A computer vision approach for automatically mining and classifying end of life products and components

Matthew L. Dering, Conrad S. Tucker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The authors of this work present a computer vision approach that discovers and classifies objects in a video stream, towards an automated system for managing End of Life (EOL) waste streams. Currently, the sorting stage of EOL waste management is an extremely manual and tedious process that increases the costs of EOL options and minimizes its attractiveness as a profitable enterprise solution. There have been a wide range of EOL methodologies proposed in the engineering design community that focus on determining the optimal EOL strategies of reuse, recycle, remanufacturing and resynthesis. However, many of these methodologies assume a product/component disassembly cost based on human labor, which hereby increases the cost of EOL waste management. For example, recent EOL options such as resynthesis, rely heavily on the optimal sorting and combining of components in a novel way to form new products. This process however, requires considerable manual labor that may make this option less attractive, given products with highly complex interactions and components. To mitigate these challenges, the authors propose a computer vision system that takes live video streams of incoming EOL waste and i) automatically identifies and classifies products/components of interest and ii) predicts the EOL process that will be needed for a given product/component that is classified. A case study involving an EOL waste stream video is used to demonstrate the predictive accuracy of the proposed methodology in identifying and classifying EOL objects.

Original languageEnglish (US)
Title of host publication20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791857113
DOIs
StatePublished - Jan 1 2015
EventASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015 - Boston, United States
Duration: Aug 2 2015Aug 5 2015

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume4

Other

OtherASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015
CountryUnited States
CityBoston
Period8/2/158/5/15

Fingerprint

Computer Vision
Computer vision
Mining
Waste management
Sorting
Personnel
Costs
Methodology
Life
Industry
Classify
Remanufacturing
Disassembly
Vision System
Engineering Design
Reuse
Minimise
Predict

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

Dering, M. L., & Tucker, C. S. (2015). A computer vision approach for automatically mining and classifying end of life products and components. In 20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems (Proceedings of the ASME Design Engineering Technical Conference; Vol. 4). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2015-47401
Dering, Matthew L. ; Tucker, Conrad S. / A computer vision approach for automatically mining and classifying end of life products and components. 20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems. American Society of Mechanical Engineers (ASME), 2015. (Proceedings of the ASME Design Engineering Technical Conference).
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Dering, ML & Tucker, CS 2015, A computer vision approach for automatically mining and classifying end of life products and components. in 20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems. Proceedings of the ASME Design Engineering Technical Conference, vol. 4, American Society of Mechanical Engineers (ASME), ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015, Boston, United States, 8/2/15. https://doi.org/10.1115/DETC2015-47401

A computer vision approach for automatically mining and classifying end of life products and components. / Dering, Matthew L.; Tucker, Conrad S.

20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems. American Society of Mechanical Engineers (ASME), 2015. (Proceedings of the ASME Design Engineering Technical Conference; Vol. 4).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Dering ML, Tucker CS. A computer vision approach for automatically mining and classifying end of life products and components. In 20th Design for Manufacturing and the Life Cycle Conference; 9th International Conference on Micro- and Nanosystems. American Society of Mechanical Engineers (ASME). 2015. (Proceedings of the ASME Design Engineering Technical Conference). https://doi.org/10.1115/DETC2015-47401