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1 – 10 of over 3000George Besseris and Panagiotis Tsarouhas
The study aims to provide a quick-and-robust multifactorial screening technique for early detection of statistically significant effects that could influence a product's life-time…
Abstract
Purpose
The study aims to provide a quick-and-robust multifactorial screening technique for early detection of statistically significant effects that could influence a product's life-time performance.
Design/methodology/approach
The proposed method takes advantage of saturated fractional factorial designs for organizing the lifetime dataset collection process. Small censored lifetime data are fitted to the Kaplan–Meier model. Low-percentile lifetime behavior that is derived from the fitted model is used to screen for strong effects. A robust surrogate profiler is employed to furnish the predictions.
Findings
The methodology is tested on a difficult published case study that involves the eleven-factor screening of an industrial-grade thermostat. The tested thermostat units are use-rate accelerated to expedite the information collection process. The solution that is provided by this new method suggests as many as two active effects at the first decile of the data which improves over a solution provided from more classical methods.
Research limitations/implications
To benchmark the predicted solution with other competing approaches, the results showcase the critical first decile part of the dataset. Moreover, prediction capability is demonstrated for the use-rate acceleration condition.
Practical implications
The technique might be applicable to projects where the early reliability improvement is studied for complex industrial products.
Originality/value
The proposed methodology offers a range of features that aim to make the product reliability profiling process faster and more robust while managing to be less susceptible to assumptions often encountered in classical multi-parameter treatments.
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Vicente-Segundo Ruiz-Jacinto, Karina-Silvana Gutiérrez-Valverde, Abrahan-Pablo Aslla-Quispe, José-Manuel Burga-Falla, Aldo Alarcón-Sucasaca and Yersi-Luis Huamán-Romaní
This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite…
Abstract
Purpose
This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R2 = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions.
Design/methodology/approach
This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R2 = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior.
Findings
The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R2” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction.
Originality/value
The authors confirm the originality of this paper.
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Jussi Putaala, Olli Salmela, Olli Nousiainen, Tero Kangasvieri, Jouko Vähäkangas, Antti Uusimäki and Jyrki Lappalainen
The purpose of this paper is to describe the behavior of different lead-free solders (95.5Sn3.8Ag0.7Cu, i.e. SAC387 and Sn7In4.1Ag0.5Cu, i.e. SAC-In) in thermomechanically loaded…
Abstract
Purpose
The purpose of this paper is to describe the behavior of different lead-free solders (95.5Sn3.8Ag0.7Cu, i.e. SAC387 and Sn7In4.1Ag0.5Cu, i.e. SAC-In) in thermomechanically loaded non-collapsible ball grid array (BGA) joints of a low-temperature co-fired ceramic (LTCC) module. The validity of a modified Engelmaier’s model was tested to verify its capability to predict the characteristic lifetime of an LTCC module assembly implementable in field applications.
Design/methodology/approach
Five printed wiring board (PWB) assemblies, each carrying eight LTCC modules, were fabricated and exposed to a temperature cycling test over a −40 to 125°C temperature range to determine the characteristic lifetimes of interconnections in the LTCC module/PWB assemblies. The failure mechanisms of the test assemblies were verified using scanning acoustic microscopy, scanning electron microscopy (SEM) and field emission SEM investigation. A stress-dependent Engelmaier’s model, adjusted for plastic-core solder ball (PCSB) BGA structures, was used to predict the characteristic lifetimes of the assemblies.
Findings
Depending on the joint configuration, characteristic lifetimes of up to 1,920 cycles were achieved in the thermal cycling testing. The results showed that intergranular (creep) failures occurred primarily only in the joints containing Sn7In4.1Ag0.5Cu solder. Other primary failure mechanisms (mixed transgranular/intergranular, separation of the intermetallic compound/solder interface and cracking in the interface between the ceramic and metallization) were observed in the other joint configurations. The modified Engelmaier’s model was found to predict the lifetime of interconnections with good accuracy. The results confirmed the superiority of SAC-In solder over SAC in terms of reliability, and also proved that an air cavity structure of the module, which enhances its radio frequency (RF) performance, did not degrade the reliability of the second-level interconnections of the test assemblies.
Originality/value
This paper shows the superiority of SAC-In solder over SAC387 solder in terms of reliability and verifies the applicability of the modified Engelmaier’s model as an accurate lifetime prediction method for PCSB BGA structures for the presented LTCC packages for RF/microwave telecommunication applications.
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Chih‐Fong Tsai, Ya‐Han Hu, Chia‐Sheng Hung and Yu‐Feng Hsu
Customer lifetime value (CLV) has received increasing attention in database marketing. Enterprises can retain valuable customers by the correct prediction of valuable customers…
Abstract
Purpose
Customer lifetime value (CLV) has received increasing attention in database marketing. Enterprises can retain valuable customers by the correct prediction of valuable customers. In the literature, many data mining and machine learning techniques have been applied to develop CLV models. Specifically, hybrid techniques have shown their superiorities over single techniques. However, it is unknown which hybrid model can perform the best in customer value prediction. Therefore, the purpose of this paper is to compares two types of commonly‐used hybrid models by classification+classification and clustering+classification hybrid approaches, respectively, in terms of customer value prediction.
