Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Current trends in structural development and modification strategies for metal-organic frameworks (MOFs) towards photocatalytic H2 production: A review

Photocatalytic H₂ generation using semiconductor photocatalysts is considered as a cost-effective and eco-friendly technology for solar to energy conversion; however, the present photocatalysts have been recognized to depict low efficiency. Currently, porous coordination polymers known as metal-organic frameworks (MOFs) constituting flexible and modifiable porous structure and having excess active sites are considered to be appropriate for photocatalytic H₂ production. This review highlights current progress in structural development of MOF materials along with modification strategies for enhanced photoactivity. Initially, the review discusses the photocatalytic H₂ production mechanism with the concepts of thermodynamics and mass transfer with particular focus on MOFs. Elaboration of the structural categories of MOFs into Type I, Type II, Type III and classification of MOFs for H₂ generation into transition metal based, post-transition metal based, noble-metal based and hetero-metal based has been systematically discussed. The review also critically deliberate various modification approaches of band engineering, improvement of charge separation, efficient irradiation utilization and overall efficiency of MOFs including metal modification, heterojunction formation, Z-scheme formation, by introducing electron mediator, and dye based composites. Also, the MOF synthesized derivatives for photocatalytic H₂ generation are elaborated. Finally, future perspectives of MOFs for H₂ generation and approaches for efficiency improvement have been suggested.     

LBM investigation of a Cu-water nanofluid over various configurations of pipes in the mixed convection flow

Increasing the heat capacity of heat exchangers is a crucial need for modern devices. The thermal conductivity of the usual fluids and the Nusselt (Nu) number of flows containing such fluids are two bottlenecks in the way of increasing heat delivery in the heat exchangers. For this reason, nanofluids have been introduced. The effect of utilizing a Cu-water nanofluid as a coolant of two hot pipes in a square cavity is investigated numerically with a two-component lattice Boltzmann method. The volume fraction of nanoparticles is assumed to be constant (0.03) while the Richardson (Ri) number varies from 0.02 to 20. Results show that the effectiveness of nanoparticles is better observed in the natural convection mode. However, sedimentation is also very probable at high Ri numbers, which significantly reduces the effectiveness of the nanoparticles. Configurations which produce a natural convection stream similar to the forced convection one as well as the configurations with high spacing and hence, low heat stream interactions, are the best choices for a uniform heat rate from the pipes.     

The dynamic effect of Micro-MHD convection on bubble grown at a horizontal microelectrode

Relatively low efficiency is the biggest obstacle to the popularization of water electrolysis, which is a particularly feasible way to produce super-pure hydrogen. Imposing a magnetic field can increase the hydrogen production efficiency of water electrolysis. However, the enhancement's detailed mechanism still lacks an insightful understanding of the bubbles' micro vicinity. Our recent work aims to understand why the micro-magnetohydrodynamic (MHD) convection hinders single bubbles' detachment on the microelectrode. A water electrolysis experiment by microelectrode is performed under an electrode-normal magnetic field, and dynamic analysis of the single bubble growing on microelectrodes is performed. The variation of bubble diameter with time in the presence or absence of the magnetic field was measured, and the forces acting on the bubble were quantified. The result shows that the micro-MHD convection, induced by Lorentz force, can give rise to a downward hydrodynamic pressure force that will not appear in large-scale MHD convection. This force can be of the same magnitude as the surface tension, so it dramatically hinders bubbles' detachment. Besides, the Kelvin force provides a new potential way for further improving the efficiency of water electrolysis.     

