Orthogonal Array Design Research Articles

Optimization of Friction Stir Welding Parameters for AA6061-T651 Aluminum Alloy: Defect Analysis and Process Improvement


 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Friction Stir Welding (FSW) is an eco-friendly process known for high-quality joints without filler metal. This study investigated the physical properties of FSW-welded joints in AA6061-T651 aluminum alloy by varying the concave shoulder angle. Optimal process parameters were determined through Taguchi optimization using an Orthogonal Array design. Macro and micro testing revealed overlap defects, kissing bond defects, and wormholes in some samples. Systematic experimentation identified key parameters to avoid defects, including tool rotation speed, welding speed, tool tilt angle, tool indentation angle, and shoulder depth. Visual inspection and microstructural analysis played a crucial role in assessing weld quality. Optimizing welding parameters, such as rotational speed, welding speed, temperature, and tool geometry, was highlighted as crucial for defect-free joints. The study offers valuable insights for researchers and professionals in the field, promoting the advancement and application of FSW in aluminum alloy welding.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Highlight:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 FSW: An environmentally friendly welding process with good joint quality.
 Defect Analysis: Identification of overlap defects, kissing bond defects, and wormholes in welded joints.
 Process Optimization: Determination of optimal parameters to avoid defects, including tool rotation speed, welding speed, tool tilt angle, tool indentation angle, and shoulder depth.
 
 Keyword:
 Friction Stir Welding, AA6061-T651 Aluminum Alloy, Welded Joint Analysis, Process Optimization, Defect Prevention

Valorization of e-waste via supercritical water technology: An approach for obsolete mobile phones

The improper handling of electronic waste has not only severe environmental impacts but also results in the loss of high economic potential. To address this issue, the use of supercritical water (ScW) technology for the eco-friendly processing of waste printed circuit boards (WPCBs) obtained from obsolete mobile phones has been explored in this study. The WPCBs were characterized via MP-AES, WDXRF, TG/DTA, CHNS elemental analysis, SEM and XRD. A L9 Taguchi orthogonal array design was employed to evaluate the impact of four independent variables on the organic degradation rate (ODR) of the system. After optimization, an ODR of 98.4% was achieved at a temperature of 600 °C, a reaction time of 50 min, a flowrate of 7 mL min−1, and the absence of an oxidizing agent. The removal of the organic content from the WPCBs resulted in an increase in the metal concentration, with up to 92.6% of the metal content being efficiently recovered. During the ScW process, the decomposition by-products were continuously removed from the reactor system through the liquid or gaseous outputs. The liquid fraction, which was composed of phenol derivatives, was treated using the same experimental apparatus, achieving a total organic carbon reduction of 99.2% at 600 °C using H2O2 as the oxidizing agent. The gaseous fraction was found to contain hydrogen, methane, CO2, and CO as the major components. Finally, the addition of co-solvents, namely ethanol and glycerol, enhanced the production of combustible gases during the ScW processing of WPCBs.

Optimization of Micro-Drilling of Laminated Aluminum Composite Panel (Al-PE) Using Taguchi Orthogonal Array Design.

Aluminum Matrix Composite (AMC) represents an innovative class of materials that is extensively utilized in industries such as automotive, defense, aerospace, structural engineering, sports, and electronics. This study investigates the thrust force, exit burr formation, changes in the micro-tool, and drilled hole diameters during the micro-drilling of an aluminum-polyethylene composite panel (Al-PE). The panel consists of 3501 series aluminum skin materials bonded to a polyethylene (PE) core. Micro-drilling test parameters were designed using Taguchi's L16 (42 23) orthogonal array. Tests were conducted with five control parameters: cutting speed with four levels (10 m/min, 20 m/min, 30 m/min, 40 m/min), feed rate with four levels (0.5 µm/rev, 1 µm/rev, 2 µm/rev, 4 µm/rev), the tool diameter with two levels (0.7 mm, 1 mm), and tool point angle with two levels (100°, 140°) using both AlTiN-coated and uncoated drills. The maximum thrust force (Fz), maximum burr height, and changes in both the drill tool and hole diameters were measured for analysis of variance (ANOVA). The results showed that, in terms of impact on Fz, tool point angle had the highest positive influence (64.54%) on the micro-drill at the entrance of composite (upper aluminum plate). The cutting speed had the highest positive influence (45.32%) on the tool in the core layer (PE core layer). The tool point angle also had the highest positive influence (68.95%) on the micro-drill at the lower layer of the composite (the lower aluminum plate). There was noticeable chip adhesion on the major cutting edge and nose area under micro-drilling conditions with higher thrust forces and burr height. The AlTiN coating had a positive effect on tool wear and hole diameter deviations, but it adversely affected the burr height.

