Industry Directory | Consultant / Service Provider / Manufacturer
Our Ultrasonic Stencil cleaners and 440-R-SMT Detergent are US & CA EPA Certified cleaners, that are environmentally and user safe. We are your single source for cleaning any type of solder paste from any fine pitch stencil.
Used SMT Equipment | In-Circuit Testers
Tektronix TDS3034 Bandwidth: 300 Mhz Channels: 4 The TDS3034 Digital Phosphor Oscilloscope (DPO) features advanced waveform capture, display, and measurement capabilities. The instrument delivers three dimensions of signal information (amplitude,
Used SMT Equipment | In-Circuit Testers
Agilent-Keysight 8753ET Network Analyzer 300kHz-3GHz or 6GHz The Agilent 8753ET vector network analyzer allows characterization of RF components at an affordable price. The Agilent 8753ET includes an integrated synthesized source, test set and
.jpg)
1)Model: EV-2515, 3020, 4030 (EV Manual series) EV series vision measuring machine has the features of powerful function and the high performance-price ratio. EV series adopt precision multi-magnification, ultra low-distortion and high resolution te
Used SMT Equipment | Chipshooters / Chip Mounters
30 intelligent spindle assemblies -> All vision processing is performed “on the fly” to maximize throughput. -> Continuous updates of X, Y, and Z-height pickup and placement locations ● On-The-Head Cameras -> narrow field of view c
Used SMT Equipment | In-Circuit Testers
Agilent 8753ES Agilent 8753ES 30 Khz to 3 or 6 Ghz Vector Network Analyzer The Agilent 8753ES vector network analyzer allows complete characterization of RF components. The 8753ES includes an integrated synthesized source, test set and tuned r
Used SMT Equipment | In-Circuit Testers
Agilent-Keysight 8753ES Agilent 8753ES 30 Khz to 3 or 6 Ghz Vector Network Analyzer The Agilent 8753ES vector network analyzer allows complete characterization of RF components. The 8753ES includes an integrated synthesized source, test set an
Technical Library | 2023-11-20 18:10:20.0
The electronics production is prone to a multitude of possible failures along the production process. Therefore, the manufacturing process of surface-mounted electronics devices (SMD) includes visual quality inspection processes for defect detection. The detection of certain error patterns like solder voids and head in pillow defects require radioscopic inspection. These high-end inspection machines, like the X-ray inspection, rely on static checking routines, programmed manually by the expert user of the machine, to verify the quality. The utilization of the implicit knowledge of domain expert(s), based on soldering guidelines, allows the evaluation of the quality. The distinctive dependence on the individual qualification significantly influences false call rates of the inbuilt computer vision routines. In this contribution, we present a novel framework for the automatic solder joint classification based on Convolutional Neural Networks (CNN), flexibly reclassifying insufficient X-ray inspection results. We utilize existing deep learning network architectures for a region of interest detection on 2D grayscale images. The comparison with product-related meta-data ensures the presence of relevant areas and results in a subsequent classification based on a CNN. Subsequent data augmentation ensures sufficient input features. The results indicate a significant reduction of the false call rate compared to commercial X-ray machines, combined with reduced product-related optimization iterations.
New Equipment | Component Programming
The TMS-100 Serial EEPROM Programmer programs 24' series EEPROM in circuit using the included software "EEPROM Tool", which runs under Windows. The TMS-100 currently supports the following devices: 24C00, 24C01, 24C02, 24C04, 24C08, 24C16, 24C32, 24C
New Equipment | Component Programming
The TMS-100 Serial EEPROM Programmer programs 24' series EEPROM in circuit using the included software "EEPROM Tool", which runs under Windows. The TMS-100 currently supports the following devices: 24C00, 24C01, 24C02, 24C04, 24C08, 24C16, 24C32, 24C