Design/methodology/approach
To construct a hybrid model, multiple techniques are usually combined in a two‐stage manner, in which the first stage is based on either clustering or classification techniques, which can be used to pre‐process the data. Then, the output of the first stage (i.e. the processed data) is used to construct the second stage classifier as the prediction model. Specifically, decision trees, logistic regression, and neural networks are used as the classification techniques and k‐means and self‐organizing maps for the clustering techniques to construct six different hybrid models.
Findings
The experimental results over a real case dataset show that the classification+classification hybrid approach performs the best. In particular, combining two‐stage of decision trees provides the highest rate of accuracy (99.73 percent) and lowest rate of Type I/II errors (0.22 percent/0.43 percent).
Originality/value
The contribution of this paper is to demonstrate that hybrid machine learning techniques perform better than single ones. In addition, this paper allows us to find out which hybrid technique performs best in terms of CLV prediction.
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Against the background of the fact that solder joints crack owing to thermal cycling, the method of predicting the lifetime of a solder joint is critically discussed. The…
Abstract
Against the background of the fact that solder joints crack owing to thermal cycling, the method of predicting the lifetime of a solder joint is critically discussed. The conclusion is that the working conditions of the solder joints have to be carefully analysed and to be brought into agreement with the material properties. On the basis of experimental values, it is shown how this can be done. Creep, relaxation and fatigue of solder joints are discussed.
Yanruoyue Li, Guicui Fu, Bo Wan, Zhaoxi Wu, Xiaojun Yan and Weifang Zhang
The purpose of this study is to investigate the effect of electrical and thermal stresses on the void formation of the Sn3.0Ag0.5Cu (SAC305) lead-free ball grid array (BGA) solder…
Abstract
Purpose
The purpose of this study is to investigate the effect of electrical and thermal stresses on the void formation of the Sn3.0Ag0.5Cu (SAC305) lead-free ball grid array (BGA) solder joints and to propose a modified mean-time-to-failure (MTTF) equation when joints are subjected to coupling stress.
Design/methodology/approach
The samples of the BGA package were subjected to a migration test at different currents and temperatures. Voltage variation was recorded for analysis. Scanning electron microscope and electron back-scattered diffraction were applied to achieve the micromorphological observations. Additionally, the experimental and simulation results were combined to fit the modified model parameters.
Findings
Voids appeared at the corner of the cathode. The resistance of the daisy chain increased. Two stages of resistance variation were confirmed. The crystal lattice orientation rotated and became consistent and ordered. Electrical and thermal stresses had an impact on the void formation. As the current density and temperature increased, the void increased. The lifetime of the solder joint decreased as the electrical and thermal stresses increased. A modified MTTF model was proposed and its parameters were confirmed by theoretical derivation and test data fitting.
Originality/value
This study focuses on the effects of coupling stress on the void formation of the SAC305 BGA solder joint. The microstructure and macroscopic performance were studied to identify the effects of different stresses with the use of a variety of analytical methods. The modified MTTF model was constructed for application to SAC305 BGA solder joints. It was found suitable for larger current densities and larger influences of Joule heating and for the welding ball structure with current crowding.
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Yuqing Xu, Guang-Ling Song and Dajiang Zheng
This study aims to provide a model to predict the service life of a thick organic coating.
Abstract
Purpose
This study aims to provide a model to predict the service life of a thick organic coating.
Design/methodology/approach
A series of thin coating films are rapidly tested under the same exposure condition as the thick coating in its service condition by means of electrochemical impedance spectroscopy, scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction.
Findings
The validity of the model is successfully verified. The long-term protectiveness or service life of a thick organic coating can be rapidly predicted.
Originality/value
The prediction model does not require long-term experiments or any test that may alter the degradation mechanism of the thick coating.
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Cristina Ledro, Anna Nosella and Andrea Vinelli
Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic…
Abstract
Purpose
Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic overview of the field, thus unveiling gaps and providing promising paths for future research.
Design/methodology/approach
A total of 212 peer-reviewed articles published between 1989 and 2020 were extracted from the Scopus database, and 2 bibliometric techniques were used: bibliographic coupling and keywords’ co-occurrence.
Findings
Outcomes of the bibliometric analysis enabled the authors to identify three main subfields of the AI literature within the CRM domain (Big Data and CRM as a database, AI and machine learning techniques applied to CRM activities and strategic management of AI–CRM integrations) and capture promising paths for future development for each of these subfields. This study also develops a three-step conceptual model for AI implementation in CRM, which can support, on one hand, scholars in further deepening the knowledge in this field and, on the other hand, managers in planning an appropriate and coherent strategy.
