Raed Al Athamneh

Pilot overhead poses a significant challenge in mmWave massive multiple-input multiple-output (MIMO) systems, as it fundamentally limits the accurate acquisition of channel state information (CSI). In this paper, we propose an enhanced adaptive channel estimation technique that leverages compressive sensing (CS) principles to effectively mitigate pilot overhead while maintaining high estimation accuracy. The proposed approach combines compressive sampling matching pursuit (CoSaMP) and sparsity adaptive matching pursuit (SAMP) algorithms, augmented by a novel iterative reweighting strategy and adaptive thresholding mechanism. The simulation results demonstrate that the proposed method achieves superior normalized mean square error (NMSE) performance compared to traditional CS-based techniques. Furthermore, the proposed technique achieves a substantial reduction in computational complexity and pilot overhead compared to traditional channel estimation methods, offering significant improvements in the performance of mmWave MIMO systems.

The Multi-skilled Resource Constrained Project Scheduling Problem (MS-RCPSP) is a complex and multi-faceted problem that involves scheduling activities whilst considering various resource constraints. These constraints include limited availability of workers, equipment, and materials, with each activity requiring a minimal set of skills to be executed. Furthermore, for a better resemblance to reality, workers/machines are assumed to be multi-skilled/multi-purpose posing another dimension of complexity to the problem. The objective is to minimize project duration, cost, or other relevant criteria while accounting for the inherent resources flexibility. This paper provides a systematic review of the literature pertaining to MS-RCPSP, and an in-depth analysis of 171 papers published between 2000 and 2021 inclusive. The conducted bibliometric analysis identifies the top contributing authors, most influential papers, existing research tendencies, and thematic research topics within the field. In addition, this review highlights different aspects of the MS-RCPSP, spanning the significance of performance measures, solution approaches, application areas, and the incorporation of time constraints. While project completion time, cost, and tardiness are common performance indicators, other measures such as multi-skilled staff assignment and schedule robustness are also deemed important. Although various methods have been employed to solve the MS-RCPSP including exact and approximate approaches, the selection of the most-suited approach depends on the problem’s scale, complexity, and constraints, necessitating careful consideration of each method’s strengths and weaknesses. Interestingly, several studies have jointly addressed resource and time constraints in the context of MS-RCPSP, often considering tardiness, and have proposed different algorithms, models, and metaheuristics to tackle these challenges. This paper clearly highlights research gaps and promising avenues for future research. This work provides valuable insights for project managers to effectively schedule tasks in the presence of multiple flexible resources.

The accuracy of reliability models is one of the most problematic issues that must be considered for the life of electronic assemblies, particularly those used for critical applications. The reliability of electronics is limited by the fatigue life of interconnected solder materials, which is influenced by many factors. This paper provides a method to build a robust machine-learning reliability model to predict the life of solder joints in common applications. The impacts of combined fatigue and creep stresses on solder joints are also investigated in this paper. The common alloy used in solder joint fabrication is SAC305 (Sn–Ag–Cu). The test vehicle includes individual solder joints of SAC305 alloy assembled on a printed circuit board. The effects of testing temperature, stress amplitude, and creep dwell time on the life of solder joints were considered. A two-parameter Weibull distribution was utilized to analyze the fatigue life. Inelastic work and plastic strain were extracted from the stress–strain curves. Then, Artificial Neural Networks (ANNs) were used to build a machine learning model to predict characteristic life obtained from the Weibull analysis. The inelastic work and plastic stains were also considered in the ANN model. Fuzzy logic was used to combine the process parameters and fatigue properties and to construct the final life prediction model. Then a relationship equation between the comprehensive output measure obtained from the fuzzy system and the life was determined using a nonlinear optimizer. The results indicated that increasing the stress level, testing temperature, and creep dwell time decreases reliability. The case of long creep dwell time at elevated temperatures is worst in terms of impact on reliability. Finally, a single robust reliability model was computed as a function of the fatigue properties and process parameters. A significant enhancement of the prediction model was achieved compared to the stress–life equations.

