Changes In Process Parameters Research Articles

In-situ monitoring of the small changes in process parameters with multi-sensor fusion during LPBF

Abstract The small changes in process parameters have significant influences on the stability of laser powder bed fusion (LPBF). Therefore, monitoring the small changes in process parameters is particularly important. This paper proposed a machine learning (ML)-based multi-sensor fusion approach to monitor the LPBF processing state by combining photodiode, acoustic, and visual signals. In order to extract the motion features of the melt pool more accurately and describe its transient changes, an ellipse adjustment algorithm is proposed to segment the melt pool images, eliminating the interference of spatters. The motion features combined with preprocessed acoustic signals and photodiode signals to identify melting states during small changes in process parameters. The proposed ML-based multi-sensor fusion approach achieves impressive prediction accuracies of 99.9% for identifying the fluctuations in the process parameters. The results demonstrate that the proposed method can accurately identify small changes in process parameters, which is of great significance for improving the process stability and providing reliable guidance in subsequent work.

Mechanical Properties of Ti Grade 2 Manufactured Using Laser Beam Powder Bed Fusion (PBF-LB) with Checkerboard Laser Scanning and In Situ Oxygen Strengthening

Additive manufacturing (AM) technologies have advanced from rapid prototyping to becoming viable manufacturing solutions, offering users both design flexibility and mechanical properties that meet ISO/ASTM standards. Powder bed fusion using a laser beam (PBF-LB), a popular additive manufacturing process (aka 3D printing), is used for the cost-effective production of high-quality products for the medical, aviation, and automotive industries. Despite the growing variety of metallic powder materials available for the PBF-LB process, there is still a need for new materials and procedures to optimize the processing parameters before implementing them into the production stage. In this study, we explored the use of a checkerboard scanning strategy to create samples of various sizes (ranging from 130 mm3 to 8000 mm3 using parameters developed for a small 125 mm3 piece). During the PBF-LB process, all samples were fabricated using Ti grade 2 and were in situ alloyed with a precisely controlled amount of oxygen (0.1–0.4% vol.) to enhance their mechanical properties using a solid solution strengthening mechanism. The samples were fabricated in three sets: I. Different sizes and orientations, II. Different scanning strategies, and III. Rods for high-cycle fatigue (HCF). For the tensile tests, micro samples were cut using WEDM, while for the HCF tests, samples were machined to eliminate the influence of surface roughness on their mechanical performance. The amount of oxygen in the fabricated samples was at least 50% higher than in raw Ti grade 2 powder. The O2-enriched Ti produced in the PBF-LB process exhibited a tensile strength ranging from 399 ± 25 MPa to 752 ± 14 MPa, with outcomes varying based on the size of the object and the laser scanning strategy employed. The fatigue strength of PBF-LB fabricated Ti was 386 MPa, whereas the reference Ti grade 2 rod samples exhibited a fatigue strength of 312 MPa. Our study revealed that PBF-LB parameters optimized for small samples could be adapted to fabricate larger samples using checkerboard (“island”) scanning strategies. However, some additional process parameter changes are needed to reduce porosity.

CMP characteristics of IGZO thin film with a variety of process parameters

Recently, amorphous indium gallium zinc oxide (a-IGZO) has been studied in the field of 3D transistors as a channel material for high mobility, good uniformity, and low leakage current performance. The CMP process needs to be applied to fully remove surface IGZO in a multilayer film stack structure and achieve the purpose of planarization. As we all know, the CMP characteristics of the desired removal rate with stability and within-wafer non-uniformity (WIWNU%) play an important role in the CMP process. In this paper, the variation of the removal rate and the non-uniformity for IGZO thin film were studied with various process parameters (such as polishing time, slurry flow rate, slurry dilution, head pressure, head and table speed). The results mean that the removal rate and the non-uniformity of IGZO thin film can be tuned by changing process parameters, which can enhance the confidence about the feasibility of IGZO-CMP in the application of advanced technology.

