AI based toolkit for modelling the disassembly/recycle processes to help streamline the infrastructure needed to circulate materials focusing around the ability for AI algorithms to recognise and identify objects using cameras and other sensors.
Toolkit that combines AI and Life Cycle methodologies (LCC, LCA, S-LCA) for identifying the best machine end-of-life by devising a multi-objective optimisation strategy to strike a balance between economic, social and environmental benefits.
Toolkit for smart retrofitting old machine tools to give them a second life by improving working conditions and product quality, developing a communication system and collaboration, enhancing productivity, efficiency, flexibility, and agility.
Toolkit for predicting remaining useful life and identifying maintenance requirements with the target of extending the overall machine remaining life.
Toolkit comprising a set of AI-enabled features for manufactured product quality monitoring.
Toolkit to train models with measurement data and then train machine controllers with said models to accommodate the machine condition and requirements.
Toolkit that will allow detecting anomalies at component-level or of the machine as a whole when it is in working conditions in the factory where it is being used.
Toolkit for determining the condition of the machine as a whole or of some of its components when it is in working conditions in the factory where it is being used.
Toolkit for the fast calibration of industrial equipment when installed for the first time in a factory or when a re-calibration is needed. It uses AI techniques for providing the most well-suited calibration parameters.
AI-based toolkit that is capable of optimising the storage and delivery of products. This optimisation will target storage space, storage conditions and product transportation. Additionally, this optimiser will provide optimisation for logistics scheduling and planning