Effect Of Process Parameters Research Articles

Parametric process optimisation of automated fibre placement (AFP) based AS4/APC-2 composites for mode I and mode II fracture toughness

In-situ consolidation of thermoplastic composites using Automated Fibre Placement (AFP) technology is an emerging manufacturing technique, offering tailored composite properties through customised processing parameters. Multiple competing parameters during AFP manufacturing influence the quality and mechanical performance of the laminates. These lay-up parameters are interrelated, and often require comprehensive experimental characterisation which is costly and time-intensive. This study aims to optimise the fracture toughness of in-situ consolidated thermoplastic composite (AS4/APC-2) and investigate the mechanisms that contribute to it. Taguchi’s method is employed to efficiently analyse the effect of various process parameters at multiple levels. Based on the obtained results, a considerable effect of process parameters on Mode I and II fracture toughness is observed. The statistical analysis reveals that the Hot Gas Torch (HGT) temperature required for AFP processing significantly affects the Mode I fracture toughness, contributing to 33.8%. Whereas, the consolidation force, another key processing parameter in AFP notably affects Mode II fracture toughness, with the contribution of 81.8%. The analysis of variance (ANOVA) reveals interdependent processing parameter relations for both fracture modes. A validation test showed good agreement between the predicted fracture toughness and the experimental test.

Progress in the Study of Quality and Mechanical Properties of Selective Laser Melting Molded Parts

Abstract: Selective laser melting (SLM) is considered to be a widely promising additive manufacturing technology with the advantages of high machining precision, high manufacturing freedom, and short cycle time, which is widely used in aerospace, the integration of medicine, and industry, chemical, and other fields. The research progress on the temperature field, stress field, forming quality, and mechanical properties during the SLM manufacturing process is reviewed. The study aims to systematically analyze how SLM process parameters affect the temperature field, stress field, forming quality, and mechanical properties, and to discuss the importance of the selection of process parameters and performance regulation to achieve high-quality, highperformance metal parts. The effects of SLM process parameters on temperature field, stress field, surface roughness, densification, hardness, strength, and fatigue properties are analyzed and summarized. The importance of process parameters in the SLM forming procedure in the quality of formed components is emphasized, and conducting an in-depth study on the optimization and performance regulation of the process parameters is of great significance in achieving the high quality and performance of metal parts. With the rapid advancement of technology, the potential of SLM technology in terms of molding quality and mechanical performance has become increasingly significant, heralding significant breakthroughs. These potential breakthroughs will greatly promote the widespread application of SLM technology in various industries, thus more efficiently meeting the growing needs and expectations of industries such as petrochemicals, transportation, aerospace, nuclear energy, as well as food and medical sectors.

System Design, Modelling, Energy Analysis, and Industrial Applications of Ohmic Heating Technology

AbstractThe food and drink industry is gradually gaining sustainability pressure due to the high carbon emissions rate and limited availability of traditional energy supplies. Thus, it is essential to consider energy efficiency and decarbonisation of the ever-expanding food and drink industry. Ohmic heating technology is a highly energy-efficient and quick method of electrically heating food products. It uses the resistance of the food material to convert electrical energy into heat. However, the heating rate of ohmic heating depends on several process variables, such as electrical conductivity, voltage gradient, and voltage frequency. Therefore, it is important to study and understand the effects of these process variables to optimise the modelling and control of ohmic heating systems to obtain desirable output from food products. Hence, this study presents a review of the effects of process parameters on nutritional and organoleptic qualities, product yields, and energy efficiency of ohmic heating, along with its various industrial applications. The technology shows promising advancements in colour and nutritional quality, increasing energy efficiency, shorter processing times, and higher product yields compared to conventional heating processes.

Thermal cycle behaviour of plasma sprayed thermal barrier coatings on cast iron substrate for the application of liner of internal combustion engine

