Knowledge and technology for more sustainable e-waste recycling (WEEE ID)

Research Project, 2013 – 2015

This project aims at developing a concept for the rapid and accurate sorting of electronic waste based on realtime machine vision and artificial intelligence data processing. Applying these technologies to waste streams is unique and will enable a higher material recovery rate and value, reduced emissions of hazardous substances, improved working conditions and detailed waste statistics. Examples of waste items that will be considered for the concept are printed circuit board assemblies, mobile phones, and lamps.

Waste of Electrical and Electronic Equipment (WEEE) is a fast-growing waste category with an estimated 20-50
million tones generated around the world every year. Discarded electronic products contain many hazardous
substances that may cause serious damage to the human health and the environment if the waste is not
properly sorted and adequately processed. Recycling end-of-life electronic products also enables to recover
valuable metals (e.g. gold, silver, copper, and aluminium), critical materials (e.g. cobalt, platinum, palladium,
rare earths), and other base materials (e.g. iron, glass, plastics) that can be used instead of virgin materials,
thus preserving natural resources and reducing pollution and emission of greenhouse gases.

Due to the diversity in product composition and materials content, all types of WEEE cannot be treated in a
similar way, but require different processes to enable efficient recovery and avoid emissions of hazardous
substances.

This project aims at developing a concept for the rapid and accurate sorting of electronic waste based on realtime
machine vision and artificial intelligence data processing. Applying these technologies to waste streams is
unique and will enable a higher material recovery rate and value, reduced emissions of hazardous substances,
improved working conditions and detailed waste statistics. Examples of waste items that will be considered for
the concept are printed circuit board assemblies, mobile phones, and lamps.

The target concept will be demonstrated by developing and implementing an automated lamp sorting
equipment that recognizes, registers and sorts the mixed waste lamp stream into relevant lamp streams for
subsequent dedicated pre-processing. This will result in an enhanced sorting and subsequent processing of
mercury-containing lamps, thus reducing mercury contamination of other material fraction (e.g. glass, metals,
and plastics) and preventing mercury release in the environment. A statistics, analysis and reporting tool will
also be implemented to generate accurate statistics on waste lamps. This will be valuable data for all actors
along the value chain from the lighting equipment producers to recyclers, producer responsibility organizations
and authorities.

The project will require research effort within the fields of materials analysis and separation, signal processing
and algorithm development, and production development.