Experimental investigation on grout propagation in poured aggregates for controlling water inrush in tunnels with flowing water

BackgroundIn recent years, the technology of blocking and grouting of has been widely used in the treatment of groundwater inrush in tunnels in China’s mines. Studies have been carried out on the aggregates pouring under hydrodynamic conditions; however, there is lack of studies of the grout propagation in the pouring aggregate mass, which formed in the earlier stage. This paper presents an experimental investigation of grout propagation in poured aggregates with flowing water, which focused on the second stage, i.e., the grouting stage, after the first stage of aggregates pouring in the salvage of an inundated underground tunnel.ResultsIn this work, a visualized tunnel replica with flowing water was adopted to investigate the main effects of sealing efficiency, water pressure variation, propagation mechanism during grouting in the poured aggregates with different grain sizes and flowing water conditions. A series of experiments with orthogonal array design were carried out, and the propagation of cement/sodium silicate and the change characteristics of fluid pressure in the tunnel were obtained. The results show that the main effects on the sealing efficiency of grouting in poured aggregates with flowing water in a descending order is cement/sodium silicate ratio, relative density of aggregates, particle size distribution of aggregates, and final water pressure difference of both ends of aggregates segment. The cementation form of grouted aggregates has four types; T shape, H shape, O shape and shell shape. The main mode of grout propagation includes three types; permeation filling mode, compaction- permeation mode, and compaction-fracturing mode, which reflects the influence of grain size, density of aggregates and grouting pressure. The variation of water pressure can be divided into four categories; overall ascending type, step ascending type, concave type, and convex type. The curve type mainly depends on water pressure, water flowrate, relative density and grain size of aggregates, gel time, propagation mechanism of grout.ConclusionThe flow rate after grouting has decreased by approximately 60% to 86% compared to that before grouting, bulk hydraulic conductivity decreased by more than 80%, reflecting a great improvement of the sealing efficiency in the grouting stage after the pouring stage. The research on grout propagation in different graded aggregate mass has guiding significance for the design and construction of a rapid disaster treatment after groundwater inrush.

Taguchi L9 (34) Orthogonal Array Design for Photocatalytic Degradation of Methylene Blue Dye by Green ZnO Particles Biosynthesized by Chrysanthemum spp. Flower Extract

The pollution of synthetic dyes in wastewater exerts many negative impacts on the environment and human health. There is an increasing demand for the degradation of dyes, with an emphasis on photocatalysis. Here, we investigated the bio-mediated synthesis of ZnO using Chrysanthemum spp. flower extract and its utilization for the removal of methylene blue dye under sunlight irradiation. The bandgap energy of green ZnO nanoparticles was determined to be 3.0. The Taguchi L9 (34) orthogonal array design was applied to optimize the photocatalytic degradation of methylene blue dye by green ZnO particles. Four parameters, including the initial concentration (10–50 mg/L), ZnO dosage (0.33–1.0 mg), contact time (30–120 min), and pH (4–10) of the solution, were surveyed based on the Taguchi design. We found that the test result (99.0%) at 10 mg/L was almost equivalent to the predicted value (99.5%) of degradation efficiency. The reaction mechanisms shed light on the major role of reactive oxygen species (•O2−, •OH). More importantly, the green ZnO particles could be reused for at least five cycles and demonstrated high stability.

Investigation on the wear rate and COF of AA356 metal matrix composites reinforced with zirconium silicate (ZrSiO4) particles

These days, metal matrix composites (MMCs) are frequently investigated by incorporating the proper reinforcement particles. In order to enhance various properties of the manufactured MMCs, reinforcement particles are embedded into the base metal. In the present investigation, A356 MMCs reinforced with 5 wt% of zirconium silicate (ZrSiO4) particles have been prepared and tested for the friction and wear behaviour. Utilizing the stir-casting technique, the composites were produced; and the test specimens have been prepared with ASTM G99 standards. Three significant process variables have been considered for performing the wear test such as normal load, sliding velocity and sliding distance. The Taguchi’s L9 orthogonal array design has been used to plan the experimental design for the wear test. Main Effect Plots (MEPs) have been drawn for the coefficient of friction (COF) and wear rate values obtained during the test for different combinations of selected input variables, and analyzed. To determine the optimal input variable combinations that lead to lower COF and wear rate, Grey-Fuzzy Reasoning Grade Analysis (GFRGA) has been used. For the taken into account input conditions and the recorded output responses, an artificial neural network (ANN) model has been created. The surfaces of the worn out samples have been tested with the aid of the micrographs taken by a Scanning Electron Microscope (SEM).