In the present scenario, research on Thermal Barrier Coatings (TBCs) is attracting significant attention in high-temperature applications due to the rising demand in industrial applications, such as gas turbine blades and internal combustion engine components. To meet these demands, it is essential to enhance the mechanical and oxidation properties of thermal barrier coatings. The atmospheric plasma spray methodology for producing these coatings has become a central focus in recent times. In this work, TBCs were prepared by blending pure alumina and Yttria-Stabilized Zirconia (YSZ) in equal proportions. Extensive study of TBCs carried out under high-temperature conditions through thermal cycle tests at elevated temperatures, around 850 °C. A total of 350 thermal cycles were conducted, and microstructures of the coating surface were examined at 150, 250, and 350 cycles. High-temperature stress, generated due to the sintering of the coating, also influences the life of the coatings. Specimen with a topcoat thickness of 300 μm, exhibited good thermal shock resistance compared to the specimens with topcoats of thickness of 100 μm and 200 μm. The effects of process parameters, porosity, and thermal shock resistance are presented in detail. The topcoat with a thickness of 300 μm demonstrated excellent thermal shock resistance and reduced formation of thermally grown oxide (TGO). The porosity of the coating, found to be between 2% and 3%, contributed to its dense nature, effectively reducing oxidation rates and enhancing the coating's lifespan under cyclic high-temperature conditions.

Preparation and Wear Resistance of Porous TC4 Titanium Alloy Micro‐arc Oxidation Coating Produced by Selective Laser Melting

The porous TC4 titanium alloy prepared by selective laser melting (SLM) is modified by micro‐arc oxidation (MAO) technology. By introducing active elements such as calcium (Ca) and phosphorus (P) into the electrolyte, a wear‐resistant active coating is constructed on the surface of porous TC4. The effects of MAO process parameters on the surface morphology and wear resistance of the coating are discussed. The results show that the thickness and adhesion of the coating increase with the increase of the first‐stage oxidation time, and decrease with the increase of the second‐stage oxidation time. In all processes, the MAO‐2 coating has better surface morphology and performance, with a median pore size of 0.51 μm and a binding force of 18 N. XPS analysis confirms that the coating is mainly composed of TiO2, Ca2P2O7, and Ca(PO3)2 phases. The study of tribological behavior shows that the wear form of the substrate is abrasive wear, while the wear form of the coating is adhesive wear. The friction coefficient of the coating is significantly lower than that of the substrate, and the wear resistance is better. This study provides an effective way to optimize the surface properties of porous TC4 titanium alloy.

Optimization of Multi-Performance Parameters in EDM through Grey Relational Analysis using Deionized Water

This study includes an experimental study of the effect of input process parameters on output parameters during the EDM of C-20 mild steel. Deionized water is being investigated as a sustainable alternative to Electrical Discharge Machining (EDM) oil, reducing toxic emissions and enhancing process sustainability. ANOVA results revealed that current and voltage had the largest impact on MRR, while TON significantly affected TWR and TON had the greatest influence on surface roughness. The study found that increasing the current and voltage resulted in significant increases in MRR (164.78% and 99.49%, respectively) and TWR (21.19% and 26.02%, respectively). However, an improve in TON led to a decrease in TWR (by 66.7%) but an increase in MRR (by 59.57%). Increased current, voltage, and TON result in a 74.34%, 72.14%, and 108.15% improvement in surface roughness, respectively. The Grey relational analyses were used for best optimum result which comes on parameters current 12 amps, voltage 20 volts and TON 200 μs.

Influence of Process Parameters on Selected Properties of Ti6Al4V Manufacturing via L-PBF Process.

This study investigates the microstructural effects of process parameters on Ti6Al4V alloy produced via powder bed fusion (PBF) using laser beam melting (LB/M) technology. The research focuses on how variations in laser power, exposure velocity, and hatching distance influence the final material's porosity, microhardness, and microstructure. To better understand the relationships between process parameters, energy density, and porosity, a simple mathematical model was developed. The microstructure of the alloy was analyzed in the YZ plane using a confocal microscope. The study identified optimal parameters-302.5 W laser power, 990 mm/s exposure velocity, and 0.14 mm hatching distance-yielding the lowest porosity index of 0.005%. The material's average hardness was measured at 434 ± 18 HV0.5. These findings offer valuable insights for optimizing printing parameters to produce high-quality Ti6Al4V components using PBF-LB/M technology, shedding light on the critical relationship between process parameters and the resulting microstructure.

Effect of Vibration Pretreatment-Microwave Curing Process Parameters on the Mechanical Performance of Resin-Based Composites.

