Selection Of Appropriate Process Parameters Research Articles

Investigating the friction stir additively manufactured AA2024 build and the influence of material flow in enhancing the inter-surface bonding

Friction Stir Additive Manufacturing (FSAM) is a solid-state joining process that operates below the material’s melting point, avoiding the drawbacks of fusion-based methods. In FSAM, inter-surface bonding is crucial for the build strength and is influenced by material flow at the interface. This study examines the influence of flat-faced (square) and smooth (threaded conical) pins, along with rotational speed, on the material flow, using Al-clad as a tracer. It also analyses the microstructure, micro-texture, mechanical properties of the builds, and the role of the forging force in FSAM. Defect-free builds were achieved with a forging force above 7000 N. The threaded conical pin caused upward migration of Al-clad, while the square pin led to fragmentation and distribution, offering excellent inter-surface bonding. Refined grain structures (∼5 µm) were observed in the top layers. The highest tensile strengths were 392 MPa in the weld direction (80 % build efficiency) with the threaded conical pin, and 358 MPa in the build direction (75 % build efficiency) with the square pin. Strong γ-fiber in ODFs indicates better ductility, with up to 60 % improvement in elongation. The current research shall guide the selection of appropriate process parameters and, in turn, reduce trial-and-error during manufacturing aluminum alloys through friction stir additive manufacturing.

Numerical simulation and analysis on melting characteristics of a solid-liquid phase change process based on hot air riveting

To improve welding efficiency, a hot air riveting technology applicable to simultaneous welding at multiple stations is proposed, with the challenge lying in clarifying the melting state of the weldment. A numerical simulation method is proposed to investigate the melting state of the tag, using the Audi airbag tag as an example. The effects of various process parameters, including the exhaust duct distance, hot air temperature, hot air velocity, and the diameter ratio β, on the melting state of the tag are discussed. The melting mass, internal contour plots of the weldment and the melting rates are compared among the different parameter settings. The results indicate that under a heating temperature of 240 °C, the increase in hot air velocity has the most significant promotional effect on the melting of the weldment. Moreover, regardless of the velocity level, an increase in hot air temperature consistently enhances the melting of the weldment. Concurrently, an increase in the exhaust duct distance has an adverse impact on melting, yet this effect diminishes as the heating temperature rises. Finally, it is observed that at lower temperatures (200 ℃), diameter ratio β = 2.0 is more conducive to melting, whereas at higher heating temperatures (240, 280 ℃), β = 2.5 is more favorable for the melting of the weldment. This method effectively grasps the melting behavior of the weldment, enabling the selection of appropriate process parameters for hot air welding in actual production based on specific requirements.

Process Parameters Optimization and Numerical Simulation of AlCoCrFeNi High-Entropy Alloy Coating via Laser Cladding.

The use of laser cladding technology to prepare coatings of AlCoCrFeNi high-entropy alloy holds enormous potential for application. However, the cladding quality will have a considerable effect on the properties of the coatings. In this study, considering the complex coupling relationship between cladding quality and the process parameters, an orthogonal experimental design was employed, with laser power, scanning speed, and powder feed rate as correlation factor variables, and microhardness, dilution rate, and aspect ratio as characteristic variables. The experimental data underwent gray correlation analysis to determine the effect of various process parameters on the quality of cladding. Then, the NSGA-II algorithm was used to establish a multi-objective optimization model of process parameters. Finally, the ANSYS Workbench simulation model was employed to conduct numerical simulations on a group of optimized process parameters and analyze the change rule of the temperature field. The results demonstrate that the laser cladding coating of AlCoCrFeNi high-entropy alloy with the single pass is of high quality within the determined orthogonal experimental parameters. The powder feed rate exerts the most significant influence on microhardness, while laser power has the greatest impact on dilution rate, and scanning speed predominantly affects aspect ratio. The designed third-order polynomial nonlinear regression model exhibits a high fitting accuracy, and the NSGA-II algorithm can be used for multi-objective optimization to obtain the Pareto front solution set. The numerical simulation results demonstrate that the temperature field of AlCoCrFeNi high-entropy alloy laser cladding exhibits a "comet tail" phenomenon, where the highest temperature of the molten pool is close to 3000 °C. The temperature variations in the molten pool align with the features of laser cladding technology. This study lays the groundwork for the widespread application of laser cladding AlCoCrFeNi high-entropy alloy in surface engineering, additive manufacturing, and remanufacturing. Researchers and engineering practitioners can utilize the findings from this research to judiciously manage processing parameters based on the results of gray correlation analysis. Furthermore, the outcomes of multi-objective optimization can assist in the selection of appropriate process parameters aligned with specific application requirements. Additionally, the methodological approach adopted in this study offers valuable insights applicable to the exploration of various materials and diverse additive manufacturing techniques.

