Material Process Parameters Research Articles

Quality prediction and process optimization in abrasive waterjet cutting of ultra‐thick carbon fiber reinforced polymer

AbstractSurface roughness and delamination extent are key indicators for assessing the surface quality of machined carbon fiber reinforced polymer (CFRP) laminates. This study conducted an in‐depth investigation on the uncontrollable surface quality of abrasive water jet (AWJ) machining of ultra‐thick CFRP. Considering the sensitivity of the laminate structure to the jet impact angle, an optimized response surface methodology was used to analyze the effects of process parameters on surface roughness. Additionally, the differences in surface roughness on both sides of the kerf under non‐orthogonal cutting were examined. Based on these analyses, a surface roughness prediction model was developed. Furthermore, the study comprehensively analyzed the effects of material mechanical properties and process parameters on delamination damage. Using dimensional analysis, a predictive model for the maximum delamination length, considering jet energy dissipation, was established. The novelty of this research is to reveal the difference in surface quality on both sides of the kerf under non‐orthogonal cutting, and to establish prediction models for surface roughness and delamination damage based on the energy dissipation characteristics of ultra‐thick CFRP AWJ machining. This research provides essential modeling foundations for enhancing the controllability of AWJ machining quality for ultra‐thick CFRP complex components.Highlights Surface roughness and delamination damage impact AWJ use for ultra‐thick CFRP. Non‐orthogonal cutting causes surface quality differences on kerf sides. A model for kerf surface roughness at any jet impact angle was established. The delamination mechanism in internal path cutting was analyzed. The delamination length model for ultra‐thick CFRP laminates was established.

Interaction between material and process parameters during 3D concrete extrusion process

Extrusion of cement-based materials in additive manufacturing is influenced by a complex interaction of various material and process parameters. This study aims to investigate the impact of rheological properties and printing parameters on the extrudability of cement-based materials as well as the interaction between rheological properties of print materials and extrusion speed, as a key printing process parameter. 20 different print materials with diverse rheological properties were extruded at 10 different extrusion speeds. The effect of material parameters (i.e. rheological properties) and process parameters (i.e., extrusion speed) and their interaction during the extrusion process were evaluated using filament continuity, conformity and consistency. At a constant printing speed, a higher yield stress adversely impacted filament continuity in mixtures with a yield stress of over 260 Pa, whereas viscosity showed minimal influence on filament quality within the tested range of the rheological properties. The results of this study highlighted a significant correlation between material and process parameters and that adapting process parameters to variations in material properties is crucial for meeting printing criteria. The filament consistency of the mixtures with high yield stress was more sensitive to change in the extrusion speed than that of mixtures with low yield stress. An opposite trend, however, was observed for filament conformity where low yield stress mixtures showed a higher sensitivity to the extrusion speed. A procedure was suggested and applied to determine the optimum extrusion speed. Optimal extrusion speeds enabled printing mixtures with a broader spectrum of rheological properties with an acceptable visual quality, filament conformity and consistency requirements. With extrusion speed adjustment, the extrudability window was expanded from dynamic yield stress of 108–126 Pa to 108–263 Pa and plastic viscosity of 8.2–12.3 Pa.s to 5.1–16.4 Pa.s.

Understanding of Wetting Mechanism Toward the Sticky Powder and Machine Learning in Predicting Granule Size Distribution Under High Shear Wet Granulation.

The granulation of traditional Chinese medicine (TCM) has attracted widespread attention, there is limited research on the high shear wet granulation (HSWG) and wetting mechanisms of sticky TCM powders, which profoundly impact the granule size distribution (GSD). Here we investigate the wetting mechanism of binders and the influence of various parameters on the GSD of HSWG and establish a GSD prediction model. Permeability and contact angle experiments combined with molecular dynamics (MD) simulations were used to explore the wetting mechanism of hydroalcoholic solutions with TCM powder. Machine learning (ML) was employed to build a GSD prediction model, feature importance explained the influence of features on the predictive performance of the model, and correlation analysis was used to assess the influence of various parameters on GSD. The results show that water increases powder viscosity, forming high-viscosity aggregates, while ethanol primarily acted as a wetting agent. The contact angle of water on the powder bed was the largest and decreased with an increase in ethanol concentration. Extreme Gradient Boosting (XGBoost) outperformed other models in overall prediction accuracy in GSD prediction, the binder had the greatest impact on the predictions and GSD, adjusting the amount and concentration of adhesive can control the adhesion and growth of granules while the impeller speed had the least influence on granulation. The study elucidates the wetting mechanism and provides a GSD prediction model, along with the impact of material properties, formulation, and process parameters obtained, aiding the intelligent manufacturing and formulation development of TMC.