The vibration pretreatment-microwave curing process can achieve high-quality molding under low-pressure conditions and is widely used in the curing of resin-based composites. This study investigated the effects of the vibration pretreatment process parameters on the void content and the fiber weight fraction of T700/TRE231; specifically, their influence on the interlaminar shear strength and impact strength of the composite. Initially, an orthogonal experimental design was employed with interlaminar shear strength as the optimization target, where vibration acceleration was determined as the primary factor and dwell time as the secondary factor. Concurrently, thermogravimetric analysis (TGA) was performed based on process parameters that corresponded to the extremum of interlaminar shear strength, revealing a 2.17% difference in fiber weight fraction among specimens with varying parameters, indicating a minimal effect of fiber weight fraction on mechanical properties. Optical digital microscope (ODM) analysis identified interlaminar large-size voids in specimens treated with vibration energy of 5 g and 15 g, while specimens subjected to a vibration energy of 10 g exhibited numerous small-sized voids within layers, suggesting that vibration acceleration influences void escape pathways. Finally, impact testing revealed the effect of the vibration pretreatment process parameters on the impact strength, implying a positive correlation between interlaminar shear strength and impact strength.

The Use of Natural Minerals as Reinforcements in Mineral-Reinforced Polymers: A Review of Current Developments and Prospects.

Natural minerals play a key role in the burgeoning field of mineral-reinforced polymers, providing an important element in strengthening and toughening the properties of composite materials. This article presents a comprehensive overview of the use of minerals in mineral-reinforced polymers, covering various aspects of their applications and impact on the final properties of these materials. The potential of various types of natural minerals (for example talc, montmorillonite, halloysite, diatomite) as reinforcements in mineral-reinforced polymers is discussed. Techniques for producing mineral-reinforced polymers using minerals, including the mixing method, impregnation, and coating application, are presented in detail. In addition, the effects of process parameters and component ratios on the final properties of mineral-reinforced polymers are discussed. The latest research on the use of minerals in mineral-reinforced polymers is also presented, including their effects on the strength, stiffness, resistance to environmental conditions, and biodegradation of the materials. Finally, the development prospects and potential applications of mineral-reinforced polymers with minerals in various industrial sectors, including packaging, automotive, construction, and medicine, are discussed.

Optimization of the Femtosecond Laser Machining Process for Single Crystal Diamond Using Response Surface Methodology

Femtosecond laser machining offers high precision and minimal thermal impact, making it a promising technique for processing hard and brittle materials like single-crystal diamonds (SCDs). In this study, the femtosecond laser machining process for SCD material was systematically optimized to improve both machining efficiency and quality. Initial single-factor experiments were conducted to explore the effects of key process parameters—laser power, scanning speed, and number of scans—on machining performance. Subsequently, response surface methodology (RSM)-based experiments designed using the Box–Behnken method were employed to comprehensively refine the process. A regression model was developed to analyze the data, and the interaction effects of the parameters were thoroughly evaluated. The validated model identified an optimal set of parameters, resulting in a significant improvement in machining performance. This research provides a comprehensive framework for optimizing femtosecond laser machining processes, offering valuable insights critical for the production of advanced lightweight components in industries such as aerospace, optical instruments, and high-performance electronics.

Characterization of TiC particle reinforced magnesium matrix composites (MMCs) prepared by laser cladding based on element evaporation

In this study, we report the preparation of AZ31/TiC composites by laser cladding based on elemental vaporization and supplementation and investigate the effects of laser process parameters and mixed powder ratio on the vaporization and spattering. It was found that the capillary pressure generated by using TiC could effectively suppress the molten pool sputtering during laser cladding. In addition, TiC particles promoted the recrystallisation behavior of the molten pool, and the grains were significantly refined from 61.58 μm to 6.46 μm. The random orientation of the recrystallized grains led to a weaker texture, decrease from 12.349 to 1.964. The microhardness of the composites higher than AZ31 from 46 to 86.2 HV0.2, and the average wear rate was reduced by 21.9%.

Investigating amplitude amplification in optimization-based control for a continuous stirred tank reactor

Quantum computers, which utilize quantum states called ‘qubits’ to process information, are becoming of increased interest in a variety of fields because they have the potential to outperform classical computers in certain situations. However, many challenges and hurdles remain, including the development of quantum algorithms that offer a speedup and can be applied to practical problems (some quantum algorithms that offer a speedup may only be applicable in specific and sometimes contrived circumstances). Our previous works have studied the use of quantum computers and quantum algorithms for process control applications. Our prior work evaluated the use of a gate-based quantum amplitude amplification algorithm when applied to a model predictive control optimization problem, specifically evaluating a linear systems example. The results suggested that the algorithm may be suited for the specific linear problem studied (meaning that there is a high probability of obtaining the desired result when measuring the quantum state after the algorithm has been applied). However, the results cannot be generalized to a wider class of systems or to systems containing nonlinearities. To begin to gain an understanding of how the amplitude amplification algorithm might be generalized, this work evaluates the use of the algorithm for the optimization-based control of a nonlinear dynamic system (specifically, a continuous stirred tank reactor). We seek to understand aspects of the problem, such as the development of a solution space, the effects of changing process and control parameters, and the operation of the amplitude amplification algorithm itself. The results demonstrate the challenges that still exist, and demonstrate a method involving inverse sampling transformations to potentially aid in addressing these issues.

