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Design, science and technology of digital manufacturing

Our work in driven through the Design, Science and Technology of:

Detection and Input Data Acquisition

The art and science of observation, acquisition, transformation and transition (e.g. sensors and actuation, human machine interface). In this evolutionary process, we can advise and help companies and institutions regardless of their size (i.e. single machine workshops, to global networked production systems) on how to upgrade, utilise and form collaborative networks with other similar industries for collective upgrade of machine, tools and production equipment. 

Input Data Interpretation and Machine Learning

A collision of big data from multiple sources provides an enriched perspective of the observable spectrum. With the introduction of advanced feature extraction, pattern recognition, data classification and analytics generalised as Machine Learning, we extract known and emerging patterns for development of both digital (e.g. event-based modelling) as well as symbolic and mathematical modelling.

Modelling and Simulation of Material, Machine and Process (Digital Twins)

The third stage in the Cyber Brain is using the observed and classified data to deploy its embedded Physical, Inferential and Heuristic close to reality high fidelity models which are continuously upgraded and improved due to knowledge discovery of step 1, 2 and human interventions. These models linked to the physical systems allow a full visualisation of current state and more importantly in a looking ahead mode, predictive and preventive strategies. Upon validation and verification of the solution such as material qualification, defect correction, fault and machine failure prevention, corrective machine adjustments, design improvement can be returned to the stakeholders through a Decision Support System.