Influences of Solder Wetting on Self-Alignment Accuracy and Modeling for Optoelectronic Devices Assembly

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Ming Kong ◽  
Sungeun Jeon ◽  
Chiwon Hwang ◽  
Y. C. Lee
Keyword(s):  
Three Dimensional ◽  
Critical Factor ◽  
Cost Effective ◽  
Optimization Method ◽  
Alignment Accuracy ◽  
Factors Affecting ◽  
Solder Bumps ◽  
Solder Volume ◽  
Incomplete Wetting ◽  
External Forces

Solder self-alignment is an important phenomenon enabling cost-effective optoelectronics assembly. In this study, the wetting of Sn-rich solder to under bump metallization (UBM) pads is identified as a critical factor affecting self-alignment accuracy. Incomplete wetting of solder to the metallization pads is responsible for chip-to-substrate misalignment larger than 1 μm, while fabrication tolerances, such as solder volume variation and pad diameter deviation, only account for misalignments in the submicron range. To quantitatively investigate the effect of incomplete wetting on self-alignment accuracy, a three-dimensional (3D) model based on a force optimization method was developed. With the input parameters of incomplete solder metallurgical wetting area, position and diameter of metallization pad, volume of individual solder bumps, coefficient of solder surface tension, mass of the chip, external forces acting on the chip, and initial pick-and-place position of the chip before assembly, the model predicts the assembled position of the chip in terms of the misalignments in the X-Y plane and the rotation angle along the Z axis. The model further confirmed that incomplete wetting of solder is the most critical modulator among the undesirable factors affecting solder self-alignment accuracy.

Effects of Solder Wetting on Self-Alignment Accuracy and Modeling for Optoelectronics Assembly

2010 ◽  
Author(s):  
Ming Kong ◽  
Sungeun Jeon ◽  
Chiwon Hwang ◽  
Y. C. Lee
Keyword(s):  
Flip Chip ◽  
Critical Factor ◽  
Cost Effective ◽  
Alignment Accuracy ◽  
Factors Affecting ◽  
Solder Volume ◽  
Pick And Place ◽  
Design And Manufacturing ◽  
On Chip ◽  
External Forces

Solder self-alignment is one of the most important technologies for cost effective optoelectronics assembly. In this study, the wetting of Sn-rich solder to the metal pads of chip and substrate was identified as a critical factor significantly affecting self-alignment accuracy during the assembly. Insufficient wetting of solder to the metallization pads was responsible for large chip-to-substrate misalignment post-assembly, while fabrication deviations, such as solder volume variation and pad diameter deviation, only account for misalignments in the range of submicrons. To aid the design of flip-chip assemblies requiring high alignment accuracy, a force optimization model was developed and validated experimentally. With the input parameters of design and manufacturing process for optoelectronics flip-chip assembly using solders, such as insufficient solder metallurgical wetting areas, positions and diameters of metallization pads, volume of individual solder bump, coefficient of solder surface tension, mass of chip, external forces acting on chip, and initial pick-and-place position of chip before assembly, the model predicts the assembled position of the chip in terms of the misalignments in the X-Y planes and the rotation angles along the Z axis. The model further confirmed that insufficient wetting of solder is the most critical modulator among the undesirable factors affecting solder self-alignment accuracy.

scholarly journals Building stone quarries: resource evaluation by block modelling and unmanned aerial photogrammetric surveys

2021 ◽  
Vol 81 (1) ◽  
Author(s):  
Maxim Bogdanowitsch ◽  
Luís Sousa ◽  
Siegfried Siegesmund
Keyword(s):  
Three Dimensional ◽  
Block Size ◽  
Cost Effective ◽  
Building Stone ◽  
Raw Material ◽  
Factors Affecting ◽  
Conditioning Factors ◽  
Full Characterization ◽  
Three Dimensional Models

