Optimal Combination Research Articles

Non-opioid analgesic combinations following total hip arthroplasty (RECIPE): a randomised, placebo-controlled, blinded, multicentre trial

Multimodal postoperative analgesia following total hip arthroplasty is recommended, but the optimal combination of drugs remains uncertain. The aim of the RECIPE trial was to investigate the relative benefit and harm of the different combinations of paracetamol, ibuprofen, and the analgesic adjuvant dexamethasone for treatment of postoperative pain following total hip arthroplasty. The RECIPE trial was a randomised, blinded, placebo-controlled trial conducted at nine Danish hospitals. Adults scheduled for total hip arthroplasty were randomly assigned (1:1:1:1) using a computer-generated list with stratification by site to receive combinations of oral paracetamol 1000 mg every 6 h, oral ibuprofen 400 mg every 6 h, or a single-dose of intravenous dexamethasone 24 mg in the following groups: paracetamol plus ibuprofen, ibuprofen plus dexamethasone, paracetamol plus dexamethasone, and paracetamol plus ibuprofen plus dexamethasone. The primary outcome was 24 h intravenous morphine consumption, analysed in a modified intention-to-treat population, defined as all randomly assigned participants who underwent total hip arthroplasty. The predefined minimal important difference was 8 mg. Safety outcomes included serious and non-serious adverse events within 90 days and 24 h. The trial was registered with ClinicalTrials.gov, NCT04123873. Between March 5, 2020, and Nov 15, 2022, we randomly assigned 1060 participants, of whom 1043 (589 [56%] women and 454 [44%] men) were included in the modified intention-to-treat population. 261 were assigned to paracetamol plus ibuprofen, 262 to ibuprofen plus dexamethasone, 262 to paracetamol plus dexamethasone, and 258 to paracetamol plus ibuprofen plus dexamethasone. Median 24 h morphine consumption was 24 mg (IQR 12-38) in the paracetamol plus ibuprofen group, 20 mg (12-32) in the paracetamol plus dexamethasone group, 16 mg (10-30) in the ibuprofen plus dexamethasone group, and 15 mg (8-26) in the paracetamol plus ibuprofen plus dexamethasone group. The paracetamol plus ibuprofen plus dexamethasone group had a significantly reduced 24 h morphine consumption compared with paracetamol plus ibuprofen (Hodges-Lehmann median difference -6 mg [99% CI -10 to -3]; p<0·0001) and paracetamol plus dexamethasone (-4 mg [-8 to -1]; p=0·0013), however, none of the comparisons showed differences reaching the minimal important threshold of 8 mg. 91 (35%) of 258 participants in the paracetamol plus ibuprofen plus dexamethasone group had one or more adverse events, compared with 99 (38%) of 262 in the ibuprofen plus dexamethasone group, 103 (39%) of 262 in the paracetamol plus dexamethasone group, and 165 (63%) of 261 in the paracetamol plus ibuprofen group. In adults undergoing total hip arthroplasty, a combination of paracetamol, ibuprofen, and dexamethasone had the lowest morphine consumption within 24 h following surgery and the most favourable adverse event profile, with a lower incidence of serious and non-serious adverse events (primarily driven by differences in nausea, vomiting, and dizziness) compared with paracetamol plus ibuprofen. The Novo Nordisk Foundation and Næstved-Slagelse-Ringsted Hospitals' Research Fund.

Simulation Study on Temperature and Stress Fields in Mg-Gd-Y-Zn-Zr Alloy during CMT Additive Manufacturing Process.

A new heat source combination, consisting of a uniform body heat source and a tilted double ellipsoidal heat source, has been developed for cold metal transfer (CMT) wire-arc additive manufacturing of Mg-Gd-Y-Zn-Zr alloy. Simulations were conducted to analyze the temperature field and stress distribution during the process. The optimal combination of feeding speed and welding speed was found to be 8 m/min and 8 mm/s, respectively, resulting in the lowest thermal accumulation and residual stress. Z-axis residual stress was identified as the main component of residual stress. Electron Backscatter Diffraction (EBSD) testing showed weak texture strength, and Kernel Average Misorientation (KAM) analysis revealed that the 1st layer had the highest residual stress, while the 11th layer had higher residual stress than the 6th layer. Microhardness in the 1st, 11th, and 6th layers varies due to residual stress impacts on dislocation density. Higher residual stress increases dislocation density, raising microhardness in components. The experimental results were highly consistent with the simulated results.

