Chemical Mechanical Polishing (CMP) is a crucial process in advanced semiconductor manufacturing, essential for achieving global planarization of the wafer surface, which directly impacts device performance and yield. Uniform material removal across the wafer is vital; however, non-uniformity frequently occurs, even with nominally uniform applied pressure. A prevalent issue is the edge effect, where the removal rate at the wafer edge significantly differs from that at the center, resulting in reduced uniformity and compromised device reliability. To tackle this challenge, this study explores the effectiveness of a multi-zone pressure-controlled carrier in enhancing polishing uniformity. Conventional single-zone carriers can only influence a narrow region of approximately 5–7 mm at the wafer edge, leading to limited improvements in nonuniformity of about 3%. In contrast, the multi-zone carrier allows for precise pressure control over a broader range, extending from 3 mm to 20 mm from the wafer edge. Experimental results show that this approach reduces non-uniformity to below 3% while effectively addressing edge removal deficiencies. These findings underscore the significant potential of multi-zone carriers to improve CMP process precision. Consequently, the proposed method is anticipated to enhance both productivity and quality in semiconductor fabrication.

In the semiconductor manufacturing industry, efficient operation of wafer transfer robots has a direct impact on productivity and product quality. Ball screw misalignment anomalies are a critical factor affecting precision transport of robots. Early diagnosis of these anomalies is essential to maintaining system efficiency. This study proposed a method to effectively diagnose ball screw misalignment anomalies using 1D-CNN and 2D-CNN models. This method mainly uses binary classification to distinguish between normal and abnormal states. Additionally, explainable artificial intelligence (XAI) technology was applied to interpret diagnostic decisions of the two deep learning models, allowing users to convince prediction results of the AI model. This study was based on data collected through acceleration sensors and torque sensors. It compared accuracies of 1D-CNN and 2D-CNN models. It presents a method to explain the model"s predictions through XAI. Experimental results showed that the proposed method could diagnose ball screw misalignment anomalies with high accuracy. This is expected to contribute to the establishment of reliable abnormality diagnosis and preventive maintenance strategies in industrial sites.

To measure the depth of the through silicon vias on 300 mm silicon wafers, a measuring machine was developed. Based on the preceding research in a laboratory environment, the machine was designed and built by modifying the optical probe for reducing the mass, combining a visible optical microscope to monitor the location of the measuring points, and constructing the metrology frame for large silicon wafers. The depths of the three different-sized through silicon vias were measured repeatedly to estimate the repeatability. Moreover, comparative measurement was carried out to verify the measured depth values. The total measurement time was also estimated by measuring 110 through silicon vias at different locations. According to the measurement results, the measurement performance satisfied the technical requirements of the industry in terms of repeatability, accuracy, and measurement time.

In this investigation, we describe a metrological technique for surface and thickness profiles of a silicon (Si) wafer by using a 6 degree of freedom (DOF) stitching method. Low coherence scanning interferometry employing near infrared light, partially transparent to a Si wafer, is adopted to simultaneously measure the surface and thickness profiles of the wafer. For the large field of view, a stitching method of the sub-aperture measurement is added to the measurement system; also, 6 DOF parameters, including the lateral positioning errors and the rotational error, are considered. In the experiment, surface profiles of a double-sided polished wafer with a 100 mm diameter were measured with the sub-aperture of an 18 mm diameter at 10x10 locations and the surface profiles of both sides were stitched with the sub-aperture maps. As a result, the nominal thickness of the wafer was 483.2 μm and the calculated PV values of both surfaces were 16.57 μm and 17.12μm, respectively.