Dimensional and experimental analysis for predicting the material removal rate in AJM

ABSTRACT One of the upcoming methods for machining brittle and heat-sensitive materials is abrasive jet machining (AJM) where the process of erosion aids in material removal. This is accomplished by the impact of abrasives transported using a stream of gas having high velocity onto the workpiece. The erosion mechanism is a complicated process, which involves cutting, fracturing and micro structural transformation, thereby causing the evaluation of response parameter like rate of material removed (MRR) an arduous task. In this paper, an effort has been made to develop a semi-empirical model for predicting MRR in hole machining of soda-lime glass by utilising dimensional analysis (DA) technique. In this model, the compressive stress developed during the impact of loading and velocity of the particle are considered as a function of work material, selected abrasive material properties and process parameters. The validation of the evolved model was carried out with experiments that involve process parameters such as operating pressure, stand of distance (SOD) and abrasive particle size. From the analysis, it’s found that the predicted MRR model created by the dimensional analysis method gave an average error of 11.8%. thereby giving a reasonably compatible value with experimental results.

Anisotropic mechanism of monocrystalline silicon on surface quality in precision diamond wire saw cutting

The surface quality of wire-saw cut monocrystalline silicon is affected by its anisotropy. This work investigates the effect of anisotropy on the surface quality of monocrystalline silicon (100), (110), and (111) crystalline surfaces in wire-saw cutting processing. The material properties of monocrystalline silicon in different crystal directions are analyzed, and the expressions of elastic modulus of monocrystalline silicon (100), (110), and (111) crystal surfaces are derived, and the influences of material properties and process parameters on macroscopic sawing force and material removal are investigated. The single abrasive grains scratching the surface of monocrystalline silicon and the wire saw cutting and processing process were simulated, and the diamond wire saw cutting and processing of monocrystalline silicon experiment was carried out. The experiment results show that: When the wire saw cuts and processes the (100), (110), and (111) crystal surfaces, the cutting angle with better sawing performance is 30°. The macroscopic normal and tangential average sawing forces on the crystalline surface of monocrystalline silicon (110) differed by 7.22N and 2.54N. The average error between the experiment value of surface warpage and the simulation value is 5.47 %, which indicates the accuracy of the surface morphology prediction model.

Microstructural Characterization of Dry Powder Inhaler Formulations Using Orthogonal Analytical Techniques

PurposeFor locally-acting dry powder inhalers (DPIs), developing novel analytical tools that are able to evaluate the state of aggregation may provide a better understanding of the impact of material properties and processing parameters on the invivo performance. This study explored the utility of the Morphologically-Directed Raman Spectroscopy (MDRS) and dissolution as orthogonal techniques to assess microstructural equivalence of the aerosolized dose of DPIs collected with an aerosol collection device.MethodsCommercial DPIs containing different strengths of Fluticasone Propionate (FP) and Salmeterol Xinafoate (SX) as monotherapy and combination products were sourced from different regions. These inhalers were compared with aerodynamic particle size distribution (APSD), dissolution, and MDRS studies.ResultsAPSD testing alone might not be able to explain differences reported elsewhere in invivo studies of commercial FP/SX drug products with different Advair® strengths and/or batches. Dissolution studies demonstrated different dissolution rates between Seretide™ 100/50 and Advair® 100/50, whereas Flixotide™ 100 and Flovent® 100 had similar dissolution rates between each other. These differences in dissolution profiles were supported by MDRS results: the dissolution rate is increased if the fraction of FP associated with high soluble components is increased. Principle component analysis was used to identify the agglomerate classes that better discriminate different products.ConclusionsMDRS and dissolution studies of the aerosolized dose of DPIs were successfully used as orthogonal techniques. This study highlights the importance of further assessing invitro tools that are able to provide a bridge between material attributes or process parameters and invivo performance.