Chemical fingerprint analysis and quality assessment of Tibetan medicine Triphala from different origins by high‐performance liquid chromatography

Although the Tibetan medicine Triphala (THL) is widely used in many countries, insufficient progress has been made in quality control. The present study aimed to propose a methodology for quality control of THL based on HPLC fingerprinting combined with an orthogonal array design. Seven identified peaks were used as indicators to examine the effects of temperature, extraction time, and solid-liquid ratio on the dissolution of active ingredients in THL. Fingerprint analysis was performed on 20 batches of THL from four geographical areas (China, Laos, Thailand, and Vietnam). For further chemometric assessment, analysis techniques including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discrimination analysis (OPLS-DA) were used to classify the 20 batches of samples. Fingerprints were established and 19 common peaks were identified. The similarity of 20 batches of THL was more than 0.9 and the batches were divided into two clusters. Four differential components of THL were identified based on OPLS-DA, including chebulinic acid, chebulagic acid, and corilagin. The optimal extraction conditions were an extraction time of 30 min, a temperature of 90°C, and a solid-liquid ratio of 30 mL/g. HPLC fingerprinting combined with an orthogonal array design could be used for comprehensive evaluation and quality assessment of THL, providing a theoretical basis for further development and utilization of THL.

Development of Machine Learning Algorithms for Application in Major Performance Enhancement in the Selective Catalytic Reduction (SCR) System

Machine learning is used in this study to deal with the reduction in the design period and major performance improvement of the selective catalyst reduction system. The selective catalyst reduction system helps in the reduction in NOx emission in the diesel engine. The existing methods for the design and performance improvement of selective catalyst reduction systems tend to be inefficient, due to layout changes that require modification when mounting a vehicle based on previously designed models. There are some factors that can affect the design of the diesel engine selective catalyst reduction system that can be identified by applying an optimized design. The Taguchi orthogonal array design is used with the eight factors and three levels of the main design factors. The distance of the urea injector, the distance of the mixer, the inflow angle of the exhaust gas, the angle of the urea injector, the angle of the mixer, the mounting angle in the direction of rotation of the mixer inside the selective catalyst reduction pipe, the number of mixer blades, the and bending angle of the mixer blade are identified as the eight major factors involved. These factors can also be considered manufacturing factors and can be established through machine learning. Machine learning has the advantage of being more efficient compared to other methods in determining the relationship between the data for each mutual factor. Machine learning can help in reducing processing time, which can further decrease the cost of the design analysis and improve the performance of the selective catalyst reduction system. This study shows that the results are statistically significant as the p values of the mixer blade number and cone length are lower than 0.05.

Effect of dietary protein, vitamin E, and vitamin C levels on the growth and gonad development of hybrid male abalone (Haliotis fulgens ♂ × H. discus hannai ♀) by the orthogonal array design

Effect of dietary protein, vitamin E, and vitamin C levels on the growth and gonad development of hybrid male abalone (Haliotis fulgens ♂ × H. discus hannai ♀) by the orthogonal array design

IMPROVEMENT OF SURFACE QUALITY OF Ti-6Al-4V ALLOY BY POWDER MIXED ELECTRICAL DISCHARGE MACHINING USING COPPER POWDER

Electrical Discharge Machining (EDM) is one of the most popular non-conventional machining processes that are being used in many high precision manufacturing industries. To increase the EDM performance, a hybrid technique, namely, powder mixed electrical discharge machining (EDM) (PMEDM) is generally used for getting more precise requirements. In this study, an experimental investigation is carried out in order to explore the machining performance of the PMEDM process on Ti-6Al-4V alloy using copper (Cu) powder in the EDM oil dielectric. Taguchi’s L18 orthogonal array design has been utilized for design of experiments and the analysis of variance (ANOVA) has been performed with the help of Minitab-19 software. The optimal parametric setting of Cu powder mixed EDM has been found utilizing the Taguchi - Grey Relational Analysis (GRA) integrated approach and also validation of optimal parametric setting is done through experimentation. It is a novel approach for machining Ti-6Al-4V alloy by this PMEDM technique in which the surface quality has been improved significantly with the addition of suitable amount of Cu powder into the dielectric medium.

