Industrial Analytics for Advanced Machinery
The essence of the project is to enable an improved resource utilization through disturbance-free manufacturing resulting in sustainable production. The project is based on the combination of data-driven with knowledge-based modelling approaches for a hybrid physics-based analytics approach that relieves the weaknesses of both individual approaches by leveraging their complementary strengths.
The aim of implemented activities
Manufacturing requirements on high-valued and high-accuracy products depend on the improved flexibility of production processes. The essence of the project is to enable an improved resource utilization through disturbance-free manufacturing resulting unsustainable production. The aim of the research activity is to:
- Identify the operational behavior of advanced manufacturing machinery
- Make use of the information to build a physics-based digital model of the machinery
- Link the operational behavior through data analytics to maintenance activities and machinery performance.
The final goal is an integrated analytics approach to analyze, predict and optimize manufacturing machinery.
Potential impact
The introduced novel modelling approach (suited for machine tools and potentially industrial robots), can assure a more reliable description for health management of production equipment. The benefits can include reliability increase for machine tools and industrial robots, early fault identification, the exploitation of optimal measurement strategies for condition monitoring purposes.
Consortium
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