Experimental Study on Optimization of Consolidation Parameters of Silty Clay Based on Response Surface Methodology: A Case Study on the Protection and Restoration of the Ming and Qing Dynasty Hangzhou Seawall Site

The preservation of the ancient seawall site is a focal point and challenge in the protection of historical relics along Hangzhou’s Grand Canal in China. This endeavor holds significant historical and contemporary value in uncovering and perpetuating Hangzhou’s cultural heritage. Researchers investigating the Linping section of the seawall site aimed to address soil site deterioration by selecting environmentally friendly alkali-activated slag cementitious materials and applying the response surface method (RSM) to conduct solidification experiments on the seawall soil. Researchers used the results of unconfined compressive strength tests and microscopic electron microscopy analysis, considering the comprehensive performance of soil solidification mechanisms and mechanical properties, to establish a least-squares regression fitting model to optimize the solidification material process parameters. The experimental results indicate that the optimal mass ratio of lime, gypsum, and slag for achieving the best solidification process parameters for the seawall soil, with a 28-day curing period, is 1:1.9:6.2. This ratio was subsequently applied to the restoration and reconstruction of the seawall site, with parts of the restored seawall exhibited in a museum to promote the sustainable conservation of urban cultural heritage. This study provides theoretical support and practical guidance for the protection and restoration of soil sites.

Enhancing Manufacturing Processing Stability and Efficiency with Linear-Regression Analysis: Modeling on a Flow-Drill Screw (FDS) Joining Process

The instability (in processing time) in the flow-drill screwing process is undesired but inescapable due to variations in material property, gauge, and process parameters. A substantial number of materials and lab labor need to be used to test and control the variability of the real manufacturing joining process. To enhance the stability and efficiency of the screwing process, this study seeks multi-disciplinary collaboration by applying linear-regression modeling. Six hundred and forty-eight data points were collected and split into an 80% training set for model building and a 20% test set for model validation. A multiple linear-regression model was built. The results indicated that, compared to variable base level (6000 rpm rotational speed and 1100 N downforce), higher rotational speed (8000 rpm, 7000 rpm), greater downforce (1200 N, 1300 N), and their interaction were significantly associated with passage (processing) time, while the switch point did not significantly affect passage time. The interaction plot and effect size were adopted to provide measurements of the effect magnitude on processing time. The coefficient of determination indicated that 86% of the variability in the passage time can be explained by this model. Statistical analysis, such as data visualization, statistical modeling, and other data-driven analysis methods, can be used to detect underlying relationships between variables, investigate variations, and make predictions in the manufacturing process. The outcomes from the data-driven analysis can benefit from improving the economical manufacturing system, refining the processing setting, and reducing test material costs, labor, and lead time.

Intelligent industry-oriented oro-solid formulation of famotidine: Advanced statistical optimization and Ex-Vivo characterization

BackgroundSol-Gel is the conventional approach for in-situ formulation having several limitations, including instability, stringent storage conditions, dose inaccuracy, inconsistent drug release, and patient inconvenience. ObjectivesThe aim of the present investigation was to design and characterize an intelligent oro-solid in-situ targeted dosage form of Famotidine (FTD) incorporating the cross-linked chitosan-vanillin (CrL-CSV) which instantly converted into a gel upon contact with acidic media. Material and MethodsCrL-CSV was designed using microwave-assisted method inculcating FTD and vanillin (VNL). Interaction was observed using FTIR and DSC. QbD was applied to develop intelligent formulation. Taguchi design was accomplished to screen significant critical material attributes (CMAs) and process parameters (CPPs). Box-Behnken design (BBD) was used to correlate the CMAs/CPPs: the amount of CS, VNL, microwave time, and critical quality attributes (CQAs): % FTD release, mucoadhesive strength, and viscosity. CrL-CSV were evaluated using various in-vitro, ex-vivo characterization and stability. Results and DiscussionFTIR and DSC revealed no interaction between the FTD and excipients. The amount of CS, VNL, and microwave time were screened as significant variables due to the high S/N ratio and delta value from the Taguchi design. A significant effect of CMA/CPP on the CQAs was observed in BBD. The optimum CrL-CSV was designed accomplishing 8.74 % chitosan (CS), 0.94 % VNL exposing 80sec in microwave. Immediate gelling (<1min.), desired viscosity (51432.6cps), optimal mucoadhesion strength (0.40 N), better control on drug release (91.5 % in 8 h) and high stability were achieved in the optimum batch of CrL-CSV. ConclusionAn intelligent formulation inculcating the CrL-CSV was developed, which has instant gelling time, high mucoadhesion time, and strength, and controlled release with desired physical properties. Progressive tools like Taguchi and BBD was explored. The formulation can be helpful at industry as it increases patient compliance, processing and stability.