Originality/value
To the best of the authors’ knowledge, this study is the first to systematise and discuss the literature regarding the relationship between AI and CRM based on bibliometric analysis. Thus, both academics and practitioners can benefit from the study, as it unveils recent important directions in CRM management research and practices.
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O. Nousiainen, O. Salmela, J. Putaala and T. Kangasvieri
The purpose of this paper is to describe the effect of indium alloying on the thermal fatigue endurance of Sn3.8Ag0.7Cu solder in low‐temperature co‐fired ceramic (LTCC) modules…
Abstract
Purpose
The purpose of this paper is to describe the effect of indium alloying on the thermal fatigue endurance of Sn3.8Ag0.7Cu solder in low‐temperature co‐fired ceramic (LTCC) modules with land grid array (LGA) joints and the feasibility of using a recalibrated Engelmaier model to predict the lifetime of LGA joints as determined with a test assembly.
Design/methodology/approach
Test assemblies were fabricated and exposed to a temperature cycling test over a temperature range of −40‐125°C. Organic printed wiring board (PWB) material with a low coefficient of thermal expansion was used to reduce the global thermal mismatch of the assembly. The characteristic lifetime, θ, of the test assemblies was determined using direct current resistance measurements. The metallurgy and failure mechanisms of the interconnections were verified using scanning acoustic microscopy, an optical microscope with polarized light, and scanning electron microscopy/energy dispersive spectrometry (SEM/EDS) investigations. Lifetime predictions of the test assemblies were calculated using the recalibrated Engelmaier model.
Findings
This work showed that indium alloying increased the characteristic lifetime of LGA joints by 15 percent compared with Sn3.8Ag0.7Cu joints. SEM/EDS analysis showed that alloying changed the composition, size, and distribution of intermetallic compounds within the solder matrix. It was also observed that a solid‐state phase transformation (Cu,Ni)6Sn5(→ (Ni,Cu)3Sn4 occurred at the Ni/(Cu,Ni)6Sn5 interface. Moreover, the results pointed out that individual recalibration curves for ceramic package/PWB assemblies with high (≥ 10 ppm/°C) and low (≈ 3‐4 ppm/°C) global thermal mismatches and different package thicknesses should be determined before the lifetime of LGA‐type assemblies can be predicted accurately using the recalibrated Engelmaier model.
Originality/value
The results proved that indium alloying of LGA joints can be done using In‐containing solder on pre‐tinned pads of an LTCC module, despite the different liquidus temperatures of the In‐containing and Sn3.8Ag0.7Cu solders. The characteristic metallurgical features and enhanced thermal fatigue endurance of the In‐alloyed SnAgCu joints were also determined. Finally, this work demonstrated the problems that exist in predicting the lifetime of ceramic packages with LGA joints using analytical modeling, and proposals for developing the recalibrated Engelmaier model to achieve more accurate results with different ceramic packages/PWB assemblies are given.
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Nikolai Petrovich Anosov, Vladimir Nikolaevich Skorobogatykh, Lyubov’ Yur’yevna Gordyuk, Vasilii Anatol’evich Mikheev, Egor Vasil’yevich Pogorelov and Valentin Kuz’mich Shamardin
The purpose of this paper is to consider a procedure of water-water energetic reactor (WWER) reactor pressure vessel (RPV) lifetime prediction at the stages of design and lifetime…
Abstract
Purpose
The purpose of this paper is to consider a procedure of water-water energetic reactor (WWER) reactor pressure vessel (RPV) lifetime prediction at the stages of design and lifetime extension using the standard irradiation embrittlement parameters as defined in regulatory documents. A comparison is made of the brittle fracture resistance (BFR) values evaluated using two criteria: shift in the critical brittleness temperature ΔTc or shift in the brittle-to-ductile transition temperature ΔTp and without shifts (Tc and Tp).
Design/methodology/approach
The radiation resistance was determined using the following three approaches: calculation based on standard values ΔTc and Tc0 or ΔTp and Tp0 (a level of excessive conservatism); calculation based on standard value ΔTc and actual value Tc0 or actual values ΔTp and Tp0 (the level of realistic conservatism); or calculation based on actual values of Tc and Tc0 or Tp and Tp0 (the level of actual conservatism). The BFR was evaluated based on the results of testing the specimens subjected to irradiation in research reactors as well as surveillance specimens subjected to irradiation immediately under operating conditions.
Findings
The excessive conservatism in determining the actual lifetime of nuclear reactor vessel materials can be eliminated by using the immediate values of critical brittleness temperature and ductile-to-brittle transition temperature.
Originality/value
Obtained results can be applied to extend WWER vessel operating time at the stages of designing and operation due to substantiated decrease in conservatism. And it will allow carrying out a statistical substantiated assessment of the resistance to brittle fracture of the RPV steels.
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