Optimising building envelope and insulation materials for energy efficiency and life-cycle cost in Cypriot residences

ABSTRACT Residential buildings consume approximately 36% of total electricity consumption in Cyprus and this is expected to continue increasing in the coming years. This study explores the potential for energy savings in residential buildings in Cyprus through optimising building envelopes and insulation materials. Using building information modelling and energy modelling software, the study analyses 120 combinations of building envelopes and eight insulation materials, identifying an optimal combination of wall, roof, and flooring materials that could result in 32% energy load reductions and 27% lower life-cycle costs compared to the median scenario. High-density rock wool insulation on roofs and double-glazed windows were also found to offer both monetary and energy performance benefits. A sensitivity analysis revealed that the current high energy prices could provide greater economic incentives to adopt these optimisation strategies. Optimising building materials in Cyprus could play a critical role in climate strategy while also offering significant economic benefits.

Experimental and numerical study on flow characteristics of dual‐cavity die based on multi‐objective optimization

AbstractSlot die coating is a common method of manufacturing electrodes for lithium‐ion batteries. In this paper, a multi‐objective optimization research on the geometry of dual‐cavity die is investigated based on the numerical simulation of lithium battery anode slurry flow combined with the surface response optimization method. First, we use the Plackett–Burman test method to screen the geometric parameters significantly affecting the optimization objective. Then, based on the Box–Behnken response surface analysis method, we determine the optimal combination of parameters. The results show that the inner cavity radius and slot gap are the main structural variables affecting exit‐velocity uniformity and die deformation. The slot gap and slot length mainly affect the inlet pressure. The coefficient of deviation of exit velocity uniformity and average inlet pressure of the optimized die structure decreased by 51.3% and 7.6%, respectively. This research provides theoretical guidance for the design of slot coating dies.Highlights Screening significant geometric parameters using Plackett–Burman test methodology. Box–Behnken response surface analysis to determine optimal parameters. Velocity uniformity and inlet pressure increased by 51.3% and 7.6%, respectively.

Optimal timing of faculty teaching when combined with near-peer teaching: A mixed methods analysis

Background Near-peer teaching is increasingly used in medical education, supporting or replacing faculty teaching. It has positive aspects for learners and tutors, some of which are explained by higher social and cognitive congruence between learners and near-peer tutors (NPTs). This study investigates the optimal combination of faculty tutors (FTs) and NPTs in an abdominal ultrasound course. Methods Sixty-four third-year medical students underwent a basic ultrasound course, with 75% of lessons taught by NPTs and 25% by FTs. Each of four groups had a different faculty teaching timing. A mixed methods approach used a survey and semi-structured interviews at the course end to elicit learners’ preferences, and end-of-course examination scores to look for differences in outcomes. Results Most learners preferred having faculty teaching in the second half of the course, saying it would be overwhelming to start with FTs. Learners preferred between a quarter and a third of the teaching to be from FTs, with NPTs rated better at teaching basics, and FTs contributing unique, helpful clinical knowledge. There was no significant between-group difference in examination scores. Conclusions Medical students preferred most of their teaching to be from NPTs, with some faculty input in the second half of the course.

Effect of laser micromachining crater-array–multi-grooves on the bonding strength and failure mode of aluminum alloy adhesive joints