Preparation of alginate beads by ionic gelation method using Encapsulator B-390: Effect of process parameters on physical properties of beads

Preparation of alginate beads by ionic gelation method using Encapsulator B-390: Effect of process parameters on physical properties of beads

Biohydrogen generation from distillery effluent using baffled up‐flow microbial electrolysis cell

AbstractMicrobial electrolysis cell (MEC) is gaining importance not only for effectively treating wastewater but also for producing hydrogen. The up‐flow microbial electrolysis cell (UPMEC) is an innovative approach to enhance the efficiency, and substrate degradation. In this study, a baffled UPMEC with an anode divided into three regions by inserting the baffle (sieve) plates at varying distances from the cathode was designed. The effect of process parameters, such as flow rate (10, 15, and 20 mL/min), electrode area (50, 100, and 150 cm2), and catholyte buffer concentration (50, 100, and 150 mM) were investigated using distillery wastewater as substrate. The experimental results showed a maximum of 0.6837 ± 0.02 mmol/L biohydrogen at 150 mM buffer, with 49 ± 1.0% COD reduction using an electrode of area 150 cm2. The maximum current density was 1335.94 mA/m2 for the flow rate of 15 mL/min and surface area of 150 cm2. The results showed that at optimized flow rate and buffer concentration, maximum hydrogen production and effective treatment of wastewater were achieved in the baffled UPMEC.Practitioner Points Biohydrogen production from distillery wastewater was investigated in a baffled UPMEC. Flowrate, concentration and electrode areas significantly influenced the hydrogen production. Maximum hydrogen (0.6837±0.02mmol/L.day) production and COD reduction (49±1.0%) was achieved at 15 mL/min. Highest CHR of 95.37±1.9 % and OHR of 4.6±0.09 % was observed at 150 mM buffer concentration.

Experimental investigation into friction stir welding of AA6061-T6 and magnesium AZ31B alloy using copper backing plate

Aluminium-magnesium alloys are lightweight and possess superior properties, making them ideal for applications in aerospace, railway, automotive, and marine structures. However, these alloys are challenging to fabricate using traditional fusion welding due to various metallurgical issues. This study investigates the feasibility of joining 3 mm thick dissimilar alloys of aluminium AA6061-T6 and magnesium AZ31B using the friction stir welding (FSW) process with copper as a backing plate. The effects of FSW process parameters, including tool rotational speed (380, 545, 765 rpm), weld speed (20, 31.5, 50 mm min−1), and tilt angle (1°, 2°, 3°), on tensile properties were examined using Taguchi-based grey relational analysis. Temperatures were recorded during the FSW process under different conditions on both sides of the joint. The highest tensile strength of 130.72 MPa, with a joint efficiency of 67.85%, was achieved at a tool rotational speed of 765 rpm, a welding speed of 50 mm min−1, and a tilt angle of 2°. Analysis of variance (ANOVA) for the grey relational grade indicated that the tilt angle had the highest percentage contribution of 43.60%. This study demonstrates the significant influence of FSW parameters on the mechanical properties of aluminium-magnesium joints and highlights the optimal conditions for achieving high joint strength and efficiency.

Adsorption parameters optimization of spent coffee ground biochar for methylene blue removal using response surface methodology

This study investigates the potential of spent coffee ground biochar (SCGB) as a sustainable and cost-effective adsorbent for the removal of methylene blue (MB), a hazardous dye commonly used in the textile and printing industries. A response surface methodology (RSM) approach with central composite design (CCD) was employed to systematically investigate the effects of key process parameters, including adsorbent dosage, solution pH, contact time and temperature, on MB removal efficiency. The analysis revealed that adsorbent dosage and temperature as critical factors influencing MB removal, with a linear model providing a strong correlation. Optimal conditions for MB removal were determined to be 0.99 g of SCGB, 30 min of contact time, 30 °C temperature, and a solution pH of 7. Under these conditions, MB removal reached 99.99%, with a desirability of 1.000. The experimental results closely matched the predicted values, differing by only 0.02%, thus validating the accuracy of the model. Kinetic studies indicated a rapid adsorption process, well-described by both pseudo-first and pseudo-second order models. Isotherm analysis confirmed the applicability of the Freundlich model, suggesting favorable adsorption with increasing MB concentration. The high adsorption capacity of SCGB is attributed to its carbonaceous and porous structure, highlighting its potential as an effective adsorbent for dye removal in wastewater treatment applications.