A study on the control of the printing accuracy in alumina parts by ceramic stereolithography

The printing accuracy in ceramic stereolithography is deteriorated by shrinkage due to photopolymerization of monomers and broadening owing to scattering of light. To improve the accuracy of printed alumina parts, a series of experiments involving the reduce of shrinkage and broadening were conducted. Firstly, the dependence of conversion of monomers, shrinkage of suspensions and warpage of parts on energy doses was quantitively investigated and correlated, with which the shrinkage was well controlled through optimization. Besides, the warpage problem was effectively resolved when adding 30 wt% PEG-200 in the suspensions to release the accumulated internal stress. Next, the broadening under different energy doses was observed and reduced by addition of absorbers, after which a self-defined parameter Cd/We was applied to suggest strategies in the selection of appropriate processing parameters and absorber content. On this basis, the holes with a diameter ranging from 50–200 μm were successfully printed.

Fabrication of Amisulpride Nanosuspension for Nose to Brain Delivery in the Potential Antipsychotic Treatment

ABSTRACT: Background: This research was aimed with the development of antipsychotic drug delivery for olfactory administration which could deliver drug to the brain. Amisulpride is a psychoactive drug that belongs to the benzamide derivatives class. It enhances dopaminergic neurotransmission by inhibiting presynaptic dopamine D2/D3 auto receptors selectively at lower dosages. Method: The nanosuspension was prepared by media milling technique for nose to brain delivery. The nose to brain delivery developed an effective route to bypass the BBB and deliver the drug to the brain. Factorial design was used for the designing and optimizing formulation based on various process and formulation factors. The optimized batch further analyzed to determine particle size, PDI, zeta potential, and drug content. With appropriate selection of process parameters like speed and bead amount. The media milling method is one of the effective methodology to reduce particle size and with the help of stabilizers nanoparticles could be stabilised. Result: The average particle size range of nanosuspension batch was observed 100-150 nm with a polydispersity index of 0.0927, Zeta potential +39.14 mV and drug content 88.12 ± 2 %. Conclusion: Intranasal administration is a promising alternative for bypassing the blood-brain barrier, reducing the adverse effects, and lowering the doses.

Stability Analysis of Milling Based on the Barycentric Rational Interpolation Differential Quadrature Method

Chatter causes great damage to the machining process, and the selection of appropriate process parameters through chatter stability analysis is of great significance for achieving chatter-free machining. This article proposes a milling stability analysis method based on the barycentric rational interpolation differential quadrature method (DQM). The dynamics of the milling process considering the regeneration effect is first modelled as a time-delay differential equation (DDE). When adjacent pitch angles of the milling cutter are symmetric, the milling dynamic equation contains a single time delay. Otherwise, when adjacent pitch angles are asymmetric, the dynamic equation contains multiple time delays. The barycentric rational interpolation DQM is then used to approximate the differential and delay terms of the milling dynamics equation, and to construct a state transition matrix between adjacent milling periods. Finally, the chatter stability lobe diagram (SLD) is obtained based on the Floquet theory. According to the SLD, the appropriate spindle speed can be selected to obtain the maximum stable axial depth of cutting, thereby effectively improving the material removal rate. The accuracy and efficiency of the proposed method have been validated by two widely used milling models, and the results show that the proposed method has good accuracy and computational efficiency.

Design and fabrication of a polydimethylsiloxane device for evaluating the effect of pillar geometry and configuration in the flow separation using deterministic lateral displacement.