The strength of aluminium (Al) alloy adhesive joints is essential for aerospace, ship and automotive applications. This study proposes the two-step laser processing of crater-array–multi-groove (CAMG) to maximize the shear strength of adhesive joints for 7075-T6 aluminum alloys. Firstly, the effects of CAMG feature parameters (groove pattern, groove spacing L, and groove depth Gp) on the surface roughness (Sa), shear strength (τ), and microscale failure mode were studied. The failure mode and anchoring structure reveal the influence mechanism of CAMG feature parameters on τ. Then, the parameters are optimized to obtain the best combination that maximizes τ. Finally, the advantages of CAMG were demonstrated by comparing it with a reference specimen and analyzing the surface morphology, wettability, chemical properties, and anchorage structure. The results show that for CAMG the surface had high cleanliness, wettability, and chemical modifications. The multi-scale anchoring structure formed by the grooves, craters, and micropores on the surfaces with the adhesive was sufficiently strong to allow cohesive failure (CF) to occur throughout the bonding region, maximizing τ. When the groove pattern is parallel-groove, L ≤ 100 μm, and the number of scans is N = 2–5, CAMG maximizes τ (∼29.34 MPa). To increase efficiency and save energy, the optimal combination of parameters for laser processing CAMG is parallel-groove, L = 100 μm, and N = 2. Compared with laser processing multi-grooves, CAMG improved the processing efficiency by 3.5 % and reduced the laser energy by 35.2 %. The proposed method shows great advantages in improvement of bonding strength.

Investigation of micro-electro-discharge machining process parameters during machining of M2 hardened die-steel

Micro-electro-discharge machining (micro-EDM) is a well-known micromachining method to create microstructures on hard-to-cut materials. To further exploit the capability of micro-EDM, the present research work investigates the effect of various important micro-EDM process parameters on the material removal rate (MRR), tool wear rate (TWR), and overcut (OC) during micro-cavity machining of M2-hardened die-steel. A Taguchi experimental design was used to study the effects of three process parameters namely pulse-on-time (Ton), peak current (Ip), and gap voltage (Vg). The experimental results showed that the most influencing process parameter in the present experimental investigation is peak current, Ip followed by pulse-on-time, Ton and gap voltage, Vg. Furthermore, a recent and effective method i.e. Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) has been successfully employed to determine optimal process parametric combination for micro-EDM process to achieve maximum MRR and minimum TWR and OC during machining of micro-cavity on M2-hardened die-steel. From the present research investigation, the optimal micro-EDM process parametric combinations obtained for higher MRR, lower TWR and OC are found as 1 A of peak current, 30 μs pulse-on time and gap voltage of 60 V. Furthermore, through various scanning electron microscope micrographs of micro-cavities and micro-machined surfaces, analysis has been done to find out the micro-cavity with best geometrical accuracy and surface feature to validate the best and most ideal combinations of micro-EDM input parameters for micromachining operations. The results of this study show that micro-EDM is a promising process for machining M2-hardened die-steel. The optimization of process parameters using the MARCOS methodology can further improve the machining efficiency and accuracy of micro-EDM.

Fluorescence guided surgery imaging systems for breast cancer identification: a systematic review.

Breast-conserving surgery (BCS) is limited by high rates of positive margins and re-operative interventions. Fluorescence-guided surgery seeks to detect the entire lesion in real time, thus guiding the surgeons to remove all the tumor at the index procedure. Our aim was to identify the optimal combination of a camera system and fluorophore for fluorescence-guided BCS. A systematic review of medical databases using the terms "fluorescence," "breast cancer," "surgery," and "fluorescence imaging" was performed. Cameras were compared using the ratio between the fluorescent signal from the tumor compared to background fluorescence, as well as diagnostic accuracy measures, such as sensitivity, specificity, and positive predictive value. Twenty-one studies identified 14 camera systems using nine different fluorophores. Twelve cameras worked in the infrared spectrum. Ten studies reported on the difference in strength of the fluorescence signal between cancer and normal tissue, with results ranging from 1.72 to 4.7. In addition, nine studies reported on whether any tumor remained in the resection cavity (5.4% to 32.5%). To date, only three studies used the fluorescent signal for guidance during real BCS. Diagnostic accuracy ranged from 63% to 98% sensitivity, 32% to 97% specificity, and 75% to 100% positive predictive value. In this systematic review, all the studies reported a clinically significant difference in signal between the tumor and normal tissue using various camera/fluorophore combinations. However, given the heterogeneity in protocols, including camera setup, fluorophore studied, data acquisition, and reporting structure, it was impossible to determine the optimal camera and fluorophore combination for use in BCS. It would be beneficial to develop a standardized reporting structure using similar metrics to provide necessary data for a comparison between camera systems.

Biodiesel production and exploring properties of Datura stramonium L. oil with its optimization using combined approaches-Taguchi, grey relational analysis, and response surface methodology.