建筑工业化发展的多群体演化博弈与仿真研究

新型建筑工业化具有高质量、低消耗、可循环发展等特征，其推广已上升到国家战略层面。利用演化博弈方法，建立“政府-开发商-银行” 的三方动态演化博弈模型，进行各博弈主体策略的演化稳定性分析，并针对初始状态、奖惩力度、借贷风险和开发成本等对演化结果的影响进行动态仿真。在此基础上， 考虑开发商群体的网络拓扑特征对演化真实性的影响，引入复杂网络理论， 以无标度网络为载体描述开发商个体的连接偏好和决策机制，构建政府监管下的建筑工业化扩散模型，并通过仿真深入研究相关因素对扩散深度的影响作用，最后结合仿真结果给出相应对策建议。     

Effects of upholstery materials on the burning behavior of real‐scale residential upholstered furniture mock‐ups

Fire spread and growth on real‐scale four cushion mock‐ups of residential upholstered furniture (RUF) were investigated with the goal of identifying whether changes in five classes of materials (barrier, flexible polyurethane foam, polyester fiber wrap, upholstery fabric, and sewing thread), referred to as factors, resulted in statistically significant changes in burning behavior. A fractional factorial experimental design plus practical considerations yielded a test matrix with 20 material combinations. Experiments were repeated a minimum of two times. Measurements included fire spread rates derived from video recordings and heat release rates (HRRs). A total of 13 experimental parameters (3 based on the videos and 10 on the HRR results), referred to as responses, characterized the measurements. Statistical analyses based on Main Effects Plots (main effects) and Block Plots (main effects and factor interactions) were used. The results showed that three of the factors resulted in statistically significant effects on varying numbers of the 13 responses. The Barrier and Fabric factors had the strongest main effects with roughly comparable magnitudes. Foam was statistically significant for fewer of the responses and its overall strength was weaker than for Barrier and Fabric. No statistically significant main effects were identified for Wrap or Thread. Multiple two‐term interactions between factors were identified as being statistically significant. The Barrier*Fabric interaction resulted in the highest number of and strongest statistically significant effects. The existence of two‐term interactions means that it will be necessary to consider their effects in approaches designed to predict the burning behavior of RUF.     

Use of La2O3 with 8YSZ as thermal barrier coating and its effect on thermal cycle behavior,microstructure, mechanical properties and performance of diesel engine operated by hydrogen-algae biodiesel blend

In this present work, the effect of lanthanum oxides (La₂O₃) on the thermal cycle behavior of TBC coatings and mechanical properties such as adhesion strength and microhardness of 8% Yttria Stabilized Zirconia (8YSZ) TBCs were investigated. CoNiCrAlY and aluminium alloy (Al–13%Si) were used as bond coat and substrate materials. 8YSZ and different wt % of La₂O₃ (10, 20, and 30%) top coatings were applied using the atmospheric plasma spray (APS) method. The thermal cycling test for TBC coated samples were conducted at 800 °C in the electric furnace. The XRD pattern shows that the La₂O₃ doped 8YSZ material transformed to cubic pyrochloric structured La₂Zr₂O₇ during thermal cycling. Further, the Taguchi-based grey relation analysis (GRA) method was applied to optimize the TBC coating parameters to achieve better mechanical properties such as adhesion strength and microhardness. And the optimized La₂O₃/8YSZ TBC coating was coated on CRDI engine combustion chamber components. The engine was tested with microalgae biodiesel and hydrogen, and the results were promising for the TBC-coated engine. The engine performance increased while using La₂O₃/8YSZ coated components, and the emissions from engine exhaust gas such as CO, HC, and smoke reduced considerably. It was found that there was no separation crack and spallation of the coating layer in the microstructure. Ultimately, the microstructural analysis of the optimized TBC coated piston sample after 50 h of running in the diesel engine confirmed that the developed coating had a superior thermal insulation effect and longer life.     

基于概率法的电力系统安全分析

为应对电力系统安全分析中的停机问题，基于概率法的方式，将常用的确定停机计算与加入了概率法的概率停机进行比较，研究了二者的区别与其在长期投资方向的不同。在进行电力系统停机分析时，通常会分别从确定停机与概率停机的角度出发，对其应急状态下的潮流进行计算。但前者的方法可能导致极低概率的停机事件被忽略，进而影响长期的资金投资。通过加入概率法的计算，使得对单个停机事件的判定由其具体的频率来确定，增加了系统运行的稳定性。