AI-enabled Operators Assistance through AR

AI-enabled Operators Assistance through AR
Summary
The Brainport DIH experiment was focused on the demonstration of an AI based hololens (AR) in assembly and operator support systems. The main idea of the experiment was to demonstrate the use of an AI based hololens to support operators with the assembly of high mix, low volume, high complexity modules. The main objective was to create the first steps towards adaptive AR support (ie. Hololens) for training and guidance in assembly making use of an AI based adaptive algorithm based on both productivity and quality as well as operator capacity and needs.
Recently, new technologies are entering the industrial market, such as Augmented Reality (AR). In these systems, the employee is guided step by step by means of projected instructions. The current systems are static: all operators receive similar instructions. However, there is a great need to make such systems adaptive and self-learning, which can be done using AI: dynamic customization of operator guidance based on skill level, performance, errors, instantaneous operator capacity and operator knowledge and feedback to improve effectivity of instructions.
This experiment has allowed efficient production of small, highly variable batches of different objects (in a nutshell, flexibility).
More information & hyperlinks
Country: NL
Address: Achtseweg zuid 159, Eindhoven 5651
Images
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Geographical location(s)
Structured mapping
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Demonstrator (project outcome type)
Industrial pilot or use case
Significant innovations and achievements
Comment:

An adaptive support system for training and guidance in assembly making use of an AI based adaptive algorithm  based on both productivity and quality as well as operator capacity and needs 

Significance of the results for SMEs
Comment:

Increase of productivity and quality of work (increase competiveness)

Increase  in workers employability

Increase in job satisfaction and reduction of work-related stress

C MANUFACTURING
Economic sustainability
Productivity
Process reliability - dependability - availability
Social sustainability
Increasing human achievements in manufacturing systems
Advanced material processing technologies
Methods for handling of parts, metrology and inspection
Integration of non-conventional technologies and conventional technologies
European Digital Innovation Hubs Cases and Demonstrators (DIH)