Biodiesel production through the synthesis of Datura stramonium L. oil is studied to explore the most efficient approaches to suggest an alternate feedstock for biodiesel production. The main objective of this work is to optimize the process variables of biodiesel synthesis by using some statistical approach (Taguchi method, grey relational analysis (GRA), and response surface methodology (RSM) analyzing three parameters, i.e., alcohol-to-oil molar ratio, catalyst (NaOH) concentration, and process temperature for achieving maximum biodiesel derived from Datura stramonium L. oil. The transesterification process is applied by using an ultrasonic-assisted technique. Grey relational analysis (GRA) was successfully applied with the Taguchi method resulting in the optimum combination of A2B1C1. Based on the findings, the best operating conditions for transesterifying are attained with the RSM approach consisting of a 5.697:1 molar ratio (level 2), 0.3 (wt.%) NaOH concentration (level 1), and 70 °C process temperature (level 1). With a value of 87.02%, these ideal operating conditions produce the maximum yield as compared to grey relational analysis (GRA) yields 83.99%. The obtained results have been verified through the characterization of oil and biodiesel as well. Also, the fuel qualities of DSL biodiesel were identified and assessed. DSL oil was found 137.6 degrees of unsaturation during fatty acid profile analysis. DSL biodiesel was found the best kinematic viscosity (4.2 mm2/s) and acid value (0.49) when compared to Karanja and palm biodiesel. D. stramonium L. was recognized as a suitable species for biodiesel feedstock according to the findings.

Theoretical optimization of micropillar arrays for structurally stable bioinspired dry adhesives

Inspired by the excellent adhesion performances of setae structure from organisms, micro/nano-pillar array has become one of the paradigms for adhesive surfaces. The micropillar arrays are composed of the resin pillars for adhesion and the substrate with different elastic modulus for supporting. The stress singularity at the bi-material corner between the pillars and the substrate can induce the failure of the micropillar-substrate corner and further hinder the fabrication and application of micropillar arrays, yet the design for the stability of the micropillar array lacks systematical and quantitative guides. In this work, we develop a semi-analytical method to provide the full expressions for the stress distribution within the bi-material corner combining analytical derivations and numerical calculations. The predictions for the stress within the singularity field can be obtained based on the full expressions of the stress. The good agreement between the predictions and the FEM results demonstrates the high reliability of our method. By adopting the strain energy density factor approach, the stability of the pillar-substrate corner is assessed by predicting the failure at the corner. For the elastic mismatch between the pillar and substrate given in this paper, the stability can be improved by increasing the ratio of the shear modulus of the substrate to that of the micropillar. Our study provides accurate predictions for the stress distribution at the bi-material corner and can guide the optimization of material combinations of the pillars and the substrate for more stable bioinspired dry adhesives.

Machining efficiency and geometrical accuracy on micro-EDM drilling of titanium alloy

ABSTRACT In the current study, micro-electric discharge drilling (µEDD) is conducted on a titanium grade 2 alloy using a tungsten carbide (WC) tool electrode of 496 µm diameter. Capacitance, voltage, and feed rate are selected as machining variables to conduct the experiments based on the full factorial experimental design method. Overcut, material removal rate (MRR), circularity, and hole taper are considered as performance measures. Furthermore, overall evaluation criteria (OEC) is utilized for multiple-objective optimization by allotting varying and equal weight percentages to each response measure. The results of OECs are compared with a revolutionary heuristic multi-objective genetic algorithm (MOGA), resulting in a similar optimal parametric combination and close response measures are obtained. Micrographic investigation demonstrates that at lower capacitance and voltage levels, there is less burr formation, recast layer, and circularity error. Moreover, FESEM and EDS analyses are employed to investigate the machined surface topology and elemental composition respectively.