Frequent failures in interconnected materials in microelectronic packages play a vital role in determining the reliability of electronic devices. Differences in the thermal expansion coefficients of the solder joint, printed circuit board (PCB), and electronic package are a major source of applied stress on solder joints. Due to health concerns and governmental regulations associated with using leaded solder alloys, SAC solder alloys are commonly used as an alternative to Pb-alloys because of their outstanding solderability and reliability. The shear fatigue creep accelerated test at different load levels (16 MPa, 20 MPa, and 24 MPa) was implemented in this study by using a universal micro-testing machine to investigate solder joint reliability. The creep effects were demonstrated by employing 60 seconds of dwell time for each alternating stress value and comparing its impact on solder joint reliability with the fatigue test results. The accelerated test was applied to SAC305 (96.5% Sn, 3% Ag, 0.5% Cu) solder joints with OSP surface finish at different testing temperatures (25°C, 60°C, and 100°C). Seven replicates were considered as a sample size for the reliability analysis. A two-parameter Weibull distribution was employed as the dominant distribution to describe the fatigue behavior at each condition. The characteristic life and shape parameters at each condition were extracted from the obtained Weibull models. The stress–life equation was used to estimate the reliability performance of the solder joints against fluctuations in stress amplitude at differing testing temperatures. The inelastic work per cycle and plastic strain were calculated from the acquired hysteresis loop under each condition. Coffin–Manson and Morrow energy models illustrate the relationships between fatigue life versus plastic strain and inelastic work, respectively. The effects of the oscillated testing temperature on the stress–life model, Morrow energy model, and Coffin–Manson model were elaborated using the Arrhenius equation. The results indicated a severe degradation of fatigue life with increased testing temperature. Raising the stress amplitude had a less significant impact on fatigue life reduction than increasing the testing temperature. The reliability prediction models, as a function of the fatigue properties and testing temperature, were derived from the Arrhenius, Coffin–Manson, and Morrow energy models. The acquired prediction equations produced acceptable goodness-of-fit values. Finally, a general reliability model with a 99% adequacy value (R ² ) was constructed as a function of testing temperature and stress amplitude.

This paper investigates the views of healthcare researchers and professionals on the implementation of the Quality Management System (QMS) approach using a 5-point Likert scale survey. Researchers and healthcare professionals who observed or participated in QMS implementation were surveyed. Multiple channels, including occupational societies, social networking, i.e., LinkedIn, hospital’s directories, award recipients, academic researchers, and professional connections, made it possible to reach this particular sample. Participants were surveyed using a series of questions with a total of 56 questions. The survey was administrated through the web portal of Qualtrics and then analyzed both on Qualtrics and SPSS software packages. Descriptive Statistics, Exploratory Factor Analysis (EFA), and Linear Regression were employed to draw conclusions. The final sample group consisted of 71 participants representing a range of healthcare settings. EFA was conducted, producing a model of 10 emergent factors and an outcome for total improvement. Regression modeling revealed the Critical Success Factors (CSFs) and the interaction between emergent factors. The results indicated that QMS Implementation Culture, Structure, and Managerial Training are critical to the QMS implementation success. This research helps quality professionals enhance their ability to prioritize elements affecting the successful implementation of the QMS.

Multi-response optimization problems investigation is a crucial element in initiatives designed to enhance quality and overall productivity for manufacturing processes. Since no particular algorithm can be employed for all multi-response problems, defining the method that is utilized as a problem-solving technique is a vital step in the process factors optimization. Identifying a formal procedure of implementing the improvement approach in a multi-criteria decision-making problem is a critical need to ensure the consistency and sustainability of the enhancement methods. In this study, a Plan–Do–Check–Act (PDCA) framework is implemented for a case study in the food industry under which a multi-response optimization problem is investigated. The design of experiment (DOE) is used to examine the effect of process parameters on the quality responses by using the Taguchi method to find the optimal setting for each parameter. An orthogonal array (OA) and signal-to-noise (SNR) ratio is employed to investigate the performance characteristics. Each performance characteristic is then converted into a signal-to-noise ratio, and all the ratios are then fed into a fuzzy model to produce a single comprehensive output measure (COM). The average COM values for various factor levels are calculated, and the level that maximizes the COM value for each factor is identified as the optimal level. Results indicated the effectiveness of the applied method to find the optimal factor levels for the multi-response optimization problem under study. The global optimal factor levels that are driven from the fuzzy logic for the studied parameters are 1250, 40, 7.5, and 1:2, for the speed, frying time, cooking time, and the coating ratio, respectively. Means of all the studied quality characteristics were closer to the target values when compared with the initial factors’ settings.

