# Estimating Recycling Return of Integrated Circuits Using Computer Vision on Printed Circuit Boards
## 6 Conclusions  
Recycling waste printed circuit boards (WPCBs) is very important for recovering high-value metals and providing an environmentally safe destination for these electronic residues. Integrated circuit detection and other components can improve the PCB recycling process since it improves automatic disassembly systems and reuses some components. In this sense, the PCB DSLR public dataset was published to support the research and development of computer-vision strategies for PCB recycling. This paper proposed a WPCB economic feasibility assessment (WPCB-EFA) method for recycling ICs from PCBs. As WPCBs have a high composition diversity, the main goal is to provide information regarding the WPCB composition to guide the recycling process such as the need to dismantle a particular PCB before the physical or mechanical recycling process.  
The first step of the WPCB-EFA is to detect ICs in a PCB. Deep learning object detection techniques require large-scale and fully-annotated datasets. Since the PCB DSLR dataset contains only 748 images from 165 different PCBs, transfer learning from the YOLOv3 pre-trained model was evaluated. In order to achieve better results in IC detection, the PCB DSLR Dataset images were split into squares of 416 \(\times\) 416 pixels, resulting in a total of 5347 images containing integrated circuits. With this image size, YOLOv3 fine-tuning resulted in 0.965 mAP. Qualitative analysis suggests that the model's errors occur when part of the IC is in the image.  
Considering the need for calculating the IC weight, we provide an IC surface density estimate based on the IC manufacturing data. Together with ICs recycling outcomes reported in the literature, we calculated the expected recovery mass for some elements. We noted that some PCBs have much more value than others and may go through different recycling processes. For instance, some PCBs may go to crushing, while others need dismantling before directly crushing. The proposed method may help to optimize the recycling process by such analysis.  
The economic evaluation of PCB recycling can be one motivational factor for recycling, aside from the urgent need to deal with electronic waste. In future works, it is necessary to expand the recycling economic evaluation to other PCB components aside from integrated circuits.  
Conceptualization, L.H.d.S.S.; Methodology, L.H.d.S.S. and B.J.T.F.; Software, A.A.F.J. and L.H.d.S.S.; Investigation, L.H.d.S.S.; Resources, S.C.O. and B.J.T.F.; Writing--original draft preparation, L.H.d.S.S. and G.O.A.A.; Writing--review and editing, L.H.d.S.S., G.O.A.A., and B.J.T.F.; Supervision, B.J.T.F. and S.C.O. All authors have read and agreed to the published version of the manuscript.  
This study was financed in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES)-Finance Code 001, and the Brazilian agencies FACEPE and CNPq.  
Not applicable.  
Data Availability Statement: The PCB DSRL dataset is a public dataset available in [10]. Source code of WPCB-EFA is available in [[https://github.com/ldhonorato/WPCB-EFA](https://github.com/ldhonorato/WPCB-EFA)]([https://github.com/ldhonorato/WPCB-EFA](https://github.com/ldhonorato/WPCB-EFA)) (accessed on 1 January 2021).