Title: Decentralised identification of used exchange parts with a mobile application

Authors: Jan Lehr; Marian Schlüter; Jörg Krüger

Addresses: Department of Automation Technology, Fraunhofer IPK, 10587 Berlin, Germany ' Department of Automation Technology, Fraunhofer IPK, 10587 Berlin, Germany ' Industrial Automation Technology Group, TU Berlin, 10587 Berlin, Germany

Abstract: Sustainable product development and use requires an extended life cycle of used and defective mechanical parts. Remanufacturing saves resources and helps the industry to utilise the product more efficiently. Reverse logistics is one of the most important challenges towards efficient remanufacturing. To improve this process, we propose an on-site part identification at the workshops. A fast on-site identification is essential for assisting repair shop personnel and saving time on searching for the right spare parts. Based on images taken by a mobile device our application provides various machine vision services, e.g., visual identification of used parts, already successfully tested in a sorting facility for remanufacturing parts. The mobile application provides a robust visual identification for different environments. We show that enhancing data for machine vision approaches with images from decentral sensors, i.e., mobile devices, leads to an improved identification accuracy.

Keywords: remanufacturing; visual identification; decentralised identification; exchange parts; used parts; mobile application; object recognition; machine vision; deep learning; convolutional neural networks; reverse logistics; logistics; machine learning.

DOI: 10.1504/IJSM.2020.107135

International Journal of Sustainable Manufacturing, 2020 Vol.4 No.2/3/4, pp.150 - 164

Received: 27 Feb 2019
Accepted: 28 Jun 2019
Published online: 04 May 2020 *

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