The Next Step in Intelligent Manufacturing
Empowering the Worker
With the Required Knowledge
The Right Information at the Right Time
Advanced Manufacturing Solutions
KIT-AR is an industrial augmented reality solution that digitally enhances the operator on the shopfloor by providing them with the required knowledge when needed.
At KIT-AR, we believe that our solutions will soon become one of the biggest segments in the industry. We’ve only just started, but we already know that every product we build requires hard-earned skills, dedication and a daring attitude. Continue reading and learn all there is to know about the smart tech behind our successful Startup Company.
Support factory workers providing the right information at the right time
Various modules that capture and understand the workplace context suggesting the right intervention to trigger in real-time.
In combination with KIT-ASSIST these modules
increase productivity and reduce mistakes.
Provides the means to generate and manage the AR-based work instructions for the KIT-ASSIST using a predefined annotation library.
Since the KIT components use a pre-defined library of purpose-built annotations, a suitably curated subset of information can be used to provide new insights into operations and processes.
Insight into how work processes are actually performed.
Support decision making on workplace and process improvements.
Discover recurring difficulties encountered by workers, identify bottlenecks and improvement opportunities.
Improve the workers skills
Provide the required knowledge when needed
Simplify the manufacturing process
Reduce mistakes and costs
Manuel worked as senior research scientist with major manufacturing companies (eg: Airbus, Comau, Volkswagen Autoeuropa, Hydro, Fiat) in improving workplace learning and productivity. His expertise in game-based learning has resulted in award winning game-based learning solutions with measurable impact on learner transformation.
Joao is a master technologist and solutions architect, with extensive knowledge and experience in delivering innovative solutions in the market. After more than a decade as a consultant at Microsoft, he designed and led implementation of complex systems in areas ranging from sensor data systems for agriculture and seaborne sensorized systems at Uavision. He successfully founded HighSkillz and built a multidisciplinary team of excellence responsible for award winning game-based learning solutions, including the multiple award-winning Child-Witness Interview Simulator for the Centre of Policing Research and Learning and the CEDR Mediation.
Felix worked as research scientist at SINTEF developing Process Mining methods that provide deep insights into work processes based on events captured on worker activities. His focus is the combination of machine learning to detect and identify relevant activities (activity recognition) and a process-centric view on the work execution (workflow management, process mining). He holds a PhD from Eindhoven University of Technology and contributed significantly to the leading open-source Process Mining software ProM and bupaR.
Mapping / Tracking
Simon, a reader at University College London, helped to developed one of the most widely used algorithms for estimation (the unscented Kalman filter) and extensively worked on filtering and estimation when the full dependency structure is not known (covariance intersection). He has worked extensively in low-level estimation, mapping and tracking as well as high-level augmented reality and user interfaces.
Youngjun worked as senior researcher and specialist at LG Electronics being responsible for several industrial projects, amongst which are novel 3D input and gesture recognition technologies used as advanced touch screen solutions in vehicles. His inventions were successfully commercialised in collaboration with automobile manufacturers including Porsche and BMW.
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