Comparing confidence limits for short-run process incapability index Cpp

Process incapability index C_pp has been proposed in the manufacturing industry to assess process incapability. In industries it is sometimes unable to get large samples, and, hence, the CAN (consistent and asymptotically normal) property of the unbiased estimator for C_pp is missing. In this paper, six bootstrap methods are applied to construct upper confidence bounds (UCBs) of C_pp for short-urn production processes where sample size is small; standard bootstrap (SB), Bayesian bootstrap (BB), bootstrap pivotal (BP), percentile bootstrap (PB), bias-corrected percentile bootstrap (BCPB), and bias-corrected and accelerated bootstrap (BCa). A numerical simulation study is conducted in order to demonstrate the performance of the six various estimation methods. We further investigate the accuracy of the six methods by calculating the relative coverage (defined as the ratio of coverage percentage to average length of UCB). Detailed discussions of simulation results for seven short-run processes are presented. Finally, one real example from Ford Company’s Windsor Casting Plant is used to illustrate the six interval estimation methods.     

The optimization of hydrothermal process of MoS_2 nanosheets and their good microwave absorption performances

In this study,flower-like MoS_2 constructed by nanosheets was synthesized by a simple hydrothermal method.The hydrothermal process was optimized and the effects of hydrothermal condition,including reaction temperature,reaction time and the ratio of Mo source to S source(Mo:S) in precursor,on microwave absorption performances and dielectric properties were investigated.Our results showed that when the reaction temperature was 180℃,the reaction time was 18 h,and the Mo:S was 1:3.5,the synthesized MoS_2 had the best performance:Its minimum reflection loss could reach-55.78 dB,and the corresponding matching thickness was 2.30 mm with a wide effective bandwidth of 5.17 GHz.Further researches on the microwave absorption mechanism revealed that in addition to the destructive interference of electromagnetic waves,various polarization phenomena such as defect dipole polarization were the main reasons for microwave loss.We believe that MoS_2 is a candidate for a practical microwave absorbent.     

Monitoring the manufacturing process of glass fiber reinforced composites with carbon nanotube buckypaper sensor

Buckypapers are free-standing porous mats of entangled CNT ropes cohesively bounded by van der waals interactions, and can be used to monitor the manufacturing process of glass fiber reinforced composite. In this paper, the buckypaper (BP) was fabricated with monodispersion of multi-wall carbon nanotubes via spray-vacuum filtration, and its morphology and pore size distribution were characterized by scanning electron microscope and nitrogen adsorption/desorption. The resistance of the BP sensor was obtained using a four-point probe method, and the resistance changes could be related to phase changes of the resin matrix,. Experimental results show that the BP sensor embedded in the glass/epoxy composite laminates has indicated a relative resistance change from −2.9% to 226.5% during the manufacturing process. In addition, the temperature sensitivity of a pristine BP sensor and a BP sensor embedded in composite were also characterized. The results demonstrate that the effect of resin phase changes on the resistance changes of a BP sensor is greater than that of the temperature during composite manufacturing.     

Real-time assessment of carbon nanotube alignment in a polymer matrix under an applied electric field via polarized Raman spectroscopy

A technique has been developed utilizing polarized Raman spectroscopy to measure alignment of carbon nanotubes in situ in a polymer matrix under an applied electric field. Previous studies of alignment have been restricted to optically transparent solvents or polymerized specimens that prevent accurate analyses of alignment dynamics in polymers. The effects of electric field strength on the degree of alignment and the time to achieve an aligned state are discussed. The use of in situ, real-time polarized Raman spectroscopy provides a non-invasive technique for assessing carbon nanotube alignment, which can assist in determining processing conditions to improve the mechanical and electrical properties of aligned nanocomposites.     

Stabilization of a viscoelastic rotating Euler‐Bernoulli beam

In this paper, we consider a rotating Euler‐Bernoulli beam. The beam is made of a viscoelastic material, and it is subject to undesirable vibrations. Under a suitable control torque applied at the motor, we prove the arbitrary stabilization of the system for a large class of relaxation functions by using the multiplier method and some ideas introduced by Tatar (J. Math. Phys. 52:013502, 2011).     