An Experimental Analysis of the Seed-Filling Mechanism of Maize-Precision Hole-Planter Clamping

Because the operating speed of current mechanical maize hole seeders is low and their ability to adapt to the seed is poor, an active clamping-type precision hole planter for corn was designed. Here, we explain its structural composition and working principle. According to the maize kernel size, the combination of hole parameters is based on the principle of virtual work on analyzing the seed extraction disc assembly’s static mechanical model. The model was imported into the ADAMS simulation for validation and the parameters and ranges affecting the seed-filling performance were identified. By further analyzing the results of the coupled ADAMS–EDEM simulation, the “arching” process of the seeds during leakage charging was revealed, and an arch-breaking method was proposed with the help of a swinging seed-collecting slider. The speed of the hole planter, the diameter of the outer edge of the gravity ring, and the angle of the block installation were used as test factors. The Box–Behnken center-combination simulation test was conducted using the sowing pass index, re-seeding index, and missed sowing index as evaluation indices. The experimental results show that the optimal parameter combination was as follows: gravity ring = 174.3 mm, stopper installation angle = 131.9°, and hole seeder speed = 85.2 rpm. At this time, the qualified seeding index was 94.53%, the multiple indices were 4.30%, and the leakage index was 1.18%. Under these conditions, the row seeding performance bench test was conducted to obtain the qualified seeding index of the hole seeder, which was 93.36%, while the multiple indices were 5.20% and the leakage index was 1.44%, which satisfied the agronomic requirements of precision seeding. This provides a theoretical reference for mechanical seeding methods for irregular seeds, as well as a basis for the research and development of maize precision sowing machinery and equipment.

WITHDRAWN: Clean production of a new activated carbon/tungstate composite from olive mill wastewater for the removal of diclofenac and paracetamol: Adsorption mechanism and transition state

A new carbon/tungstate composite based on liquid by-products, in particular olive mill wastewater (OMWW), was used to remove diclofenac and paracetamol, by adsorption. The composite was prepared using a clean method based on the addition of dissociated tungstate in hydrogen peroxide (H2O2), combined with single carbonization at 950 °C for 5 min. To study the effect of tungstate on composite properties, 4 carbon/tungstate combinations, varying as a function of the mass content of tungstate added, were studied: 0, 1, 2 and 3%wt. The optimum combination showed significant porosity, thermal stability and a wealth of sites suitable for adsorption. The adsorption tests showed that the Freundlich and double-layer adsorption models best described the equilibrium relationship, while the pseudo-second-order model best described the kinetics, regardless of adsorbate. Moreover, high saturation adsorption capacities, for diclofenac (712 mg g−1) and paracetamol (517 mg g−1), were obtained. Non-steric results showed a double-layer adsorption in a parallel orientation and an interaction ratio of 3 sites per molecule. The Activation parameters confirmed rapid adsorption kinetics, physical interactions and easy desorption from the surface. The chemical mechanism was governed by bi/tridentate interactions with a predominance of π-π interactions. The treatment of a real pharmaceutical wastewater with a chemical oxygen demand of 8.1 g(O2).L−1 resulted in 89% removal. Overall, this work presents a new clean solution for the capture of pharmaceutical molecules from water and a detailed presentation of adsorption mechanisms, in particular: chemical, physical, non-steric and at the transition state.

Investigation of viscoelastic behavior of Abaca-reinforced epoxy composites

Natural fiber-based composites demonstrate excellent and comparable static and dynamic mechanical properties to conventional materials, such as steel and aluminum. They also extend their applications to aeronautical, sports equipment, and marine fields. This experimental study aims to find the effect of untreated and treated Abaca-reinforced epoxy composites on the viscoelastic behavior and the optimum combinations of fiber and resin to produce better bonding efficiency. The different specimens used for this study were pure epoxy, untreated, and chemically treated composite specimens. The four weight percentages of Abaca fibers are 10%, 20%, 30%, and 40% used to prepare composite specimens. Similarly, four different sodium hydroxide (NaOH) concentrations, 4, 6, 8, and 10 wt. %/vol. %, have been used for the chemical treatment of fibers. The storage modulus of Abaca-reinforced epoxy composite specimen has been investigated with respect to temperature and fiber content. The result shows that the 30% weight fraction of fibers with chemically (8 wt. %/vol. %) treated fiber-reinforced epoxy specimen produces 41.67% higher storage modulus than the 10% weight fraction of fibers content of composite specimens. Fourier-Transform Infrared Spectroscopy (FTIR) broad transmittance has been used to distinguish the raw and chemically treated fibers. FTIR results reveal the removal of functional groups after NaOH treatment.