Implementation of inverse method for identification of process parameters in a laser heating process

Changes in process parameters can alter the temperature data of a solid body during the laser heating process. This paper proposes an inverse method to determine the laser heating parameters, namely, sheet width, sheet thickness, laser power, and scan speed of the work specimen for the given temperature response which is assigned by the user. The method uses an analytical tool on moving heat source as a forward model capable of real-time temperature prediction of the sheet under the laser heating process. The effectiveness of the present forward model that incorporated the temperature-dependent material properties is tested by experimental findings performed on Al 6061-T6 sheets. Next, an iterative search process based on heuristic method is carried out for satisfying a prescribed temperature response by the optimization of unknown parameters. To illustrate the implementation and assess the practicality of the inverse method, two examples based on laser heating applications are used. The method proposed herein recover the unknowns for the prescribed temperature response after a few iterations, provides an efficient way to optimize the laser heating process. Additionally, the effect of measurement error on the findings of the inverse problem is addressed.

Tackling P3HT:Y‐Series Miscibility Through Advanced Processing for Tunable Aggregation

AbstractPolymer and small molecule blend thin films are of strong interest for organic electronics and particularly organic solar cells. The high miscibility in blends of ordinary P3HT and state‐of‐the‐art Y‐series non‐fullerene acceptors (NFAs) suppresses phase separation and aggregation challenging successful charge separation and transport. In this recent work, current‐induced doping (CID) is introduced, a method to precisely control the aggregation of Poly(3‐hexylthiophene) (P3HT) grazing incidence wide angle X‐ray scattering in solution. The highly ordered pre‐aggregation in solution is used here to control the P3HT aggregation in neat films and blends with Y12 (BTP‐4F‐12). This results in a 25‐fold increase in hole mobility in P3HT organic field‐effect transistor (OFET) devices and tunability of the P3HT aggregate quality in the presence of Y12 over large ranges. At the same time, particularly the Y12 long‐range ordering is heavily suppressed by increasing P3HT aggregation. However, solvent vapor annealing (SVA) leads to an extraordinarily high Y12 ordering, changes in the crystal orientation of Y12, and a further improvement of P3HT aggregation. A broad range of different degrees of aggregation of both materials can therefore be obtained in the final thin films solely by changing processing parameters without changing the composition of the material system.

Influence of the Parameters of an Agricultural Biogas Plant on the Amount of Power Generated

Energy from biogas is widely available, inexpensive, and often contributes to waste management, making it one of the most promising renewable energy sources. The main factors influencing this process’ efficiency include the substrates’ chemical composition, temperature, and digester load. This paper presents the possibilities offered by a biogas plant built at a farm specialising in dairy cows. The dependence of the power generated in the micro biogas plant on its technical parameters was analysed in detail. Studies carried out by the authors in an agricultural microgas plant (with an electrical output of 40 kW) have shown that they are designed to maintain continuous energy production, despite changing process parameters such as digester mass level, biogas height, temperature or slurry flow into the digester. However, from the point of view of the amount of electricity generated, changes would have to be made to the design of the biogas plant. Firstly, a more powerful generator would have to be installed to cover the electricity requirements of the equipment installed in the biogas plant so that power close to the rated capacity of the biogas plant is still sent to the grid. Secondly, replacing the two existing agitators of the digestion mass (9 kW each) with more agitators of lower power (e.g., four agitators of 4.5 kW each) would be necessary. These should be programmed so that one of the agitators operates at any given time (the operating time of a given agitator should depend on the composition of the digestate).

Synergy between Fe-Co oxide catalysts supported over HZSM-5 for direct conversion of methane to methanol