AbstractThe production of building stones shown an exponential growth in last decades as consequences of the demand and developments in the extraction and processing techniques. From the several conditioning factors affecting this industry, the geological constrains at quarry scale stands out as one of most important. Globalization and increasing competition in the building stone market require large raw material blocks to keep further processing as cost-effective as possible. Therefore, the potential extraction volume of in-situ stone blocks plays an important role in the yield of a dimensional stone quarry. The full characterization of the fracturing in the quarries comes up as fundamental in the assessment of the in-situ blocks volume/shape and potential extracted raw blocks. Identify the joint sets present, their spacing and the differences across the quarry demands a continuous assess during the quarry live span. Information from unmanned aerial vehicles helps in the field survey, namely trough digital surface models, orthophotos, and three-dimensional models. Also, the fracturing modelling by specific software programs is crucial to improve the block size assessment and the increase the quarry yield. In this research fracturing of twenty-one quarries of granite, limestone, marble, and slate from Portugal were assessed by combining field surveys with new techniques. From the studied quarries several cases were selected and presented to highlight the importance of this combined methodology in the fracturing assessment and how they can be helpful in the maximization of the resources and quarry management.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2338
Author(s):  
Sofia Agostinelli ◽  
Fabrizio Cumo ◽  
Giambattista Guidi ◽  
Claudio Tomazzoli
Keyword(s):  
Artificial Intelligence ◽  
Renewable Energy ◽  
Energy Management ◽  
Three Dimensional ◽  
Cost Effective ◽  
Automation System ◽  
Climate Conditions ◽  
Digital Twin ◽  
Building Energy Management ◽  
Computing Paradigm

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

scholarly journals Factors Affecting the Lut Desert Tourism in Iran: Developing an Interpretive-Structural Model

2021 ◽  
Vol 13 (13) ◽  
pp. 7245
Author(s):  
Beniamino Murgante ◽  
Mohammad Eskandari Sani ◽  
Sara Pishgahi ◽  
Moslem Zarghamfard ◽  
Fatemeh Kahaki
Keyword(s):  
Sampling Method ◽  
Structural Model ◽  
Tourism Development ◽  
Cost Effective ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Factors Affecting ◽  
Purposive Sampling ◽  
Interpretive Structural Model ◽  
Lut Desert

The Lut desert is one of the largest and most attractive deserts in Iran. The value of desert tourism remains unclear for Iran’s economy and has only recently been taken into consideration by the authorities, although its true national and international value remains unclear. This study was aimed at investigating the factors that influence tourism development in the Lut desert. Data collected through the purposive sampling method was analyzed using Interpretive Structural Modeling and the MICMAC Analysis. According to the results, cost-effective travel expenses, security, and safety provided in the desert, together with appropriate media advertising and illustration of the Lut desert (branding) are the leading factors that influence tourism in the Lut desert in Iran. This paper highlighted the importance of desert tourism, especially in this region.

scholarly journals Economic Development Based on a Mathematical Model: An Optimal Solution Method for the Fuel Supply of International Road Transport Activity

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2963
Author(s):  
Melinda Timea Fülöp ◽  
Miklós Gubán ◽  
György Kovács ◽  
Mihály Avornicului
Keyword(s):  
Decision Making ◽  
Ad Hoc ◽  
Market Competition ◽  
Optimal Solution ◽  
Cost Savings ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimal Decision ◽  
Environmental Damage ◽  
Fuel Cost

Due to globalization and increased market competition, forwarding companies must focus on the optimization of their international transport activities and on cost reduction. The minimization of the amount and cost of fuel results in increased competition and profitability of the companies as well as the reduction of environmental damage. Nowadays, these aspects are particularly important. This research aims to develop a new optimization method for road freight transport costs in order to reduce the fuel costs and determine optimal fueling stations and to calculate the optimal quantity of fuel to refill. The mathematical method developed in this research has two phases. In the first phase the optimal, most cost-effective fuel station is determined based on the potential fuel stations. The specific fuel prices differ per fuel station, and the stations are located at different distances from the main transport way. The method developed in this study supports drivers’ decision-making regarding whether to refuel at a farther but cheaper fuel station or at a nearer but more expensive fuel station based on the more economical choice. Thereafter, it is necessary to determine the optimal fuel volume, i.e., the exact volume required including a safe amount to cover stochastic incidents (e.g., road closures). This aspect of the optimization method supports drivers’ optimal decision-making regarding optimal fuel stations and how much fuel to obtain in order to reduce the fuel cost. Therefore, the application of this new method instead of the recently applied ad-hoc individual decision-making of the drivers results in significant fuel cost savings. A case study confirmed the efficiency of the proposed method.

Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength

2021 ◽  
pp. 095441192098703
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Experimental Data ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Three Dimensional ◽  
Optimization Method ◽  
Weight Lifting ◽  
Joint Torque ◽  
Maximum Weight ◽  
Angular Velocities ◽  
Asymmetric Lifting

In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.

scholarly journals Optimization of Polymer Extrusion Die Based on Response Surface Method

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1043 ◽  
Author(s):  
Amin Razeghiyadaki ◽  
Dichuan Zhang ◽  
Dongming Wei ◽  
Asma Perveen
Keyword(s):  
Three Dimensional ◽  
Theoretical Work ◽  
Optimization Method ◽  
Extrusion Die ◽  
Surface Method ◽  
Spline Fitting ◽  
Die Profile ◽  
Response Optimization ◽  
Geometric Variables ◽  
Volume Method

A coupled surface response optimization method with a three-dimensional finite volume method is adopted in this study to identify five independent geometric variables of the die interior that provides a design with the lowest velocity variance at the exit of the coat-hanger extrusion die. Two of these five geometric variables represent the manifold dimension while the other three variables represent the die profile. In this method, B-spline fitting with four points was used to represent the die profile. A comparison of the optimized die obtained in our study and the die with a geometry derived by a previous theoretical work shows a 20.07% improvement in the velocity distribution at the exit of the die.

Trends in pediatric imaging: ultrasound

2013 ◽  
Vol 54 (9) ◽  
pp. 1096-1105 ◽  
Author(s):  
Ansgar Berg ◽  
Gottfried Greve
Keyword(s):  
Heart Diseases ◽  
Three Dimensional ◽  
Cost Effective ◽  
Clinical Work ◽  
Ventricular Volume ◽  
Tissue Doppler ◽  
Doppler Imaging ◽  
Strain And Strain Rate ◽  
2D Echocardiography ◽  
Systolic And Diastolic Function

For the last three decades, two-dimensional (2D) echocardiography and Doppler echocardiography have been the primary imaging modalities for the diagnosis and management of heart disease in infants, children, and adolescents. These methods are non-invasive, highly sensitive, and cost-effective, and widely available, making them very useful in clinical work. During this period, the anatomic and hemodynamic abnormalities associated with different congenital and acquired pediatric heart diseases have been well outlined by echocardiography. Recent advances in computer technology, signal processing, and transducer design have allowed the capabilities of pediatric echocardiography to be expanded beyond qualitative 2D imaging and blood flow Doppler analysis. New modalities such as three-dimensional echocardiography, tissue Doppler imaging and speckle tracking echocardiography have been used to evaluate parameters such as ventricular volume, myocardial velocity, regional strain, and strain rate, providing new insight into cardiovascular morphology and ventricular systolic and diastolic function. Accordingly, a comprehensive and sophisticated quantification of ventricular function is now part of most echocardiography protocols. Use of measurements adjusted for body size and age is common practice today. These developments have further strengthened the position of echocardiography in pediatric cardiology.

Packing Optimization by Enhanced Rubber Band Analogy

2005 ◽  
Author(s):  
Hong Dong ◽  
Georges M. Fadel ◽  
Vincent Y. Blouin
Keyword(s):  
Three Dimensional ◽  
Optimization Method ◽  
Rubber Band ◽  
Volume Relaxation ◽  
New Developments ◽  
Packing Problems ◽  
Rubber Balloon ◽  
Elastic Forces ◽  
Reaction Forces ◽  
Packing Optimization

In this paper, some new developments to the packing optimization method based on the rubber band analogy are presented. This method solves packing problems by simulating the physical movements of a set of objects wrapped by a rubber band in the case of two-dimensional problems or by a rubber balloon in the case of three-dimensional problems. The objects are subjected to elastic forces applied by the rubber band to their vertices as well as reaction forces when contacts between objects occur. Based on these forces, objects translate or rotate until maximum compactness is reached. To improve the compactness further, the method is enhanced by adding two new operators: volume relaxation and temporary retraction. These two operators allow temporary volume (elastic energy) increase to get potentially better packing results. The method is implemented and applied for three-dimensional arbitrary shape objects.

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