Sensitivity Analysis of Influencing Factors of Karst Tunnel Construction Based on Orthogonal Tests and a Random Forest Algorithm

To conduct a sensitivity analysis of the relevant parameters that impact the mechanics of tunnel construction in karst areas, firstly, the orthogonal design and range analysis method is applied to sort the 11 kinds of karst-tunnel-influencing factors from high to low according to the sensitivity degree. Secondly, the random forest algorithm based on an orthogonal experimental design is applied to the feature importance ranking of the influencing factors of karst tunnels. Thirdly, according to the results of the sensitivity analysis, the optimum combinations of influencing factors of tunnel construction in karst areas is obtained. The research based on these two methods shows that when taking the vertical displacement as the target variable, the parameters with the highest feature importance are A6 (tunnel diameter) and A10 (tunnel buried depth). When taking the first principal stress as the target variable, the most important influencing factors are A10 (tunnel buried depth) and A9 (location of karst cave). When taking the principal stress difference as the target variable, the most important influencing factors are A10 (tunnel buried depth) and A6 (tunnel diameter). The level combination of the 11 influencing factors obtained by taking the principal stress difference as the target variable was more balanced than the vertical displacement and the principal stress difference as the target variables. The results of this study will provide a theoretical basis to study key parameters in the response of mechanical characteristics to the safe construction of tunnels in karst areas.

Experimental study of the effect of different 3D printing parameters on tensile strength, using artificial neural network

Numerous research studies have been conducted to optimize printing parameters using the fused deposition modeling technique (FDM) to improve mechanical properties. The large number of process parameters creates a need to search for optimal combinations of parameters to improve mechanical properties. This study examines the effects of three parameters when printing 3D with melted filament of a PLA material (Polylactic Acid) on the ultimate tensile strength of the printed parts. This search combines an experimental study of the most influential printing parameters on the tensile strength property, namely layer thickness, printing temperature, and feed rate. The experimental results are then analyzed and modeled as a linear regression model. Then develop an intelligent artificial model based on ANN (Artificial Neural Network) derived from these experimental results capable of predicting the optimal combination of parameters providing maximum tensile strength. The observed results showed that the feed rate dominates among the other variables, followed by the thickness of the layer. Also, at the level of prediction, the artificial model provides a better prediction of the tensile strength with a value of 36.1625 MPa by combining the following parameters: Feed rate: 70 mm s−1, temperature: 200 °C, and layer thickness: 0.26 mm, compared to the prediction obtained by the linear regression model. Neural networks enable more accurate optimization of 3D process parameters, leading to an overall improvement in the quality of finished products. predictive models, significantly reducing the iteration time required to obtain optimal parameters. The quality of the data used to train neural networks is crucial.

Specificity and sensitivity of an indirect fluorescent antibody test to detect antibodies against bovine viral diarrhea virus.

Since being reported in 1979 and 2006, indirect fluorescent antibody (IFA) tests have not been reported to detect bovine viral diarrhea virus (BVDV) antibodies to our knowledge. Thus, we re-evaluated the efficacy and usefulness of IFA tests for BVDV serology. We tested 4 combinations of 2 antibody conjugates (fluorescein isothiocyanate [FITC]-conjugated rabbit IgG anti-bovine IgG; rabbit IgG F(ab')2 fragment anti-bovine IgG [F(ab')2 FITC-IgG]) and 2 washing solutions (PBS; carbonate-bicarbonate-buffered saline [CBBS]) to evaluate the specificity of an IFA test for BVDV. We compared the sensitivity of the optimal combination with virus neutralization (VN) tests and an ELISA, and compared IFA with VN titers against different genotype (subgenotype) strains. For the F(ab')2 FITC-IgG/CBBS combination, only 1 of the 156 (0.6%) 4-fold diluted cattle sera resulted in a nonspecific reaction; other combinations led to a much higher incidence (22.9-37.2%). For the F(ab')2 FITC-IgG/CBBS combination, IFA detection rates were identical (36 of 59) for BVDV1 and BVDV2 genotypes, and IFA titers against them were strongly correlated (r = 0.99). The antibody-detection rates of the IFA tests were almost identical to those of VN tests and the ELISA (κ: 0.96 and 0.89, respectively). The IFA titers against 4 strains (BVDV1a, BVDV1j, BVDV2a, and an unidentified strain) were similar, 1,024 to ≥4,096, although the VN titers were different. Thus, our IFA tests were specific and sensitive, and more useful than VN tests given that the IFA tests could evaluate the immune status of cattle using a representative strain, regardless of genotype (subgenotype).

