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Solder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation.

A robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint.

The experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment.

The precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality.

The proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.

In the vibration reduction field, constrained stand-off layer damping cylindrical shell plays an important role. However, due to the lack of accurate analysis of its damping characteristics, this hinders its further research and application. Therefore, the purpose of this paper is concerned with an accurate solution for the vibration-damping characteristics of a constrained stand-off-layer damping cylindrical shell (CSDCS) under various classical boundary conditions and conducts a further analysis.

Based on the Rayleigh–Ritz method and the Hamilton principle, a dynamic model of CSDCS is established. Then the loss factor and the frequency of CSDCS are obtained. The correctness and convergence behavior of the present model are verified by comparing the calculation results with the literature. By using for various classical boundary conditions without any special modifications in the solution procedure, the characteristics of CSDCS with S-S, C-C, C-S, C-F and S-F boundaries are discussed.

The Rayleigh–Ritz method is effective in handling the problem of CSDCS with different boundaries and an accurate solution is obtained. The boundary conditions have an important influence on the vibration and damping behavior of the CSDCS.

Based on the Rayleigh–Ritz method and Hamilton principle, a dynamic model of CSDCS is established for the first time, and then the loss factor and frequency of CSDCS are obtained. In addition, the effectiveness of adding the stand-off layer between the base shell and the viscoelastic layer is confirmed by discussing the characteristics of CSDCS with S-S, C-C, C-S, C-F and S-F boundaries.

This paper aims to propose a novel method to predict and alleviate feature fatigue. Many products now are loaded with an extensive number of features. Adding more features to one product generally makes the product more attractive on the one hand but, on the other hand, may result in increasing difficulty to use the product. This phenomenon is called “feature fatigue”, which will lead to dissatisfaction and negative word-of-mouth (WOM). Feature fatigue will damage the brand’s long-term profit, and ultimately decrease the manufacturer’s customer equity. Thus, a problem of balancing the benefit of increasing “attractiveness” with the cost of decreasing “usability” exists.

A novel method based on the Bass model is proposed to predict and alleviate feature fatigue. Product capability, usability and WOM effects are integrated into the Bass model to predict the impacts of adding features on customer equity in product development, thus helping designers alleviate feature fatigue. A case study of mobile phone development based on survey data is presented to illustrate and validate the proposed method.

The results of the case study demonstrate that adding more features indeed increases initial sales; however, adding too many features ultimately decreases customer equity due to usability problems. There is an optimal feature combination a product should include to balance product capability with usability. The proposed method makes a trade-off between initial sales and long-term profits to maximize customer equity.

The proposed method can help designers predict the impacts of adding features on customer equity in the early stages of product development. It can provide decision supports for designers to decide what features should be added to maximize customer equity, thus alleviating feature fatigue.

Various demands and requirements of foreign home-buyers from different background are yet unclear to most of the residential developers. The aim of this study is to blueprint a fuzzy mapping of psychological phenomena reflected in consumer behavior, and to develop a Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) decision making model to assist residential developers in dealing with potential foreign customers. Through a questionnaire survey in the form of pair wise comparison matrix among 126 expatriates, this study introduces a new approach to assist residential developers dealing with expatriates' preference on house purchase in Malaysia in a simple and efficient way. With this fuzzy mapping, residential developers could utilize psychological phenomena to manipulate expatriates' preference on housing purchase rather than to merely comply passively.

Polymeric parts produced by 3D stereolithography (SL) process have poorer mechanical properties as compared to their counterparts fabricated via conventional methods, such as injection or compression molding. Adding nanofillers in the photopolymer resin for SL could help improve mechanical properties. This study aims to achieve enhancement in mechanical properties of parts fabricated by SL, for functional applications, by using well-dispersed nanofillers in the photopolymers, together with suitable post-processing.

Carbon nanotubes (CNTs) have high strength and Young’s modulus, making them attractive nanofillers. However, dispersion of CNTs in photopolymer is a critical challenge, as they tend to agglomerate easily. Achieving good dispersion is crucial to improve the mechanical properties; thus, suitable dispersion mechanisms and processes are examined. Solvent exchange process was found to improve the dispersion of multiwalled carbon nanotubes in the photopolymer. The UV-absorbing nature of CNTs was also discovered to affect the curing properties. With suitable post processing, coupled with thermal curing, the mechanical properties of SL parts made from CNTs-filled resin improved significantly.

With the addition of 0.25 wt.% CNTs into the photopolymer, tensile stress and elongation of the 3D printed parts increased by 70 and 46 per cent, respectively. With the significant improvement, the achieved tensile strength is comparable to parts manufactured by conventional methods.

This allows functional parts to be manufactured using SL.

In this paper, an improved procedure to incorporate CNTs into the photopolymer was developed. Furthermore, because of strong UV-absorption nature of CNTs, curing properties of photopolymer and SL parts with and without CNT fillers were studied. Optimized curing parameters were determined and additional post-processing step for thermal curing was discovered as an essential step in order to further enhance the mechanical properties of SL composite parts.