The advancement of microfluidics and the manufacturing of microdevices has led to a strategic change in the biomedical industry. The flow through narrow channels and the pillars are placed strategically, leading to the phenomenon of particle separation through deterministic lateral displacement (DLD). In such a phenomenon, the shape, size, location and orientation of the obstacles play an important role. For the first time, particle separation is achieved with DLD modules having high row shift angles of 25°, 30° and 35°, reducing the number of pillars. The significance of circular and triangular micropillars executing deterministic lateral displacement, oriented at different angles, has been investigated, and it is found that the triangular pillars oriented at 75° resulted in better separation compared to the other configurations. In this report, the fabrication, location, orientation of the micropillars and the selection of appropriate process parameters are detailed. The structures are fabricated on silicon wafers using the standard photolithography process followed by the deep reactive ion etching process. These dies are further used to fabricate the polydimethylsiloxane-based microfluidic chips. These fabricated devices are characterised by their size, structure and quality using 3D microscopy and scanning electron microscopy. Further, blood plasma separation is carried out using the devices fabricated in this work, and the particles at the inlet and outlets are evaluated using microscopy and a novel image processing technique, replacing the use of a hemocytometer. The path traced by the particles at different flow conditions is numerically evaluated and validated with experiments. The novel device is capable of separating blood cells from plasma with a recovery factor varying from 44% to 100%. PDMS-PDMS bonding experiments using oxygen and argon plasma have been carried out to evaluate the maximum bond strength and flow velocity in the devices. It is observed that the oxygen plasma results in a bond strength of 0.404 N mm-1, thus a high throughput of 135.34 μL s-1 is achieved using the fabricated device.

Efficient Analysis of Interdependencies in Electrode Manufacturing Through Joint Application of Design of Experiments and Explainable Machine Learning

AbstractBattery cell production is a key contributor to achieving a net‐zero future. A comprehensive understanding of the various process steps and their interdependencies is essential for speeding up the commercialization of newly developed materials and optimizing production processes. While several approaches have been employed to analyze and understand the complexity of the process chain and its interdependencies – ranging from expert‐ and simulation‐based to data‐driven – the latter holds significant potential for real‐time application. This is particularly relevant for inline process control and optimization. To streamline the development and implementation of data‐driven models, a holistic framework that encompasses all necessary steps – from identification of relevant parameters and generation of data to development of models – is imperative. This article aims to address this objective by presenting a comprehensive and systematic methodology, demonstrated for efficient cross‐process analysis in electrode manufacturing. Through the combined utilization of design of experiments methods, data‐driven models, and explainable machine learning methods, the interdependencies between production parameters and the physical, mechanical, and electrochemical characteristics of the electrodes were uncovered. These actionable insights are essential for enabling informed decision‐making, facilitating the selection of appropriate process parameters, and ultimately optimizing the production process.

Analysis of the Effect of Skew Rolling Parameters on the Surface Roughness of C60 Steel Products Using ML Methods.

This paper presents results from experimental and numerical studies of the skew rolling process used to shape axisymmetric products made of C60-grade steel. An experimental study was carried out to investigate the effect of process parameters described by the forming angle α, the skew angle θ, the reduction ratio δ, and the jaw chuck velocity Vu on the surface roughness Ra of the forgings. Stepped forgings made of C60-grade steel were rolled. Based on numerical calculations, a machine learning regression model was developed that uses process parameters to predict the surface roughness of produced parts. The random forest model was found to be the most effective based on the determined metrics (MAE, RMSE, R2). A more detailed analysis of this model was performed using the SHAP library. The application of ML methods will enable optimization of skew rolling through appropriate selection of process parameters affecting improvement in product quality.

Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance.

