Next event

26/08/2026

TechBBQ 2026

Category: Factory-Level Optimisation

Country
Organisation
Category
Subcategory

AI Industrial Metaverse

Experiment

. Testing the immersive interaction in a digital twin environment of a real scenario.
. Evaluation of AI-provider capabilities of automatically creating source code and 3D environments
. Evaluate and visualize in 3D data of the AI-provider neural network

Target Audience

AI solution finder – Toolbox Lean 4.0

Study

Report with recommendations and profiles of identified solution elements

Target Audience

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AI-based Control for Wireless Power Transfer Systems

Experiment

Feasibility report, measurement results

Target Audience

AI-based Control of Electric Machines

Experiment

Feasibility report, measurement results

Target Audience

AI-based Fault Detection of Electric Drives

Experiment

Feasibility report, measurement results

Target Audience

AI-based Parameter Identification of Electric Machines

Experiment

Feasibility report, measurement results

Target Audience

AI-based Parameter Identification of Wireless Power Transfer Systems

Experiment

Feasibility report, measurement results

Target Audience

AI-based Sales & Operation planning

Experiment, Test

AI – based solution: 1) Automated workflow of production planning activities; 2) Automated data collection from market and specific clusterization of customer requirements; 3) Intelligent forecasting of market demand

Target Audience

AI-driven identification of high-variation parts

Experiment, Test, Study
  • Evaluation of ability to leverage existing technology modules to cope a higher variety of parts beyond what is currently possible.
  • The gained knowledge and infrastructure applied to new segments
    of applications & SMEs
  • Technology modules enhanced to the most prominent cases.
Target Audience

AI-driven material handling and automated bagging for high-variation production

Experiment, Study, Test
  • Evaluation of ability to leverage existing technology modules to cope a higher variety of parts beyond what is currently possible.
  • The gained knowledge and infrastructure applied to new segments
    of applications & companies
  • Technology modules enhanced to the most prominent cases.
Target Audience

AI-driven Palletization & Load Optimization

Test, Experiment

• Validated AI-based pallet loading optimization tool
• Improved loading efficiency and resource utilization
• Adaptation of the tool to product variability
• Benchmarking results demonstrating performance and scalability
• Readiness for deployment in industrial environments

Deliverables: Comprehensive technical report (specification analysis, algorithm adaptation, dataset preparation and training approach, implementation and benchmarking results), validated optimization tool (prototype level), performance evaluation results and recommendations for industrial deployment

Target Audience

AI-driven post-processing automation and workflow optimization for high-variation manufacturing

Experiment

Evaluation of ability to leverage existing technology for high variability of parts

Target Audience

AI-driven sorting of high-variation parts

Experiment, Study, Test
  • Evaluation of ability to leverage existing technology modules to cope a higher variety of parts beyond what is currently possible.
  • The gained knowledge and infrastructure applied to new segments
    of applications & companies
  • Technology modules enhanced to the most prominent cases.
Target Audience

AI-Explorer

Study

Report (on prioritised use cases and a short evaluation for the top few).

Target Audience

AI-powered Quality Inspection

Experiment, Study, Test
  • Detected defects and inspection accuracy
  • AI model performance and analytical insights
  • Suitability for the SME’s production process and materials
  • Recommendations for further development, optimization, or industrial adoption
Target Audience

AI4audio analysis

Experiment, Test

The service is meant to support the implementation of artificial intelligence and machine learning models for the continuous analysis of sounds and noises generated, for example, on production lines and in plants (such as vibrations, knocking, friction, airflow, and acoustic alarms). The expected result is a validated AI-based solution able to analyze audio for different purposes such as: (i) early identification of anomalies or faults through the recognition of “unexpected” acoustic patterns compared to normal operations; (ii) generating operational insights to improve personnel comfort and safety (e.g., noise reduction).

Target Audience