The direct conversion of methane to methanol over iron and cobalt oxide based composite catalysts supported over HZSM-5 was carried out in a fixed-bed micro reactor under changing process parameters and catalyst compositions. The prepared catalysts were well characterized by various techniques including N2 adsorption desorption, X-ray diffraction (XRD), Fourier transformed infrared spectroscopy (FTIR), pyridine FTIR, X-ray photoelectron spectroscopy (XPS), UV–vis spectroscopy and temperature programmed reduction (H2-TPR). The characterization results revealed the presence of various reducible iron and cobalt oxide species depending on the Fe/Co molar ratio and total metal oxide loading. Moreover, the XPS and UV–vis spectroscopic results also confirmed the variation of Fe2+/Fe3+ and Co2+/Co3+ species depending on the Fe-Co molar ratio which had strong influence on the performance of the composite catalysts. It was found that the cobalt species favours the formaldehyde formation whereas the iron species promotes the formic acid formation in their respective pure supported oxide catalysts. However, the synergistic effect of iron and cobalt oxide in equimolar ratio in composite catalysts appeared as effective for achieving highest yield of methanol. The methanol selectivity was also influenced by the alteration of various studied process parameters. The higher reaction temperature favoured the overoxidation of methanol to CO2 whereas the methanol selectivity increased with increasing the methane to oxygen ratio. The lattice to adsorbed oxygen ratio also had strong influence on the activity of composite catalysts and methanol selectivity. The highest methanol yield of 1.87% was achieved at the methane conversion of 42.81 % with the 20Fe1Co1Z catalyst at 873 K reaction temperature with CH4/O2 ratio of 2:1 and WHSV of 1030 ml hr−1 gcat−1.

Model predictive control (MPC) applied to a simplified model, magnetic nanoparticle hyperthermia (MNPH) treatment process

Magnetic nanoparticle hyperthermia (MNPH) has emerged as a promising cancer treatment that complements conventional ionizing radiation and chemotherapy. MNPH involves injecting iron-oxide nanoparticles into the tumor and exposing it to an alternating magnetic field (AMF). Iron oxide nanoparticles produce heat when exposed to radiofrequency AMF due to hysteresis loss. Minimizing the non-specific heating in human tissues caused by exposure to AMF is crucial. A pulse-width-modulated AMF has been shown to minimize eddy-current heating in superficial tissues. This project developed a control strategy based on a simplified mathematical model in MATLAB SIMULINK® to minimize eddy current heating while maintaining a therapeutic temperature in the tumor. A minimum tumor temperature of 43 [°C] is required for at least 30 [min] for effective hyperthermia, while maintaining the surrounding healthy tissues below 39 [°C]. A model predictive control (MPC) algorithm was used to reach the target temperature within approximately 100 [s]. As a constrained MPC approach, a maximum AMF amplitude of 36 [kA/m] and increment of 5 [kA/m/s] were applied. MPC utilized the AMF amplitude as an input and incorporated the open-loop response of the eddy current heating in its dynamic matrix. A conventional proportional integral (PI) controller was implemented and compared with the MPC performance. The results showed that MPC had a faster response (30 [s]) with minimal overshoot (1.4 [%]) than PI controller (115 [s] and 5.7 [%]) response. In addition, the MPC method performed better than the structured PI controller in its ability to handle constraints and changes in process parameters.

Effect and mechanism of solution flow rate during interfacial polymerization on morphology and performance of hollow fiber membranes

Interfacial polymerization (IP) using m-phenylenediamine and trimesoyl chloride (TMC) is an essential method for producing thin-film composite (TFC) membranes. Nevertheless, IP is highly sensitive to changes in process parameters, especially the TMC solutions flow rate during inside-out TFC hollow fibers (HF) production. Research on the impact of flow conditions (i.e., laminar vs. turbulent flows) of these organic solutions on the final membrane characteristics and corresponding mechanism is still lacking. This research tested different TMC flow rates (0.1–2 mL/min) to produce inside-out TFC HF. With a TMC flow rate increase, (i) the leaf-like structures of the polyamide (PA) layer decreased in size, (ii) the thickness of the PA layer slightly increased, and (iii) the pure water permeability decreased. However, the elemental composition, chemical bonds, and NaCl rejection remained stable. Different fluid regimes are considered to affect the performance of HF membranes by affecting the heat dissipation process during IP reaction. A TMC flow rate in the laminar flow state (i.e., low flow rates) is recommended for synthesizing HFs. The current research provides new insights into the IP reaction mechanism of HF membrane, thus offering valuable guidance to optimize and produce membrane products with better performance.