In recent years, there has been a growing interest in the field of 3D printing technology. Among the various technologies available, fused deposition modeling (FDM) has emerged as the most popular and widely used method. However, achieving optimal results with FDM presents a significant challenge due to the selection of appropriate process parameters. Therefore, the objective of this research was to investigate the impact of process parameters on the tribological and frictional behavior of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) 3D-printed parts. The design of experiments (DOE) technique was used considering the input design parameters (infill percentage and layer thickness) as variables. The friction coefficient values and the wear were determined by experimental testing of the polymers on a universal tribometer employing plane friction coupling. Multi-response optimization methodology and analysis of variance (ANOVA) were used to highlight the dependency between the coefficient of friction, surface roughness parameters, and wear on the process parameters. The optimization analysis revealed that the optimal 3D printing input parameters for achieving the minimum coefficient of friction and linear wear were found to be an infill percentage of 50% and layer thickness of 0.1 mm (for ABS material), and an infill percentage of 50%, layer thickness of 0.15 mm (for PLA material). The suggested optimization methodology (which involves minimizing the coefficient of friction and cumulative linear wear) through the optimized parameter obtained provides the opportunity to select the most favorable design conditions contributing to a more sustainable approach to manufacturing by reducing overall material consumption.

RSM design-based hybrid approach to multi-response optimization in milling Ti-6Al-4 V alloy: A comparative study

The Selection of appropriate process parameters in milling Ti-6Al-4 V alloy to reduce energy and power consumption while maintaining product quality and process stability is challenging. This study aims to optimize process parameters in milling Ti-6Al-4 V alloy with five primary criteria i.e., average cutting force, shear stress, specific cutting energy, power consumption, and average surface roughness. A total of 26 experimental tests was carried out with the variation of process parameters such as cutting speed (m/min), feed rate (mm/min), and depth of cut (mm) based on the Box-Behnken design (BBD) matrix of response surface method (RSM) under dry and high-pressure cooling (HPC). The criteria importance through the inter-criteria correlation (CRITIC) method was used to determine the relative weights of each response. At the same time, the evaluation of optimum process parameters was done by hybrid multi-response optimization (MRO) techniques such as complex proportional assessment (CRITIC-COPRAS), additive ratio assessment (CRITIC-ARAS), combined compromise solution (CRITIC-COCOSO) and technique for order of preference by similarity to ideal solutions (CRITIC-TOPSIS). After the evaluation, a cutting speed of 32 m/min, feed rate of 22 mm/min, and 0.75 mm depth of cut with HPC were selected as the optimum process parameters. Due to the lack of an identical solution, the sensitivity of the used MRO methods was checked out with the weight variation of the selected criteria. TOPSIS was noticed as the most robust MRO method with less sensitivity. Spearman’s Correlation coefficient was used to assess the correlation among the used hybrid MRO methods.

Processing diagram for powder bed additive manufacturing

This paper presents the developed software for processing parameter simulation and optimization of powder bed additive manufacturing by concentrated energy beams. The simulations are realized by implementation of a normalized processing diagram and analytical model simulating heating of powder layers by a moving linear heat source. Their implementation is demonstrated for electron beam or laser additive manufacturing of industrial alloys. The developed software and the processing diagram provide a useful reference and methodology to support the selection of appropriate processing parameters during the early development stages of concrete powder bed additive manufacturing technology, building production digital twins or development of integrated process management system.

Biofunctional impact of textured coatings in the application of heart assist therapy

Due to a lack of organs, cardiac support systems are being implanted in patients with severe congestive heart failure. One of the solutions to overcome complications such as inflow obstruction or pump thrombosis, which may occur in the case of ventricular assist devices, is to modify the surface of cannulas for the controlled blood clotting process. The results obtained up till now for developed surface coatings clearly show the influence of topographical and mechanical parameters of the coatings on cell viability and protein adsorption mechanism. The new coatings should enable the controlled growth of scar tissue, resulting in the limitation of thromboembolic events, and the reduction of cystic tissue growth into the flow lumen. The aim of this study is to evaluate the correlation between surface topography parameters on the susceptibility of cells to grow and adhere to the substrate as a solution with potential for use in MCS (mechanical circulatory support) devices. Research on surfaces used in MCS devices and on inflow cannulas has been carried out for many years, while the novelty of the present solution makes it a milestone within that type of application simultaneously allowing for appropriate selection of process parameters. Surface modification of titanium alloy Ti6Al7Nb was carried out using vacuum powder sintering of CP-Ti (commercially pure titanium) powder with two morphologies (regular spheres and irregular grains). The characterization of coatings obtained with the proposed method and the influence of measured topographic parameters (applying scanning electron microscopy, contact angle measurement and contact profilometry) on the cytotoxicity and susceptibility to protein adsorption were presented. Advanced albumin adsorption studies have fully confirmed the dependence of surface complexity on protein adsorption. The obtained results show a high potential of the produced coatings toward enabling permanent integration at the implant with the soft tissue.