Enhancement of Tensile Strength of Coconut Shell Ash Reinforced Al-Si Alloys: A Novel Approach to Optimise Composition and Process Parameters Simultaneously

The research presents a novel approach to develop high-strength functionally graded composite materials (FGCMs) by using recycled coconut shell ash (CSA) particles as reinforcement for a hypereutectic Al-Si alloy matrix. Using a centrifugal casting technique, test specimens are prepared for the study under ASTM standards. The optimal combination of materials to maximise the materials’ overall tensile strength is obtained through the mixture methodology approach. The results show that CSA particles in the matrix material increase the tensile strength of the produced material. Process parameters, melting temperature and rotating speed were found to play a pivotal role in determining the tensile strength. A better tensile strength of the material is obtained when Al-Si = 90.5 wt%, CSA = 9.5 wt%, rotating speed = 800 RPM, and melting temperature = 800 °C; the proposed regression model developed has substantial predictability for tensile strength. This work presents a methodology for enhancing the tensile strength of FGCMs by optimising both the material composition and processing parameters. The achieved tensile strength of 197.4 MPa, at 800 RPM and 800 °C, for a concentration of 7.5 wt% CSA particles, makes these FGCMs suitable for use in multiple engineering sectors.

Utilization of "Intersection" Methodology for Optimization with Many Objectives in Designed Experiments of Material Processing

Material processing involves many factors, and evaluation of final quality of a product also relates to many indexes from different respects. Thus the optimization of qualities and processing of a product is an optimization problem with many objectives (MOO) inevitably. Although there are some approaches proposed to deal with optimization problem with many objectives in nowadays, the inherent shortcomings in these approaches make them puzzled, which include their missing standpoint and use of additive algorithm containing subjective factors. Currently, an "intersection" methodology for optimization with many objectives is proposed by initiating a novel idea of favorable probability to depict the favorite degree of an alternative in optimal option impersonally, which aims to characterize the concurrent optimization of many objectives in a system in spirits of probability theory and set theory. In this article, some regulations are put forward for performing optimal option of material processing parameters in designed experiments of response surface methodology, orthogonal experiment design and uniform experiment design by means of the total / global favorable probability. In the treatment, the total / global favorable probability of an alternative is the decisive indicator in the optimal option uniquely, which transfers the optimization problem with many objectives into a mono-objective one. The result indicates that the novel approach can be employed to deal with the optimal problem of designed experiments for material processing rationally.

Effect of flip-chip ball grid array structure on capillary underfill flow

During the capillary underfill (CUF) process in flip-chip packaging, issues like incomplete filling, voids, wire sweeping, and overflow can impact product reliability and the relatively long filling time required. Therefore, finding ways to improve filling efficiency is a critical challenge. Conducting experiments to address these issues can be costly. As a result, the industry often relies on simulation software to simulate the actual manufacturing process, predict potential problems, compare results with experimental data, and analyze ways to improve the process. This approach helps enhance the package yield and further improves production efficiency.This study investigates the capillary underfill (CUF) process through simulation. Firstly, the viscosity and reaction kinetics of the underfill material are measured to establish the necessary data for the simulation. Then, Moldex3D, a mold flow simulation software, is used to create the model, generate the mesh, and perform the process simulation analysis. The effects of material properties and process parameters on the capillary underfill process are considered. The simulation results are compared with experimental data to validate the feasibility of the simulation. Subsequently, different flip-chip package structures and CUF process parameters are analyzed through simulation to explore the impact of these parameters on the flow pattern and filling efficiency of the adhesive material during the filling process.According to the simulation results, the filling speed is faster when the bump pitch and gap height are larger. However, the required filling time still has a considerable relationship with the volume of the filling region. Dispensing from the side with lower bump density can shorten the filling time when the bump distribution is uneven.

