The SmartWater project was aimed at reducing and controlling water consumption depending on the activity of the manufacturing site and supply restrictions in case of drought, in order to achieve more responsible water management.
The PREHDIGIT project aims to demonstrate the contribution of multi-finger modular grippers that can adapt to different loads and shapes, to automate and allow the use of cobots in some industrial manipulation and handling tasks. By combining advanced mechatronics and teaching strategies, these systems aim to optimise productivity, heighten safety and improve quality, while making operators’ work less strenuous. The project focuses on the validation of their modularity and compliance with current manufacturing requirements.
The COGEFLUX project has led to the definition and validation of a method for optimising thermal comfort on the basis of energy consumption data from production workshops. The three use cases selected for control and prediction via an energy digital twin brought out valuable potential energy savings (of about 10%).
