Technical Library | 2018-07-18 16:28:26.0
Reduction of first pass defects in the SMT assembly process minimizes cost, assembly time and improves reliability. These three areas, cost, delivery and reliability determine manufacturing yields and are key in maintaining a successful and profitable assembly process. It is commonly accepted that the solder paste printing process causes the highest percentage of yield challenges in the SMT assembly process. As form factor continues to get smaller, the challenge to obtain 100% yield becomes more difficult.This paper will identify defects affecting SMT yields in the printing process and discuss their Root Cause. Outer layer copper weight and surface treatment will also be addressed as to their effect on printability. Experiments using leadless and emerging components will be studied and root cause analysis will be presented
Technical Library | 2020-10-08 01:01:01.0
Flexible hybrid electronics (FHE) is emerging as a promising solution to combine the benefits of printed electronics and silicon technology. FHE has many high-impact potential areas, such as wearable applications, health monitoring, and soft robotics, due to its physical advantages, which include light weight, low cost and the ability conform to different shapes. However, physical deformations in the field can lead to significant testing and validation challenges. For example, designers must ensure that FHE devices continue to meet their specs even when the components experience stress due to bending. Hence, physical deformation, which is hard to emulate, has to be part of the test procedures for FHE devices. This paper is the first to analyze stress experience at different parts of FHE devices under different bending conditions. We develop a novel methodology to maximize the test coverage with minimum number of text vectors with the help of a mixed integer linear programming formulation. We validate the proposed approach using an FHE prototype and COMSOL Multiphysics simulations
Technical Library | 2021-06-07 19:06:32.0
The technological growth of the last decades has brought many improvements in daily life, but also concerns on how to deal with electronic waste. Electrical and electronic equipment waste is the fastest-growing rate in the industrialized world. One of the elements of electronic equipment is the printed circuit board (PCB) and almost every electronic equipment has a PCB inside it. While waste PCB (WPCB) recycling may result in the recovery of potentially precious materials and the reuse of some components, it is a challenging task because its composition diversity requires a cautious pre-processing stage to achieve optimal recycling outcomes. Our research focused on proposing a method to evaluate the economic feasibility of recycling integrated circuits (ICs) from WPCB. The proposed method can help decide whether to dismantle a separate WPCB before the physical or mechanical recycling process and consists of estimating the IC area from a WPCB, calculating the IC's weight using surface density, and estimating how much metal can be recovered by recycling those ICs. To estimate the IC area in a WPCB, we used a state-of-the-art object detection deep learning model (YOLO) and the PCB DSLR image dataset to detect the WPCB's ICs. Regarding IC detection, the best result was obtained with the partitioned analysis of each image through a sliding window, thus creating new images of smaller dimensions, reaching 86.77% mAP. As a final result, we estimate that the Deep PCB Dataset has a total of 1079.18 g of ICs, from which it would be possible to recover at least 909.94 g of metals and silicon elements from all WPCBs' ICs. Since there is a high variability in the compositions of WPCBs, it is possible to calculate the gross income for each WPCB and use it as a decision criterion for the type of pre-processing.
| 1 |
winsouce.jpg)