Electrocoagulation treatment of compost leachate using aluminium alloy, carbon steel and zinc anode

Analysis of surface changes and corrosion occurrence at the electrode surface, electro-generated sludge analysis, and electrocoagulation (EC) treatment efficiency using aluminium alloy, low carbon steel, and zinc sacrificial anode as electrodes for the treatment of compost leachate with the medium organic load were compared for the first time. Different operating conditions (initial pH values in the range of 4–8, stirring rates in the range 70–270 rpm, and contact times in the range of 10–30 min) were used to study the EC process. Light microscopy analysis show the significant corrosion of anodes, while minor corrosion damage was also observed on the cathodes. Pitting was found on carbon steel and aluminium electrodes, and general corrosion on the zinc electrodes, which increase with the duration of EC (10 to 30 min). Weight loss analysis of electrodes shows a decrease in anode mass in all experiments and aluminium cathode mass, while steel cathode mass increases. Zinc cathode mass increases in initially acid and decreases in an alkaline environment. The highest anode consumption was obtained in the experiment with the Zn electrode (in the range of 0.3300–0.6469 g). SEM/EDS analysis of the electro-generated sludge confirmed the presence of aluminium, zinc, and iron, with oxygen as the main elements, while carbon indicated collected organic matter from the compost leachate. PXRD analysis of sludge shows a mixture of amorphous phase with the a semicrystalline phase of AlO(OH) and the crystalline phase of AlPO4 obtained with Al electrodes, an amorphous structure of the sludge obtained with Fe electrodes, and structurally well-ordered phases of Zn7Cu(OH)13((SiO(OH)3)0.7(O4H7)0.3(SO4)) and (Zn0.9Cu0.1)O obtained with Zn electrodes. In addition, the treatment efficiency was analysed and Taguchi's L9 orthogonal array design was performed.

Soy Protein/Polyvinyl-Alcohol (PVA)-Based Packaging Films Reinforced by Nano-TiO2

This work was investigated to prepare a reinforcing composite packaging film composited of soy protein/polyvinyl alcohol (PVA) and nano-TiO2. First, different film compositions were designed by the particle size of nano-TiO2, concentration of nano-TiO2, concentration of polyvinylpyrrolidone (PVP, a dispersing agent for nano-TiO2), and pH of film casting solution. Then, the film composition that yielded the optimal physical properties was identified using orthogonal array design single-factor experiments, considering its physical properties, including tensile strength, elongation, water absorption, water vapor transmission, oxygen permeation, thermal property, and film morphology. The results displayed that the optimal film composition was (1) soy protein/PVA film with 2.5 wt% nano-TiO2, (2) 30 nm nano-TiO2 particle size, (3) 1.5 wt% PVP, and (4) pH 6.0 of film-forming solution. It yielded tensile strength of 6.77 MPa, elongation at break rate of 58.91%, and water absorption of 44.89%. Last, the films were characterized by scanning electron microscope (SEM) and differential scanning calorimetry (DSC). SEM analysis showed that compared with the film without TiO2, the film containing TiO2 has a smoother surface, and DSC determined that adding nano-TiO2 can improve the thermostability of soy protein/PVA film. Therefore, the film prepared in this paper is expected to provide a new theoretical basis for use in the packaging industry.

Microwave Supported Extraction and Optimization of Flavonoid Mangiferin from Mangifera indica L. Stem Bark using Orthogonal Array Design

A modest and swift microwave-backed extraction process has been established for the abstraction of a flavonoid mangiferin from the Shoot bark of Mangifera indica L. The content in the extracts was quantified by planar chromatography. An orthogonal array strategy was employed to conclude the effects of variables that affect the efficiency of MAE, namely temperature, irradiation period, the clout of irradiation, and particle size of drug powder. Under optimal conditions, MAE showed expressively higher recovery of mangiferin and markdown in the extraction period as well as solvent intake in comparison to the conventional method.