In situ build surface topography determination in electron beam powder bed fusion

AbstractElectron optical imaging is the most promising process monitoring method in electron beam powder bed fusion. State of the art in modern machines is the installation of a single detector in the top center of the build chamber. Exemplary applications are the reconstruction of digital twins of manufactured parts to compare their dimensional accuracy or analysing the top surface of each layer to identify surface features like pores or material transport. Multi-detector systems are currently under research and have shown great potential in reconstructing the surface topography in situ. A recently developed ray tracing model, describing the image formation process, allows to formulate design guide lines for multi-detector systems and provides a method for the computation of the normal vector field of the build surface. This work utilizes the recent progress and presents a newly developed four-detector system and an updated computation chain, which enable build surface topography reconstruction in situ in every layer of a build process. The computation chain contains a normal integration algorithm, which employs Tikhonov regularization to cope with measurement irregularities. The integration method is validated with ex situ measured as-built surfaces. Additionally, first applications are demonstrated and connections to process parameter changes illustrated.

Effect of Case Depth and Hardness Distribution on the Rolling Contact Fatigue Performance of G20CrNi2MoA Carburized Steel

This study aims to investigate the effects of the case depth and hardness distribution of carburizing on the rolling contact fatigue (RCF) properties of G20CrNi2MoA steel under deeper carburizing conditions. Four groups of specimens of different case depths are prepared and subjected to RCF tests. A 2D finite element model based on continuum damage mechanics is developed to further analyze these two factors. As the depth of the carburized case increases, the RCF life first increases and then decreases. The optimum case depth is approximately one‐quarter of the thickness of the specimen. A gentler hardness distribution due to a change in the diffusion process parameters ensures a minimal increase (8%) in the RCF performance. The proper case depth has a more notable effect on the RCF life compared with those of the gentle or steep hardness distribution. It is expected that the results can help to promote a better understanding of the heat treatment process of carburized bearings and ensure more reliable carburized bearings are produced.

Modeling-based Approach Towards Quality by Design for a Telescoped Process.

A telescoped, two-step synthesis was investigated by applying Quality by Design principles. A kinetic model consisting of 12 individual reactions was successfully established to describe the synthesis and side reactions. The resulting model predicts the effects of changes in process parameters on total yield and quality. Contour plots were created by varying process parameters and displaying the model predicted process response. The areas in which the process response fulfils predetermined quality requirements are called design spaces. New ranges for process parameters were explored within these design spaces. New conditions were found that increased the robustness of the process and allowed for a considerable reduction of the used amounts of a reagent. Further optimizations, based on the newly generated knowledge, are expected. Improvements can either be direct process improvements or enhancements to control strategies. The developed strategies can also be applied to other processes, enhancing upcoming and preexisting research and development efforts.

Determining the patterns of asymmetric interaction of plastic medium with counter-directional metal flow

The plane problem of rolling theory is analytically solved using the method argument of functions of a complex variable. The solution to the plane problem has been strengthened from the point of view of the asymmetry of the process, which made it possible to consider the applied problem as the interaction of differently directed zones in the deformation zone. The interaction of lagging and advancing zones is represented as a combination of multidirectional processes in a single deformation zone. With a change in kinematic, power characteristics in local zones, the process parameters change in the entire deformation zone. Stressed states of intermediate loading schemes between stable and unstable rolling are considered. A feature of the interaction of zones with the opposite flow of metal is the analogy with the action of back tension on the deformation zone in literally all parameters - this is the presence of tensile stresses in the lagging zone, a decrease in local specific pressures, a shift in maximum normal stresses towards the exit from the rolls, a change in the length of the advance zone, reduction in rolling force. The studies confirm and repeat the generally accepted provisions of the theory of rolling but reveal the effects of changes in the stress state under different loading models. The results of the work make it possible to determine the modes of rolling processes visually and computationally under conditions of strong and weak interaction of zones with an oppositely directed metal flow. The effects of plastic deformation with a decrease in the total effort in the processes that are within the reach of the limiting focus of crimping under conditions of increasing kinematic load when the gripping angles vary between 0,077…0,168 are given

Analysis of the Influence of Gas Leakage in The Dipleg of Cyclone Separators on Particle Properties

