Automatic Optical Inspection of Micro Drill Bit in Printed Circuit Board Manufacturing Based on Pattern Classification

Abstract

Automatic optical inspection (AOI) of micro drill bit becomes more and more important with the rapid expanding of Printed Circuit Board (PCB) manufacturing industry. Distinguished from most traditional manual inspection approach, AOI is time-saving, objective and non contact. In this work, a pattern classification method is proposedfor the AOI of micro drill bit in PCB manufacturing, in which three features of drill bit blade are extractedfor classification. In order to be independent on the clamp that can guarantee the exact position of drill bit blade for photography, and reduce the cost of the AOI system, an image registration method is used to align the drill bit blade, which can also make the feature extraction much easier. The evaluation result indicates that the approach works wellfor the AOI ofmicro drill bit. It is real time, more detailed result providing and low requirement on photographic device.

Automatic Optical Phase Identification of Microdrill Bits in Printed Circuit Board Manufacturing

“…We select three features (16) , length, width, and normalized end area of cutting plane to classify the phases of microdrill bits. In the following we will describe how to calculate them.…”

“…However, besides whether there are any geometric defects on a microdrill bit, we should like to have further particulars, such as the phase which it falls in. The phase of the lifecycle is an important index to evaluate drill life (16) , which reveals not only the state of drill wear but also the condition of drill fix. Generally during a microdrill using lifecycle there are six important phases which are denoted as N, ND, K1, K1D, K2 and K2D (examples are shown in Fig.…”

Yapay Sinir Ağı ve Görüntü İşleme tabanlı Basınç Dayanımı Tahmini

“…Especially image processing and artificial intelligence-based methods are used to measure the compressive strength in buildings (Chen et al, 2002;Hsiao et al, 2010). Especially problems that take a lot of time to solve and require intensive experimental studies can be easily calculated with computer vision technology and solutions are produced in a short time (Duan et al, 2008;Yazdi et al, 2011).…”

MATLAB based defect detection and classification of printed circuit board

“…Contact method tests the connectivity of circuits but unable to detect major flaws in cosmetic defects [7]. Non-contact uses methods such as ultrasonic and x-ray imaging to detect anomalies in the circuit design, both cosmetic and functional [8][9][10][11]. The use of manual labour to visually inspect each PCB is no longer viable since it is prone to human errors, time consuming, requires large overhead costs and results in high wastage.…”