Criteria for -continuity

Bernoullicity is the strongest mixing property that a measure-theoretic dynamical system can have. This is known to be intimately connected to the so-called metric on processes, introduced by Ornstein. In this paper, we consider families of measures arising in a number of contexts and give conditions under which the measures depend -continuously on the parameters. At points where there is -continuity, it is often straightforward to establish that the measures have the Bernoulli property.

     

Artificial Intelligence Computation to Establish Relationships Between APS Process Parameters and Alumina–Titania Coating Properties

Modeling the behavior of air plasma spray (APS) process, one of the challenges nowadays is to identify the parameter interdependencies, correlations and individual effects on coating properties, characteristics and influences on the in-service properties. APS modeling requires a global approach which considers the relationships between coating characteristics/ in-service properties and process parameters. Such an approach permits to reduce the development costs. This is why a robust methodology is needed to study these interrelated effects. Artificial intelligence based on fuzzy logic and artificial neural network concepts offers the possibility to develop a global approach to predict the coating characteristics so as to reach the required operating parameters. The model considered coating properties (porosity) and established the relationships with power process parameters (arc current intensity, total plasma gas flow rate, hydrogen content) on the basis of artificial intelligence rules. Consequently, the role and the effects of each power process parameter were discriminated. The specific case of the deposition of alumina–titania (Al₂O₃–TiO₂, 13% by weight) by APS was considered.     

Self-modeling curve resolution (SMCR) analysis of near-infrared (NIR) imaging data of pharmaceutical tablets

The idea of quality by design (QbD) has been proposed in pharmaceutical field. QbD is a systematic approach to control the product performance based on the scientific understanding of the product quality and its manufacturing process. In the present study, near-infrared (NIR) imaging is utilized as a tool to achieve this concept. A practical use of a chemometrics technique called self-modeling curve resolution (SMCR) is demonstrated with NIR imaging analysis of pharmaceutical tablets containing two ingredients, a soluble active ingredient, pentoxifylline (PTX), and an insoluble excipient, palmitic acid. Concentration profiles obtained by SMCR reveal that the homogenous distribution of chemical ingredients strongly depends on the grinding time and that its process plays a central role in quantitative control, say sustained-release of PTX. In addition, pure component spectra by SMCR indicate a sequential change of specific NIR peak intensities following the increase of the grinding time. The spectra change shows a molecular structure change related to its crystallinity during grinding process. Accordingly, this study clearly demonstrates that NIR imaging combined with SMCR can be a powerful tool to reveal chemical or physical mechanism induced by the manufacturing process of pharmaceutical products and that it may be a solid solution for QbD of pharmaceutical products.     

Atomically Dispersed Iron Regulating Electronic Structure of Iron Atom Clusters for Electrocatalytic H2O2 Production and Biomass Upgrading

The integration of highly active single atoms (SAs) and atom clusters (ACs) into an electrocatalyst is critically important for high-efficiency two-electron oxygen reduction reaction (2e⁻ ORR) to hydrogen peroxide (H₂O₂). Here we report a tandem impregnation-pyrolysis-etching strategy to fabricate the oxygen-coordinated Fe SAs and ACs anchored on bacterial cellulose-derived carbon (BCC) (FeSAs/ACs-BCC). As the electrocatalyst, FeSAs/ACs-BCC exhibits superior electrocatalytic activity and selectivity toward 2e⁻ ORR, affording an onset potential of 0.78 V (vs. RHE) and a high H₂O₂ selectivity of 96.5 % in 0.1 M KOH. In a flow cell reactor, the FeSAs/ACs-BCC also achieves high-efficiency H₂O₂ production with a yield rate of 12.51±0.18 mol g_cat⁻¹ h⁻¹ and a faradaic efficiency of 89.4 %±1.3 % at 150 mA cm⁻². Additionally, the feasibility of coupling the produced H₂O₂ and electro-Fenton process for the valorization of ethylene glycol was explored in detail. The theoretical calculations uncover that the oxygen-coordinated Fe SAs effectively regulate the electronic structure of Fe ACs which are the 2e⁻ ORR active sites, resulting in the optimal binding strength of *OOH intermediate for high-efficiency H₂O₂ production.