This paper aims to explore factors affecting young consumers’ purchasing of new smart products under the influence of social media.

Twenty semi-structured, face-to-face, in-depth interviews were conducted with young consumers who used new media, and five extended interviews were conducted with popular smartwatch retailers in Macau.

The findings reveal that they tend to garner product information from multiple channels of communication. Social media exert the greatest influence. Reliable information, strong branding and interactions with vendors are also influential, although new product pre-announcements may be boring and difficult to understand.

This study presents new insights into diffusion of innovation theory and provides retailers launching smart products with a better understanding of their target young customers’ purchasing behavior.

The aim of this paper is to explore the potential of particle swarm optimization (PSO) methods for minimizing the sidelobe levels (SLL) and placing null at arbitrary angles of a nonlinear antenna array.

An improved PSO algorithm is designed.

The improved PSO method is an efficient and robust global optimizer for minimizing the SLL and placing null at arbitrary angles of a nonlinear antenna array.

Some improvements, such as the design of some new formulae for both position and velocity updating, the introduction of an age variable, and the devise of an intensification searches using the cross entropy method, are proposed.

The purpose of this paper is to study the profit optimization of manufacturers who provide personalized products to customers, thus avoiding additional operational costs and response times in the production process of personalized product design.

First, the authors present an integrated model for optimizing profit where the design and production of personalized products are both considered. The authors propose the concept of personalization level and four cases of personalization level are considered including top, high, medium and low levels. Polynomial-time optimal rules are provided for each level by analyzing 17 subcases where all possible personalized products are considered. Then, the authors compare the obtained profit of personalized products with the optimal profit of standardized products.

At low and high levels of personalization, personalized manufacturing is more profitable for specific products with specific characteristics. At the top and middle level of individuation, assuming that the product has certain characteristics, whether the best choice to produce personalized products depends on the level of individuation chosen by customers.

An important decision issue for manufacturers is whether to produce personalized or standardized products. In this study, the authors consider this decision problem and analyze the operational functions of personalized products. The authors hope to provide theoretical support in the operational management of manufacturers offering personalized products.

This study aims to investigate the impact of indium (In) content on the thermal properties, microstructure and mechanical properties of Sn-3Ag-3Sb-xIn (x = 0, 1, 2, 3, 4, 5 Wt.%) solders to enhance the performance of tin-based solder under demanding conditions and to meet the urgent need for high-reliability microelectronic interconnection materials in emerging sectors such as automotive intelligent technology, 5G communication technology and high-performance computing.

In this study, Sn-3Ag-3Sb-xIn solder alloys were prepared. The thermal properties of the solder alloys were characterised by differential scanning calorimetry. Subsequently, optical microscopy, scanning electron microscopy, X-ray diffraction and an electron probe X-ray microanalyser were used to analyse the influence of the In content on the microstructure of the solder. The mechanical properties of solder alloys were determined through tensile testing.

As the In content increased, the melting temperature of the Sn-3Ag-3Sb-xIn solder decreased, accompanied by less nucleation undercooling and an expanded melting range. The incorporation of In led to an enhancement in the yield and tensile strengths of the Sn-3Ag-3Sb-xIn solder alloys, but with a concomitant decrease in plasticity. In comparison to commercial Sn-3.0Ag-0.5Cu solder alloys, the yield strength and tensile strength of the Sn-3Ag-3Sb-3In alloy increased by 8.64 and 21.69 MPa, respectively, while the elongation decreased by 11.48%.

Sn-3Ag-3Sb-3In solder alloy was the most appropriate and expected comprehensive properties. The enhancements will provide substantial assistance and precise data references for the interconnection requirements in high-strength interconnection fields, such as automotive intelligent technology, 5G communication technology and high-performance computing.

The application of industrial robots in modern production is becoming increasingly widespread. In the context of flexible production lines, quickly and accurately identifying and grasping specified workpieces is particularly important. This study aims to propose a grasping scheme that combines traditional methods with deep learning to improve grasping accuracy and efficiency.

First, a dataset generation method is proposed, which constructs a point cloud dataset close to the real scene without the need for extensive data collection. Then, the 3D object detection algorithm PointPillars is improved based on the features of the scene point cloud, allowing for the analysis of part poses to achieve grasping. Finally, a grasp detection strategy is proposed to match the optimal grasp pose.

Experimental results show that the proposed method can quickly and easily construct high-quality datasets, significantly reducing the time required for preliminary preparation. Additionally, it can effectively grasp specified workpieces, significantly improving grasping accuracy and reducing computation time.

The main contribution of this paper is the integration of a novel dataset generation method, improvements to the PointPillars algorithm for 3D object detection and the development of an optimal grasp detection strategy. These advancements enable the grasping system to handle real-world scenarios efficiently and accurately, demonstrating significant improvements over traditional methods.