The FCC unit uses a cyclone separator for gas-solid separation of catalysts from flue gas or oil and gas. When the cyclone separator experiences a gas leakage fault, it directly affects its separation performance, causing excessive catalyst emissions and leading to the occurrence of catalyst running faults. However, there is currently a lack of diagnostic technology for cyclone separator equipment malfunction and gas leakage. Therefore, the influence of the dipleg of the cyclone separator on the particle loss rate under different gas leakage velocities was investigated experimentally. Experiments show that under normal conditions, particles are subject to multiple cycle separation, and fewer particles randomly enter the riser with the upward rotating flow to escape, which is mainly determined by the structure size and inlet velocity of the cyclone separator. When gas leakage occurs in the dipleg, the higher the gas leakage velocity, the higher the particle loss rate. As the number of particle cycles increases, the loss rate gradually decreases. For this purpose, the cyclone separator inside the FCC unit in the industrial site is taken as the object. In response to multiple cyclone separator loss faults, the changes in process parameters and collected catalyst particle properties of the cyclone separator are analyzed, and the changes in the running dose inside the device during operation are analyzed. Based on the analysis results, the operation of the unit is optimized and adjusted to avoid unplanned shutdown and maintenance. Therefore, based on this, a fault diagnosis technology for catalyst loss in FCC unit cyclone separators based on particle property parameters has been created, which has the characteristics of accuracy and reliability and can be applied to the analysis and diagnosis of catalyst loss faults in FCC unit.

Process parameter effects estimation and surface quality prediction for selective laser melting empowered by Bayes optimized soft attention mechanism-enhanced transfer learning

Additive Manufacturing (AM), particularly Selective Laser Melting (SLM), has revolutionized the industrial manufacturing sector owing to its remarkable design flexibility and precision. However, it is well known that slight changes in SLM process parameters may highly affect the surface quality of the as-built product. In this paper, we investigate the influence of SLM printing parameters (laser power, laser scanning speed, layer thickness, and hatch distance) on surface quality and develop a predictive model for surface quality based on the given printing parameters. The developed model is constructed by a Bayesian Optimization and soft Attention mechanism-enhanced Transfer learning (BOAT) framework with superior domain adaptability and generalization capability. Through experimental validation, the effectiveness of the BOAT approach in estimating printing parameters and correlating them with surface quality has been verified. The comprehensive methodology, experimental configurations, prediction results, and ensuing discussions are all presented. This study contributes to providing valuable insights and practical implications for improving the competitiveness and impact of SLM in advanced manufacturing by accurately predicting surface quality with specified printing parameters.

Pilot-scale co-precipitation synthesis of a novel active ingredient made of ultrasmall iron (oxyhydr)oxide nanoparticles for the treatment of hyperphosphatemia.

Due to its simplicity, co-precipitation is the most commonly used method for producing iron (oxyhydr)oxide nanoparticles. However, it is reported to be sensitive to changes in process parameters, which complicates scale-up and is why only volumes up to 1.2 L have been described in the literature. This study aims to demonstrate the scale-up of a co-precipitation synthesis to 100 L using the example of a new phosphate-binding active ingredient based on iron (oxyhydr)oxide. The synthesis was shown to be very robust to changes in synthesis parameters and stirrer geometries. The in vitro phosphate-binding efficacy and the yield were maintained in all five scales tested. Only the content of the components in the nanoparticles varied slightly. However, Mössbauer spectroscopy, dynamic light scattering (DLS), and attenuated total reflection Fourier transform infrared spectroscopy (FT-IR) revealed no evidence of structural changes, but a reduction in the size of the iron (oxyhydr)oxide cores and the total core-shell nanoparticle sizes. Overall, this study has successfully demonstrated that ultrasmall iron (oxyhydr)oxide nanoparticles can be produced on a pilot scale by co-precipitation with a yield of >40 g L-1.