A new interactive design method for carbon fibres laminate component

Carbon fibre is the most common reinforcing phase in composite materials. However, it is difficult to determine the performance parameters of a monofilament. This paper provides an efficient method for performing the global layup optimization of composite laminates, considering the relationship between material characteristics and process parameters. In particular, a new method is proposed that, by integrating commercial tools, can support designers in the design and construction of carbon fibre components. The approach involves four functional groups that interact with each other: requirements and specifications, material definition, process implementation, and design and simulation. The idea is to create a continuous process to realize continuous product optimization. The approach was applied to the optimization of the front wing of a Formula 4 vehicle. After the validation method phase, through a comparison between real data and numerical simulations, product optimization was conducted. Different optimized solutions were obtained, and the solution minimizing the mass but ‘allowing the vehicle to bear stress and strain values within the required limits was chosen. This methodology can be applied to support the designer during both the early design phase and the optimization phase of laminated products.

The effect of material properties and process parameters on die filling at varying throughputs: A PLS-model-based analysis

When tablets are manufactured on a rotary tablet press and the throughput is increased, it leads to changes in powder dynamics during die filling due to formulation characteristics and changing powder flow in the feed frame. This may result, a.o. in increased tablet weight variability, poorer content uniformity, capping and lamination. This research focuses on explaining the die filling performance depending on material properties and process settings, including throughput for small and large tablets. It was concluded that throughput had a negative impact on die filling variability, which is related to reduced residence time and lower fill fraction of the feed frame and dies. Furthermore, the die filling mechanism was inherently different for large tablets in comparison to small tablets. Higher die filling consistency was observed for dense, less porous, less compressible and better flowing powders. As a result of this work, a model was developed to predict the impact of formulation properties and process settings on die filling variability and its dependency on changes in throughput. This model will benefit formulation development at an early stage when active ingredient availability may be challenging as it will avoid the need to conduct experiments at high throughputs.

Toward high-resolution 3D-printing of pharmaceutical implants – A holistic analysis of relevant material properties and process parameters

In this work, filament-based 3D-printing, the most widely used sub-category of material extrusion additive manufacturing (MEAM), is presented as a promising manufacturing platform for the production of subcutaneous implants. Print nozzle diameters as small as 100 µm were utilized demonstrating MEAM of advanced porous internal structures at the given cylindrical implant geometry of 2 mm × 40 mm. The bottlenecks related to high-resolution MEAM of subcutaneous implants are systematically analyzed and the print process is optimized accordingly. Custom synthesized biodegradable phase-separated poly(ether ester) multiblock copolymers exhibiting appropriate melt viscosity at comparatively low printing temperatures of 135 °C and 165 °C were utilized as 3D-printing feedstock. The print process was optimized to minimize thermomechanical polymer degradation by employing print speeds of 30 mm∙s−1 in combination with a nozzle diameter of 150 µm at layer heights of 110 µm. These results portray the basis for further development of subcutaneous implantable drug delivery systems where drug release profiles can be tailored through the adaption of the internal implant structure, which cannot be achieved using existing manufacturing techniques.