Quality Prediction Algorithm for Flow Drilling Screw Joining of 590 MPa High-Strength Steel and 6xxx Series Aluminum Alloy

Flow drilling screw (FDS) process is applied to various components such as car bodies and battery cases due to its advantage of enabling one-sided joining. Various studies have been conducted on the correlation between monitored process parameters and joint quality. These correlations suggest the potential for non-destructive classification or prediction of joint quality using process monitoring signals. In this study, the effect of FDS process parameters on joint quality was analyzed, and a decision tree-based quality prediction model for classifying joint quality was developed. The material combination consisted of a 1.8 mm thick SGAFC 590DP as the upper plate and a 3.0 mm thick Al 6061 as the lower plate. To develop the joint quality prediction algorithm, the effect of process parameters in each process step on joint quality was analyzed. It is used as input data to identify various features. The output data were generated by classifying the products into three categories from class 0 to class 2. Based on the extracted feature data, a machine learning algorithm was trained to develop the joint quality prediction model.

Research on the process of preparing fiber filtration membrane by centrifugal blowing electrospinning technology

AbstractCurrently, the problem of air pollution is getting more and more serious, especially the pollution of tiny solid particles (PM, particulate matter) in the air, which poses a great challenge to the environment and human health. Therefore, it is particularly important to develop air filtration materials with high filtration efficiency and low resistance to meet this challenge. In this study, we propose to prepare air filtration membranes by centrifugal jet electrospinning technology, design multifactorial orthogonal coupling experiments, and investigate the effects of key process parameters of centrifugal jet electrostatic spinning, including solution concentration, airflow rate, rotational speed, and voltage, on the fiber diameter and uniformity by applying the polar analysis of variance and analysis of variance. PAN‐BaTiO3 electret nanofiber filtration membranes with high efficiency and low resistance were prepared by combining the optimized process of centrifugal blowing electrospinning. Various characterization methods (tensile test, water contact angle test, surface charge test, filtration test) were used to evaluate the effect of different BaTiO3 electret contents (0%, 0.1%, 0.5%, 1%) on the comprehensive performance of the filtration membranes, and the electret filtration efficiency of the electret filtration membranes prepared by the present process reached as high as 96.56% with a pressure drop of 29 Pa.

Exploring Osmotic Dehydration for Food Preservation: Methods, Modelling, and Modern Applications.

This study summarizes the most recent findings on osmotic dehydration, a crucial step in food preservation. The many benefits of osmotic dehydration are listed, including longer shelf life and preserved nutritional value. Mass transfer dynamics, which are critical to understanding osmotic dehydration, are explored alongside mathematical models essential for comprehending this process. The effect of osmotic agents and process parameters on efficacy, such as temperature, agitation and osmotic agent concentration, is closely examined. Pre-treatment techniques are emphasized in order to improve process effectiveness and product quality. The increasing demand for sustainability is a critical factor driving research into eco-friendly osmotic agents, waste valorization, and energy-efficient methods. The review also provides practical insights into process optimization and discusses the energy consumption and viability of osmotic dehydration compared to other drying methods. Future applications and improvements are highlighted, making it an invaluable tool for the food industry.

Research Paper on Analytical Investigation of the Effect of 3d Printing Process Parameters on Anisotropic Mechanical Behaviour of Additively Constructed Concrete

This research identifies key challenges in additively constructed concrete, including the need for understanding the scalability of mechanical behaviour from small to large structures, addressing variability in material properties, and predicting failure mechanisms. It highlights the need for improved finite element modelling for accurate 3DCP simulation, and further investigation into concrete foundation interactions and initial imperfections. The study acknowledges difficulties in simulating complex shapes and calls for refinement of the numerical model for better predictive accuracy. It also emphasizes the need to understand long-term behaviour, durability, and the impact of the 3DCP process on microstructural morphology and mechanical properties. The influence of pores and time gaps between layers on the overall capacity of the specimen, and the development of a model considering different properties of 3D concrete material are also identified as areas for future research.