Reassessment of performance evaluation of EWMA control chart for exponential process

AbstractMemory control charts or charts, such as cumulative sums and exponentially weighted moving average (EWMA), are widely used for tracking minor to moderate changes in process parameters. The literature presented an EWMA chart for monitoring exponential processes, assuming probability limits to determine both in‐ and out‐of‐control average run length (ARL). The use of probability limits for memory charts is an incorrect method. So, we are aiming to correct the EWMA chart by Aslam et al. and the proposed EWMA chart (represented by ) for the exponential process using the run‐length (RL) method based on the simulation method instead of the probability‐based method. The ARL, standard deviation of RL, and median of RL are used to evaluate the proposed chart's performance. For practical consideration of the proposed chart, a real‐world example of a urinary tract infection is also presented.

Establishing Interconnections and Predictive Modelling for CMT Cladding on 316L Stainless Steel

Background Austenitic stainless-steel cladding is vital for corrosion resistance in industries such as petrochemicals, marine, and nuclear. Weld bead geometry and dilution, governed by process parameters, impact cladding quality. This study examines weld bead geometry with welding current, speed, and nozzle-to-plate distance, creating equations to predict dimensions and control geometry. Method This research explores Cold Metal Transfer (CMT) cladding, emphasizing its interaction with parameters using ANOVA and orthogonal arrays. It uncovers patterns and correlations, leading to a robust mathematical model derived from a Definitive Screen Design in Surface Methodology. Results Process parameter changes particularly affect internal shape (bead width, dilution, penetration area) compared to external shape (penetration, reinforcement) using mathematical model. And the validity of the model is defined. Penetration is primarily affected by welding current and nozzle-to-plate distance, with higher current and smaller distances leading to deeper penetration. Reinforcement is minimally impacted by welding current, speed, and error but decreases with a larger nozzle-to-plate distance. Bead width increases with higher welding current and larger nozzle-to-plate distances, while the effects of welding speed and error are relatively small. Dilution is reduced by higher welding current and larger distances, but error can significantly increase dilution. Welding speed has minimal impact on dilution. Conclusion This study enhances the understanding of CMT cladding. By analyzing parameter interactions, it predicts and controls weld dimensions. Statistical tools reveal patterns, aiding in a strong mathematical model. Significant for industrial applications, it emphasizes the impact of parameters on the quality and structure of cladding using austenitic stainless steel.

Robust method for chromatogram shape analysis to improve early detection of performance drifts and adverse changes in process parameters during purification column operations.

The biopharmaceutical industry is under increased pressure to maximize efficiency, enhance quality compliance, and reduce the cost of drug substance manufacturing. Ways to reduce costs associated with manufacturing of complex biological molecules include maximizing efficiency of chromatography purification steps. For example, process analytical technology (PAT) tools can be employed to improve column resin life, prevent column operating failures, and decrease the time it takes to solve investigations of process deviations. We developed a robust method to probe the shape of the chromatogram for indications of column failure or detrimental changes in the process. The approach herein utilizes raw data obtained from manufacturing followed by a pre-processing routine to align chromatograms and patch together the different chromatogram phases in preparation for multivariate analysis. A principal component analysis (PCA) was performed on the standardized chromatograms to compare different batches, and resulted in the identification specific process change that affected the profile. In addition, changes in the chromatogram peaks were used to create predictive models for impurity clearance. This approach has the potential for early detection of column processing issues, improving timely resolution in large-scale chromatographic operations.

Effect of temperature, pH and calcium phosphate concentration on the properties of reassembled casein micelles

Reassembled casein micelles (RCMs) can be made by reassembling sodium caseinate with calcium and phosphate as well as other ions under controlled conditions into casein micelle-like structures. During the reassembly, the changes in processing parameters lead to differences in the properties of RCMs such as size, composition and structure. Understanding the effect of processing parameters on RCM properties is essential for their potential application in food products. However, the effect of process parameters has not been studied systematically. Therefore, the objective of this study was to evaluate the effect of temperature, pH and calcium phosphate concentration on the properties of reassembled casein micelles. The effect of pH on the size and structure of RCMs both during and after their formation was studied by dynamic light scattering and small-angle X-ray scattering. We found that pH affects both the size and internal structure of RCMs. We could also modulate the size and composition of RCMs by changing the temperature and calcium phosphate concentration. The insights of this study not only can be used to modulate the composition and structure of RCMs, but also help us to understand how processing parameters will influence the assembly of RCMs from novel sources, such as recombinant caseins.