Properties and interaction of layers in board-biodegradable primer-printing ink screen-printed system

Surface interactions of the materials during and after the printing process are extremely important for understanding and optimizing the process of graphic reproduction. In screen printing on porous and absorbent substrates, mesh type and ink composition significantly influence the properties of the printed product. To protect the absorbent printing substrates such as board from moisture penetration and to ensure the optimal interaction of the printed ink layer and the substrate, board substrates can be coated with protective primers before printing. In this research, biodegradable primers made of poly(ɛ‐caprolactone) and poly(lactic acid) were applied on the board substrate which was then screen‐printed using two screen rulings of the mesh and two different types of water‐based printing inks on unprimed and primed board substrates. Printed ink layer thickness, surface roughness, water vapor transmission rate, surface free energy and adhesion parameters were measured/calculated on all produced samples. Microscopy of the printed elements was performed to visualize the influence of the primers on the printed line edge. Results of the research have shown that the primers influence the roughness reduction of the printed ink layer. Furthermore, thickness of the printed ink layers increased when the primers were applied on the substrate, pointing to the decreased permeability of the board, which was confirmed by the reduced water vapor transmission rate of the primed and printed substrates. The surface free energies of the tested surfaces and the adhesion parameters between biodegradable primers and prepared printing inks differed depending on the type of the ink and primer, pointing to the optimal combination of the primer and ink for the favorable acceptance of printing ink on the substrate. Results of this research have enabled the optimization of the quality of screen‐printed board product.

Experimental Investigation of the Surface Roughness for Aluminum Alloy AA6061 in Milling Operation by Taguchi Method with the ANOVA Technique

The surface roughness of the machined parts is the most important parameter to predict the performance of mechanical components. Moreover, predicting the optimal machining parameters conditions is the preferable method for cost reduction and achieving the desired surface quality of the product. This study investigates three cutting parameters, such as depth of cut, spindle speed, and feed for the milling aluminium alloy AA6061, to predict the surface roughness quality. The experimental work utilized a manual milling machine with a coated carbide cutter. Furthermore, the experiments were arranged using the Taguchi L9 orthogonal array (OA) method. The average surface roughness (Ra) was measured and converted to signal-to-noise (S/N) ratio and then analyzed in the statistical method of analysis of variance (ANOVA). Finally, the optimal combination set speed, feed, and depth of cut was 2400 rpm, 30 mm/min, and 0.5 mm, respectively. Also, according to the ANOVA test, the most influential parameter was the spindle speed among the selected parameters, with the highest P value of (66.42%). In comparison, the lowest P value is a depth of cut (5.34%). Furthermore, spindle speed was the only significant factor statistically. By selecting a high spindle speed (2400 rpm), surface quality was enhanced, but the preferable level was low for depth of cut and feed.

Optimal Sensor Placement for Vibration-Based Damage Localization Using the Transmittance Function.

A methodology for optimal sensor placement is presented in the current work. This methodology incorporates a damage detection framework with simulated damage scenarios and can efficiently provide the optimal combination of sensor locations for vibration-based damage localization purposes. A classic approach in vibration-based methods is to decide the sensor locations based, either directly or indirectly, on the modal information of the structure. While these methodologies perform very well, they are designed to predict the optimal locations of single sensors. The presented methodology relies on the Transmittance Function. This metric requires only output information from the testing procedure and is calculated between two acceleration signals from the structure. As such, the outcome of the presented method is a list of optimal combinations of sensor locations. This is achieved by incorporating a damage detection framework that has been developed and tested in the past. On top of this framework, a new layer is added that evaluates the sensitivity and effectiveness of all possible sensor location combinations with simulated damage scenarios. The effectiveness of each sensor combination is evaluated by calling the damage detection framework and feeding as inputs only a specific combination of acceleration signals each time. The final output is a list of sensor combinations sorted by their sensitivity.