Unravelling the effect of CO2 laser machining parameters on the surface and shape memory characteristics of CuAlFeMn quaternary shape memory alloy

Shape Memory Alloys (often called SMAs) belong to a branch of alloys that “remember” their original shape. When the metals are twisted or disturbed from their initial shape, they are capable of coming back to their original shape on application of external stimuli such as magnetic field, heat or stress. Despite its widespread commercialization, Ni-Ti is considered a costly alternative. As a result, cost-effective and easy-to-process alloys such as Cu- and Fe-based alloys are currently being investigated. Processing of Fe-based alloys is difficult as their properties are texture dependant. Cu-based shape memory alloys are thus considered viable alternatives. So the unconventional machining operations like electrical discharge machining (EDM) and laser machining can also be used to manufacture Cu-based SMA components. But thermal machining operations like IBM (ion beam machining), EBM (electron beam machining), LBM (laser beam machining), PAM (plasma arc machining) and EDM (electrical discharge machining) removes material from the surface of the work piece through melting/vaporization. However, thermal damage such as theheat affectedzone is brought on by the intense heat flow in laser machining. Hence only a few works have been reported to differentiate and characterize the varied properties of the SMA machined through laser machining. This research work aims at optimizing the laser beam machining parameters and study its influence on surface characteristics and shape memory properties of Cu-based SMA. Based on the experiments carried out using L9 orthogonal array design matrix, optimal parameters were found out with response tables and graphs which is further analysed using grey relational analysis. Surface topography was analysed by scanning electron microscope (SEM). Differential scanning calorimetry (DSC) was used to investigate phase transformation temperatures and some thermodynamic parameters. X-Ray Diffraction (XRD) was also performed to find out the different phases that are present. The results showed the grey relational analysis coupled with Taguchi approach is an effective and convenient technique to optimize the laser machining parameters and achieve better results.

Orthogonal array design based multi-objective CBO and SOS algorithms for band reduction in hyperspectral image analysis

Orthogonal array design based multi-objective CBO and SOS algorithms for band reduction in hyperspectral image analysis

Laser machining sapphire via Si-sapphire interface absorption and process optimization using an integrated approach of the Taguchi method with grey relational analysis

Laser machining of sapphire faces challenges due to the low laser beam energy absorption. A silicon (Si) plate contacting the rear surface of the sapphire substrate was used as an absorptive material to improve the laser absorption and affect material removal from the rear surface. A near-infrared laser with a wavelength of 1030 nm and pulse duration of 2 ns was focused at the interface, causing Si ablation and generation of a plasma plume with immense recoil pressure. The proposed approach for sapphire machining via enhanced laser absorption at the Si-sapphire interface is illustrated, and a probable material removal mechanism is discussed. Effects of processing parameters on machining depth and surface roughness were investigated using Taguchi L27 orthogonal array design and analysis of variance (ANOVA). It is found that repetition rate has the most significant effect on the machining performance characteristics, among other parameters. Furthermore, a multi-objective optimization was performed to optimize the process by integrating the Taguchi method with Grey Relational Analysis (GRA). The maximum machined depth of 59.1 μm and the minimum surface roughness of 0.145 μm were obtained by conducting confirmation tests at the optimal settings. The optimal processing parameters were obtained corresponding to the repetition rate of 1000 kHz, laser fluence of 1.2 J/cm2, hatching distance of 0.01 mm, scanning speed of 1000 mm/s, and single pass. The integrated Taguchi and GRA methodology offers an alternative for optimizing laser machining processes.

MACHINABILITY STUDIES OF WROUGHT TITANIUM ALLOY Ti-6Al-4V BASED ON ORTHOGONAL ARRAY DESIGN

This research focuses on wrought Ti-6Al-4V machining using coated carbide inserts under flood cooling to study the machinability characteristics. Machining parameters are optimized, and mathematical models are developed for correlations. Surface roughness lies between 0.215[Formula: see text][Formula: see text]m and 0.830[Formula: see text][Formula: see text]m and even below 1[Formula: see text][Formula: see text]m during machining. Flank wear lies within 0.033–0.16[Formula: see text]mm which is below the 0.2[Formula: see text]mm criteria of wear. Cutting temperature lies between 31∘C and 158∘C. The reduction of cutting temperature and chip serration under flood cooling and the subsequent transfer of heat from the shear zones help to generate good surface finish and may be due to the evolution of a lower wear rate. Abrasion, chipping, adhesion and built-up-edge are seen as major mechanisms of wear. The optimal conditions are found to be a depth of cut of 0.1[Formula: see text]mm, 0.1[Formula: see text]mm/rev feed rate and 70[Formula: see text]m/min cutting speed. There is an improvement in results at optimal conditions of 38.42% for Ra, 60.86% for VBc and 27% for [Formula: see text], respectively, than initial parametric conditions. Further, grey relational grade has been improved by 0.263. Machinability models developed through quadratic regression are observed to be significant.

