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This paper aims to propose a novel placing method, i.e., place-between-paste-andpad (PB), for mini-scale passive components to enhance electronic assembly lines' yield. PB means a component is designed to be placed at the midpoint between the pastes and pads on the length direction while it aligns with the pads' center on the width direction. An experiment that involves 12 printed circuit boards (PCB) is designed and conducted to get comparative results. Four PCBs are employed for place-on-pad (PP), place-on-paste (PPS), and PB separately. On each board, 375 resistors R0402M (0.40 mm × 0.20 mm) are assembled horizontally.To study the components' misalignment under various solder paste offset conditions in different placement methods, a stencil with 25 solder paste offset settings is utilized. Based on this experiment's results, PB has superior performance to the other two methods to minimize components' misalignment. Regarding the number of acceptable components when post-reflow offsets are within 25% of components' dimensions, PB and PP have equivalent performances, and they both outperform PPS. Furthermore, PB is a lowcost placing strategy because PB needs not the real-time communication between the solder paste inspection machine and the pickand-place machine. With the miniaturization trend in electronic products, the postreflow components' misalignment is more frequently observed than before. The placement method proposed in this study is expected to offer a low-cost exploration in the component pick-and-place procedure to enhance the surface mount technology (SMT) assembly quality.Keywords SMT assembly • mini-scale passive components • pick-and-place • place-on-pad • place-on-paste beneficial for large components in decreasing 56 the misalignment [3]-[5], it did not perform so 57 well for mini-scale components.

Motivation: As passive components’ size gets smaller, quality rejects due to overhang and misalignment after the reflow appear more frequently. This situation is partly because the pass-fail criterion is set based on the offset concerning the component dimensions. Therefore, understanding the self-alignment characteristics of electronic components becomes very critical for surface-mount assembly yield. This research investigates the dissimilarity of self-alignment in the length and width directions. Approach: To avoid the argument of sample to sample variations, data are collected from 81 printed circuit boards (PCB) and 182,250 assembled components. Within a PCB, 25 different solder paste printing offset locations and 81 component placement offset settings are implemented. Component-placement positions before and after the reflow are monitored. The results are compared to identify different component sizes’ self-alignment characteristics in the length and width directions. Key findings: The misalignment of smaller passive components, e.g., R0402M(0.40 mm × 0.20 mm), is worse than the larger component under the identical solder paste printing and component placement conditions. Furthermore, the self-alignment characteristic in the length direction of these passive components, e.g., R0402M, to R1005M (1.00 mm × 0.50 mm) is superior to that of width direction. The observations are not consistent with the results found in earlier research that reported on larger components, e.g., C0402M(0.40 mm × 0.20 mm), to C3216M(3.20 mm × 1.50 mm).

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We propose a new calibration method for pure rotational Raman (PRR) lidar temperature profiling based on the different temperature sensitivities of Stocks and anti-Stocks PRR lines. This method reconstructs the expression of the differential backscatter cross section according to the temperature dependencies of each component and forms a temperature factor and a calibration factor in the intensity ratio. With these factors, the temperature is retrievable from the lidar return. The effectiveness and accuracy of the proposed method have been verified through simulations and experiments. The inversion error can be reduced by~50% compared with the commonly used calibration methods in weak signal-to-noise situations.Plain Language Summary A new calibration method for temperature detecting by a pure rotational Raman lidar is proposed. Based on the properties of the pure rotational Raman spectrum, a calibration factor is formed in the return signals and is used to retrieve the temperature in combination with local radiosonde. Both simulations and experiments validate the effectiveness of our proposed method. The inversion errors are reduced by~50% compared with the traditional fitting methods in weak signal-to-noise environments. HE ET AL.10,925

Purpose This paper aims to study the component pick-and-place (P&P) defect patterns for different root causes based on automated optical inspection data and develop a root cause identification model using machine learning. Design/methodology/approach This study conducts experiments to simulate the P&P machine errors including nozzle size and nozzle pick-up position. The component placement qualities with different errors are inspected. This study uses various machine learning methods to develop a root cause identification model based on the inspection result. Findings The experimental results revealed that the wrong nozzle size could increase the mean and the standard deviation of component placement offset and the probability of component drop during the transfer process. Moreover, nozzle pick-up position can affect the rotated component placement offset. These root causes of defects can be traced back using machine learning methods. Practical implications This study provides operators in surface mount technology assembly lines to understand the P&P machine error symptoms. The developed model can trace back the root causes of defects automatically in real line production. Originality/value The findings are expected to lead the regular preventive maintenance to data-driven predictive and reactive maintenance.

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