The failure of one solder joint out of the hundreds of joints in a system compromises the reliability of the electronics assembly. Thermal cycling is a result of both creep–fatigue mechanisms working together. To better understand the failure process in thermal cycling, it is crucial to analyze both the effects of creep and fatigue mechanisms in a methodical manner. In this work, individual solder junctions are subjected to accelerated shear fatigue testing to investigate the effects of creep and fatigue on joint dependability at room temperature. A modified fixture is used to conduct fatigue tests on an Instron 5948 micromechanical tester. SAC305 joints with an OSP surface finish were cycled under stress control at first, and then the strain was maintained for a set amount of time. In this investigation, three stress amplitudes of 16, 20, and 24 MPa are used, together with varying residence periods of 0, 10, 60, and 180 s. The fatigue life of solder junctions is described for each testing condition using the two-parameter Weibull distribution. Additionally, as a function of stress amplitude and residence time, a dependability model is created. For each testing scenario, the progression of the stress–strain loops was studied. By quantifying relevant damage metrics, such as plastic work per cycle and plastic strain at various testing circumstances, the damage due to fatigue is distinguished from creep. To investigate the relationships between plastic work and plastic strain with fatigue life, the Coffin–Manson and Morrow Energy model is used. The results indicate that using greater stress magnitudes or longer dwell periods significantly shortens fatigue life and dramatically increases plastic work and plastic strain. The housing impact is significant; in some circumstances, testing with a longer dwelling period and lower stress amplitude resulted in more damage than testing with a shorter dwelling period and higher stress levels. When illustrating the fatigue behavior of solder junctions under various stress amplitudes or dwellings, the Coffin–Manson and Morrow Energy model were both useful. In the end, general reliability models are developed as functions of plastic work and plastic strain.

The mechanical and fatigue properties of microelectronic interconnection materials are important issues in critical applications in the life of electronic assemblies. Due to the growth in the applications of electronic components in new technological products used in tough conditions, evaluating the reliability of solder alloys has become crucial to the prediction of product life. SAC (Sn-Ag-Cu) solder alloys are common lead-free alloys used to form solder joints. In the current study, the reliability of individual SAC305 solder joints in actual setting conditions with an organic solderability preservative (OSP) surface finish was examined using an accelerated shear fatigue test at different load levels (16 MPa, 20 MPa, and 24 MPa). Four operating temperature levels (−10, 25, 60, and 100 °C) were also used. Seven samples were utilized at each experimental condition. An orthogonal array (L12) was employed for this experiment. The fatigue behavior of the SAC305 solder joints in actual setting conditions was described by a two-parameter Weibull distribution. The characteristic life and the shape parameter were extrapolated from the Weibull distribution for each experimental condition. Characteristic life was employed to represent the fatigue resistance of the solder joints. For each sample, the inelastic work per cycle and plastic deformation were determined. The results indicated a notable increase in the inelastic work per cycle and the plastic strain as a result of increasing either the stress load or the working temperature. Combinations of stress amplitude, working temperature, inelastic work, and plastic deformation were applied as inputs to the fuzzy system for computing a comprehensive output measure (COM-Value) using the Mamdani method. A negative relationship was observed between the solder life and the four fuzzy inputs. To fuzzify the inputs of the fuzzy system, two membership functions, “MFs”, were formed for each input, and five MFs were set for the output. The center-of-gravity (COG) theorem was utilized as a defuzzification method in the fuzzy inference system. The characteristic life of the solder joints was predicted by the COM-Value, which was used as an independent variable. Finally, The COM-Value was used to generate a general predicted reliability model for SAC305 solder joints with an acceptable model adequacy index.

The interconnection materials that are used in electronics assembly fabrication operating in harsh environmental conditions are frequently exposed to different types of mechanical stress and fatigue. Fatigue resistance does significantly affect the reliability of electronic assemblies. SAC alloys are commonly utilized in electronic assemblies' fabrication operating in harsh conditions due to their superior mechanical and fatigue properties. Hence, this provokes the need to model and perform a detailed statistical analysis of their reliability behavior. SAC305 is commonly used as a lead-free alloy which is being utilized as a replacement of the eutectic SnPb alloy. The main goal of this study is to investigate the effect of aging temperature on the fatigue and mechanical behavior of SAC305 solder joints using accelerated shear-fatigue and shear tests. An Instron Microtester machine with a customized fixture was used to perform the tests. A two-factor test matrix for the fatigue test was constructed; where the stress amplitude has three levels (16, 20, and 24MPa) and the aging temperature has four levels (0, 50, 100, and 150∘C). Microstructural analysis was performed on samples aged at different temperatures using SEM microscopy to address the evolutions in the precipitates size and the intermetallic compound (IMC) layer. A stress-life equation and an Arrhenius model are used to develop a general reliability model as a function of aging temperature and stress amplitude. The relationship between the fatigue life and the inelastic work were analyzed using Morrow Energy equation. The results indicate a major reduction in the reliability and shear strength of the solder joints with increasing the aging temperature. Aging has been also found to have a more notable effect on the fatigue life when compared to shear strength.