The Grey-Taguchi method analysis for processing parameters optimization and experimental assessment of 42CrMo steel treated by ultrasonic surface rolling

Static force, ultrasonic amplitude, feed rate, and rolling spacing parameters of 42CrMo steel treated by the ultrasonic surface rolling process (USRP) were optimized by the Grey-Taguchi method. Nine sets of experiments based on an orthogonal array design and grey relational analysis were used to obtain the optimum combination of mechanical properties for USRP. The influence of processing parameters on mechanical properties was investigated based on the grey relational analysis. The results indicated that the feed rate is the dominant parameter affecting the mechanical properties, followed by rolling space, ultrasonic amplitude, and static force. The effects of plastic strain caused by USRP on the compressive residual stress and microhardness were investigated. The effects of the dislocation and cementite evolution on the mechanical properties were investigated to determine the origin of the best and worst mechanical properties. For the best mechanical property, the level and depth of distribution of compressive residual stress and tensile strain hardening capacity are the highest, which is benefited from the optimum synergistic of the elastic-plastic deformation, dislocation evolution, gradient distribution, and cementite evolution. For the worst mechanical property, a large amount of cementite is distributed within and around martensitic laths, increasing brittleness and the lowest comprehensive mechanical properties. These findings can provide a reference for accurately controlling the processing parameters of USRP and improving their mechanical properties.

A hybrid ANN/PSO optimization of material composition and process parameters for enhancement of mechanical characteristics of 3D-printed sample

PurposeThis paper aims to study the effects of inorganic CaCO3 nanoadditives in the polylactic acid (PLA) matrix and fused filament fabrication (FFF) process parameters on the mechanical characteristics of 3D-printed components.Design/methodology/approachThe PLA filaments containing different levels of CaCO3 nanoparticles have been produced by mix-blending/extrusion process and were used to fabricate tensile and three-point bending test samples in FFF process under various sets of printing speed (PS), layer thickness (LT), filling ratio (FR) and printing pattern (PP) under a Taguchi L27 orthogonal array design. The quantified values of mechanical characteristics of 3D-printed samples in the uniaxial and the three-point bending experiments were modeled and optimized using a hybrid neural network/particle swarm optimization algorithm. The results of this hybrid scheme were used to specify the FFF process parameters and the concentration of nanoadditive in the matrix that result in the maximum mechanical properties of fabricated samples, individually and also in an accumulative response scheme. Diffraction scanning calorimetry (DSC) tests were conducted on a number of samples and the results were used to interpret the variations observed in the response variables of fabricated components against the FFF parameters and concentration of CaCO3 nanoadditives.FindingsThe results of optimization in an accumulative scheme showed that the samples of linear PP, fabricated at high PS, low LT and at 100% FR, while containing 0.64% of CaCO3 nanoadditives in the matrix, would possess the highest mechanical characteristics of 3D-printed PLA components.Originality/valueFFF is a widely accepted additive manufacturing technique in production of different samples, from prototypes to the final products, in various sectors of industry. The incorporation of chopped fibers and nanoparticles has been introduced recently in a few articles to improve the mechanical characteristics of produced components in FFF technique. However, the effectiveness of such practice is strongly dependent on the extrusion parameters and composition of polymer matrix.

Optimization of the Factors Influencing Biodegradation and Thermal Stability of Banana Pseudo Stem Fibers in Nigeria

ABSTRACT Lignocellulosic fibers, one of natural biopolymers, are derived from abundant banana pseudo stem (BPS) agricultural waste in different parts of Nigeria. In this study, the lignocellulosic fibers of three common banana cultivars, agbagba, paranta, and omini, were investigated to determine their chemical composition and mechanical properties. Furthermore, the experimental investigations were correlated with the corresponding Taguchi L9 orthogonal array design under three factors – fiber treatment, diameter, and cultivar type – to find the optimal factors that are pertinent to the desired biodegradation and thermal stability of the fibers. The optimization results indicated that the fiber treatment followed by diameter and the cultivar type was the most influential of the responses, respectively. However, increased cellulosic content led to higher tensile strength and modulus, while higher lignin corresponded to higher elasticity. Meanwhile, the predictions of the biodegradation and thermal stability derived from the Taguchi design via S/N ratio ANOVA and regression modeling correlated adequately with the corresponding experimental observations. Ultimately, the fibers with optimum factors were T3D1C1 and T3D1C3, where T3, D1, C1, and C3 denote that the associated fiber was treated with acetic acid, had a diameter of 60.77 µm, and belong to the cultivar type of agbagba and omini, respectively.