Low-cycle fatigue life prediction of austenitic stainless steel alloys: A data-driven approach with identification of key features

A data-driven approach for predicting the low-cycle fatigue (LCF) life of austenitic stainless steel (AusSS) is proposed to address the limitations of classical fatigue life prediction models. This approach integrates four key characteristics of the AusSS alloys, namely chemical compositions, microstructure, material processing parameters, and experimental parameters, to compile a comprehensive fatigue life prediction dataset. By employing the classification and regression technique, the relationship between various input features and LCF life is analyzed in depth, leading to the eventual identification of eight key features. Subsequently, various machine learning (decision tree, random forest, XGBoost, and support vector regression) and artificial neural network (ANN) are utilized to predict the LCF life using the compiled dataset. Comparative analysis of the results reveals higher prediction accuracy of ANN, with respective R2 and mean squared error values of 0.941 and 0.024, showcasing superior performance over the classical Basquin-Coffin-Manson model. This proposed methodology effectively captures the intricate feature-life relationships in AusSS, potentially reducing experimental time and costs of fatigue life estimation and offering promising applications in alloy design and manufacturing optimization.

Thermal history transfer from complex components to representative test specimens in laser powder bed fusion

AbstractAdditively manufactured components are characterized by heterogeneous mechanical properties due to variations of the microstructure, flaws and residual stresses resulting from the inhomogeneous fabrication process. The large number of influencing factors poses a further challenge in understanding the correlation between material properties, process parameters and component geometry. Therefore, the qualification of components based on witness specimens produced within the same job is questionable. This work aims to present a new strategy for the characterization of PBF-LB/M components based on representative specimens. The key assumption is the feasibility of a transfer of the thermal history from a component to a specimen. It is assumed that similar material properties are determined for components and specimens produced adopting a similar thermal history. After the definition of a region of interest in the component, a combination of thermal analyses by means of finite elements and in-situ experimental determination of the thermal history through infrared thermography is used to produce test coupons with a similar thermal history. The effectiveness of the procedure is demonstrated on a pressure vessel for applications in the chemical industry.

A low-friction and high-stability hydrophilic PVP/PEG coated TPU for interventional catheter applications

Vascular interventional catheters are generally made of hydrophobic polymers, which may lead to vascular injury, poor lubrication and other consequences due to friction with vascular wall or stent in the process of intervention. In this study, the PDA-PVP/PEG composite coating was prepared based on common TPU catheter material to improve its hydrophilic lubrication behavior. Firstly, the oxidative self-polymerization of dopamine (PDA) was initiated and deposited on the surface of TPU in a weak alkali environment, and then the PVP/PEG coating was prepared by UV curing with PDA as the intermediate adhesion layer. The composite coating was optimized step by step by lubricating material system, process parameters, molecular weight, and concentration. Compared with the blank control group, the water contact angle decreased from 91.3° to about 28.3°, and the friction coefficient decreased from 0.4 to about 0.03, and the composite coating was not damaged after 30 min of reciprocating sliding. The results of cytotoxicity grade Level 1 and hemolysis rate less than 5 % also proved that the composite coating showed good cytotoxicity and blood compatibility. In summary, the PDA-PVP/PEG hydrophilic lubricating composite coating revealed excellent comprehensive properties.

Research on the welding process of Q355ND thick plate with narrow gap double wire submerged arc welding

Abstract Aiming at the problems of low welding efficiency and unstable quality of thick plates of marine equipment in offshore deep-water areas represented by offshore wind power, the high-efficiency welding process of narrow-gap double-wire submerged arc welding of 30 mm thick Q355ND low alloy high-strength steel plate was developed by selecting the suitable welding material and welding process parameters. The results show that the welded joint has a beautiful appearance, well-fused sides, and no defects. The structure of the heat-affected zone of the joint is mainly composed of pro eutectoid ferrite, acicular ferrite, bainite, and a small amount of pearlite. The center of the seam is composed of a large amount of massive ferrite and a small amount of bainite. The average tensile strength of the joint reaches 536.5 Mpa, and the average impact energy of the weld center at -20°C reaches 48.4 J. The average impact energy of the heat-affected zone reaches 164 J. All physical and chemical performance tests meet the standard requirements. The development of welding processes has important practical significance for improving production efficiency and product quality. It will be widely used to construct offshore wind power towers, offshore platform jackets, and other offshore deep-water engineering equipment.

Effect of Material type and Process Parameters on Tensile Strength of 3D Printed Specimen

Effect of Material type and Process Parameters on Tensile Strength of 3D Printed Specimen