An improved time-varying stability analysis of micro milling considering tool wear

Micro-milling is widely used to process micro-parts and structures, which has the advantages of high material removal rate, high precision and high flexibility of applicable materials. The chatter in micro-milling process seriously reduces the machining efficiency and surface quality. The existing researches are focusing on a selection of appropriate process parameters to suppress the occurrence of chatter, while the influence of tool wear has rarely been considered. In this work, an improved time-varying stability analysis of micro milling considering tool wear was studied. A modified force model taking tool wear, bottom edge milling force, tool runout, and size effect into consideration was established. The dynamic forces due to regenerative undeformed chip thickness in both the shearing region and the transition region were investigated. A dynamic equation which combined the modified force model and the dynamic forces was developed and solved for stability analysis. Experiments on micro-milling of Ti-6Al-4 V titanium alloy with coated micro-milling tools, were carried out to verify the improved time-varying stability analysis model. The results showed that the modified force model had relatively high prediction accuracy, and the calculated stability lobe diagram (SLD) of micro-milling considering tool wear was verified. This work offers theoretical and technical guidance toward the improvement of chatter stability and the development of process online monitoring in micro-milling.

STEP-NC Process Planning for Powder Bed Fusion Additive Manufacturing

Abstract Powder bed fusion (PBF) is an additive manufacturing (AM) technology that uses high-power beams to fuse powder material into layers of scanned patterns, thus producing parts with great geometric complexity. For PBF, the selection of appropriate process parameters, environmental control, and machine functions play critical roles in maintaining fabrication consistency and reducing potential part defects such as cracks and pores. However, poor data representations in the form of approximated geometry and incoherent process plans can negatively impact the relationship between the selected parameters. To address this issue, the Standard for the Exchange of Product model data Numerical Control (STEP-NC) recently added standardized data entities and attributes specifically for AM applications. Yet, the current STEP-NC data representations for AM do not have definitions for process parameters and scan strategies that are commonly used in PBF processes. Therefore, there is a need for defining data models that link process parameters with process control. To bridge this gap, in this paper, an amended STEP-NC compliant data representation for PBF in AM is proposed. Specifically, the characteristics of the interlayer relationships in PBF, along with the technology and scan strategy controls, are defined. Simulation results demonstrate the feasibility of granular process planning control and the potential for producing high-quality parts that meet geometric requirements and tight tolerances. The contributions of this paper highlight the importance of information models in AM, promoting data representations as key enablers of the AM technology and supporting the neutrality and interoperability of data across AM systems.

Multi criteria decision making through TOPSIS and COPRAS on drilling parameters of magnesium AZ91

Magnesium (Mg) alloys are extensively used in the automotive and aircraft industries due to their prominent properties. The selection of appropriate process parameters is an important decision to be made because of the cost reduction and quality improvement. This decision entails the selection of suitable process parameters concerning various conflicting factors, so it has to be addressed with the Multiple Criteria Decision Making (MCDM) method. Therefore, this work addresses the MCDM problem through the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and COPRAS (COmplex PRoportional ASsessment) methods. The assessment carried out in the material Mg AZ91 with the Solid Carbide (SC) drill bit. The dependent parameters like drilling time, burr height, burr thickness, and roughness are considered with the independent parameters like spindle speed and feed rate. Drilling alternatives are ranked using the above said two methods and the results are evaluated. The optimum combination was found on the basis of TOPSIS and COPRAS for simultaneous minimization of all the responses which is found with a spindle speed of 4540 rpm and a feed rate of 0.076 mm/rev. The identical sequencing order was observed in TOPSIS and COPRAS method. The empirical model was developed through Box-Behnken design for each response. Superior empirical model developed for drilling time which is 3.959 times accurate than the conventional equation. The trends of various dependents based on the heterogeneity of various independents are not identical, these complex mechanisms are identified and reported. The optimized results of the Desirability Function Approach are greater accordance with the TOPSIS and COPRAS top rank. The confirmation results are observed with lesser deviation suggesting the selection of the above independent parameters.

