Technical Library | 2023-12-18 11:33:57.0
Elevate your electronic manufacturing game with the I.C.T-D600 SMT Dispensing Machine! Precision, safety, and efficiency in one powerful solution. In the dynamic realm of electronic manufacturing, precision and efficiency are not just preferences but essential requirements. Introducing the I.C.T-D600, an automatic glue dispenser machine engineered to enhance production processes across various applications. From chip encapsulation to PCB assembly, SMT red-glue dispensing, LED lens production, and medical device creation, SMT dispensing machine is a versatile solution tailored to meet the demands of the industry. Essential Attributes Of The I.C.T-D600 Automatic Glue Dispenser Machine 1. Compliance with European Safety Standards: The I.C.T-D600 SMT dispensing machine prioritizes not only efficiency but also safety, boasting compliance with European safety standards and holding a CE certificate. This ensures a secure and reliable manufacturing environment, aligning with global quality benchmarks. 2. International Component Quality: Internationally renowned components form the core of the D600 SMT dispensing machine. From Panasonic servomotors to MINTRON CCD, each element is carefully selected, guaranteeing high performance and durability. This commitment to quality components results in a machine that operates seamlessly, reducing downtime and maintenance costs. 3. Impressive Performance Metrics: The SMT dispensing machinedoesn't just meet expectations; it surpasses them with exceptional performance metrics: Maximum Guide Rail Speed: 400mm/s Fastest Injection Valve Speed: 20 spots/sec Dispensing Accuracy: ±0.02mm Repeated Accuracy: ±0.01mm Machine Characteristics: Core Part – Jet Valve The non-contact jet dispensing method ensures high-speed operation (max jet speed: 20 spots/second), high accuracy with a minimum dispensing volume of 5nl, and flexibility with extremely small dispensing volumes. The thermostatic system for the flow channel and sprayer ensures uniform glue temperature, resulting in low maintenance costs and an extended service life. Enhanced Capacity: Non-contact jet dispensing eliminates the need for Z-axis motion. Integrated temperature control technology reduces manual intervention. Automatic glue compensation minimizes artificial regulation time. Dual-track design reduces waiting time. Automatic visual location identification and compensation. Non-contact height detection with laser reduces height detection time. Flexibility: Capable of handling substrates or backings of various sizes. Optional heating module. Independent control of dual tracks with user-friendly software. Fast switching between different product lines. Universal platform suitable for various processes with different glues
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.
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