Evaluating Suitable Weld Condition to Obtain Enlarged Bead Width of 316 Stainless Steel Towards Weld Cladding

Usually bead-on-plate welding is performed to standardize process parameters before cladding. Selection of appropriate process parameters plays a vital role for achieving good weld bead geometry. In this experimental investigation, Metal Active Gas Welding is used with 316 austenitic stainless steel wire electrode. An experimental design for Response Surface Methodology named, Box-Behnken (Three Variable) design is adopted for determining the experimental runs. Heat input of 0.6kJ/mm and higher than this can be used to obtain desirable bead-on-plate welding that may also be recommended for weld cladding for this substrate-filler material combine.

Process parameter optimization of metal additive manufacturing: a review and outlook

The selection of appropriate process parameters is crucial in metal additive manufacturing (AM) as it directly influences the defect formation and microstructure of the printed part. Over the past decade, research efforts have been devoted to identifying "optimal" processing regimes for different materials to achieve defect-free manufacturing, which mostly involve costly trial-and-error experiments and computationally expensive mechanistic simulations. Hence, it is apropos to critically review the methods used to achieve the optimal process parameters in AM. This work seeks to provide a structured analysis of current methodologies and discuss systematic approaches toward general optimization work in AM and the process parameter optimization of new AM alloys. A brief review of process-induced defects due to process parameter selection is given and the current methods for identifying "optimal processing windows" are summarized. Research works are analyzed under a standard optimization framework, including the design of experiments and characterization, modelling and optimization algorithms. The research gaps that preclude multi-objective optimization in AM are identified and future directions toward optimization work in AM are discussed. With growing capabilities in AM, we should reconsider what the definition of the "optimal processing region".

Influence of Fe Dilution and W Dissolution on Abrasive Wear Resistance of NiCrBSi–WC Composite Hardfacing Deposited by Plasma Transferred arc Hardfacing

The control of Fe dilution and carbide dissolution plays a vital role on the performance of metal matrix composite hardfacings. In this paper, the NiCrBSi–WC composite hardfacing is deposited on 304 austenitic stainless steel by plasma transferred arc hardfacing at 120[Formula: see text]A (specimen 1) and 140[Formula: see text]A (specimen 2) transferred arc current values to obtain different levels of Fe dilution and W dissolution for comparative investigations. The Fe dilution examined by scanning electron microscopy for specimen 1 was 24.54% and for specimen 2 was 33.09%. The microstructural investigations revealed higher W dissolution for specimen 2 due to higher heat input which led to significant reduction in the amount of WC and W2C hard phases. The slurry abrasive wear test performed as per ASTM G105 showed two times reduction in abrasive wear resistance of specimen 2 as compared to specimen 1. The significant reduction in the performance of specimen 2 is mainly due to higher Fe dilution and higher W dissolution caused due to higher heat input. Hence, selection of appropriate process parameters is vital to control Fe dilution and carbide dissolution in order to achieve superior performance of composite hardfacings.

Effect of sheet thickness on the fusion zone temperature distribution, melt pool dimensions, mechanical properties, and microstructure in laser welding of Ti6Al4V alloy

Generally, sheet thickness plays a significant role in the selection of appropriate process parameters in order to produce high quality weld joint in the laser welding process. The heat sink capacity and weld penetration are known as two criteria that are mainly influenced by sheet thickness. In this study, the effect of sheet thickness, welding speed, nozzle distance, and laser power were investigated in order to determine the temperature distribution near the melt pool, dimensions of molten pool through experimental and numerical analysis. The weld joint mechanical characterization was determined via elongation rate and tensile strength. The highest value of tensile strength is about 80% of the typical base metal and the elongation of the welded samples achieved about 40% of the base metal. The thinner sheets showed more sensitivity related to the elongation of the joint by increasing the welding speed. Also, the temperature rise with increasing laser power near the melt pool for the thinner sheet was about 200 °C in comparison to the 3 mm sheet, which is about 90 °C. The obtained simulation results for the maximum temperature discrepancy at near the melt pool was 12 °C and 4 °C for 1 and 3 mm thickness orderly, which depicts good agreement with the temperature experimental results.