Full Factorial Design Approach Research Articles

Experimental Heat Transfer Analysis of a New Turbulator in a Concentric Heat Exchanger Tube: A Full Factorial Design Approach

Abstract People have been looking for alternative energy sources because current sources may be depleted. Furthermore, it is critical to utilize available energy sources as effectively as possible. Turbulators are among the topics to consider when it comes to energy efficiency. In practice, turbulators are often used in exchangers to enhance heat transfer. Putting newly constructed turbulators in determined locations of the constant surface temperature heat exchanger, velocity, temperatures, pressure, and flow measurements have been performed in the inlet and outlet. In the case of using different numbers of turbulators, their placement in different locations, their arrangement at different distances, and their use at different Reynolds, the changes in pressure drop, Nusselt number, friction factor, efficiency, exergy loss rate, and NTU were determined with the full-factor experimental design. When the test data were evaluated, it was seen that as the number of turbulators increased, the thermal efficiency, friction factor, and pressure loss also increased. Using turbulators in different numbers, at different positions, at different distances, and with different Reynolds numbers, the effect ratio on the pressure loss, Nusselt number, and friction factor parameters was detected. In the analyses made, the most efficient parameters on heat transfer were determined, respectively, as Reynolds number (64.55%), the position of turbulators (19.73%), the distance between turbulators (6.09%), and the number of turbulators (5.94%).

Optimizing Physical and Mechanical Properties of Recycled Filler and Fiber Sand Concrete: A Full Factorial Design Approach

Optimizing Physical and Mechanical Properties of Recycled Filler and Fiber Sand Concrete: A Full Factorial Design Approach

Experimental Analyses and Predictive Modelling of Ultrasonic Welding Parameters for Enhancing Smart Textile Fabrication.

This study aims to illustrate the design, fabrication, and optimisation of an ultrasonic welding (UW) machine to join copper wires with non-woven PVC textiles as smart textiles. The study explicitly evaluates UW parameters' impact on heat generation, joint strength, and electrical properties, with a comprehensive understanding of the process dynamics and developing a predictive model applicable to smart textiles. The methodological approach involved designing and manufacturing an ultrasonic piezoelectric transducer using ABAQUS finite element analyses (FEA) software and constructing a UW machine for the current purpose. The full factorial design (FFD) approach was employed in experiments to systematically assess the influence of welding time, welding pressure, and copper wire diameter on the produced joints. Experimental data were meticulously collected, and a backpropagation neural network (BPNN) model was constructed based on the analysis of these results. The results of the experimental investigation provided valuable insights into the UW process, elucidating the intricate relationship between welding parameters and heat generation, joint strength, and post-welding electrical properties of the copper wires. This dataset served as the basis for developing a neural network model, showcasing a high level of accuracy in predicting welding outcomes compared to the FFD model. The neural network model provides a valuable tool for controlling and optimising the UW process in the realm of smart textile production.

OPTIMAL SETTINGS OF A MELON SEED SHELLER USING STATISTICAL DESIGN OF EXPERIMENTS

A community melon seed shelling machine, used by farmers and households to reduce the constraints associated with the manual processing, was found to produce larger quantities of unshelled seeds. In particular, the optimum seed moisture content and motor speed were unknown. The objective of this study was to determine the appropriate motor speed and moisture content of melon seeds to improve the effectiveness of seed dehulling. A full factorial design approach was used to develop a regression model and investigate the effect of moisture content and machine speed on dehulling efficiency. The results of the experiments showed that both motor speed and seed moisture content had a significant effect on seed shelling efficiency. The motor speed had the greatest effect (0.21567), followed by the moisture content (0.19732). The modelled optimization conditions were as follows: seed moisture content at 26%, motor speed at 2100 rpm. The regression model showed a coefficient of determination value of 0.999, indicating that 99.90% of the variation in response could be explained by the model; only 0.1% of the variation in response could not be explained by the model and was random. Three experimental validation runs were carried out under optimal conditions, and the highest average yield was 86.2%, corresponding to a significant improvement of 26% on the initial yield of 60 %. Other experimental design methods should be investigated to improve the results for appropriate parameter settings of the production process.

Preparation of Metformin Biodegradable Polymeric Microparticles by O/O Emulsion Solvent Evaporation: A 32 Full Factorial Design Approach

Background: Sustained release of synthetic polymeric microparticles has gained more attention as drug delivery carriers because of their properties such as good stability, low toxicity, dosing frequency, and simple and mild preparation method. The present work was envisaged to reduce the dosing frequency by preparing drug loaded biodegradable microspheres by the O/O emulsion solvent evaporation technique. Objective: The objective behind microspheres’ preparation is to sustain the metformin release by using ethyl cellulose as a synthetic polymer. The model drug metformin having a low biological half-life (1.5-3 hours) is selected. Methods: As the metformin is highly water soluble in nature, the oil-in-oil solvent evaporation techniques are used and span 80 is utilized as surfactant. The effect of stirring rate and surfactant concentration on the characteristics of encapsulation efficiency and drug release from the microsphere are investigated. Results: The results show that the drug-polymer (1:1) ratio gives better sustained release results. The obtained microparticles are characterized by X-RD analysis and Fe-SEM, and release behavior is checked for release patterns. A 32 full factorial design is employed for the responses. The free-flowing spherical microspheres show high drug entrapment efficiency. Conclusion: The data obtained suggest that microspheres can be successfully designed with sustained release for diabetic treatment.

Method operable design region for robust RP-HPLC analysis of pioglitazone hydrochloride and teneligliptin hydrobromide hydrate: incorporating hybrid principles of white analytical chemistry and design of experiments

BackgroundA combination of pioglitazone hydrochloride with teneligliptin hydrobromide hydrate is used to treat type-2 diabetes. Several chromatographic techniques have been described in the literature for determination of each of these medications separately. But these procedures used organic solvents that could be dangerous for humans and animals, not to mention harmful to the environment. It is vital to substitute or reduce the use of these neurotoxic and teratogenic solvents in the chromatographic analysis of these anti-diabetic medications to ensure the safety of life and safeguard the environment. The chromatographic technique used for sample analysis should have characteristics like robustness, eco-friendliness, cost-effectiveness, and user-friendliness following the recently developed idea of white analytical chemistry. Teneligliptin and pioglitazone have not yet been simultaneously estimated using a chromatographic method that has been documented in the literature.MethodsA white analytical chemistry-assisted RP-HPLC method has been developed to fill this gap, using economical and eco-friendly solvents. The design of the experiment approach was used during the development of the RP-HPLC method to reduce organic waste and guarantee that the procedure complied with all applicable regulations. Response surface models were built using the full factorial design approach, and the analytical design space was investigated. This method allowed for the identification of an optimal chromatographic condition within the method's operational design region, allowing reliable RP-HPLC analysis of pioglitazone and teneligliptin.ResultsThe developed RP-HPLC technique underwent validation and was used effectively to assess these drugs in their fixed-dose combinations. Assessments were made of the suggested and published RP-HPLC techniques' validation status, process greenness, cost, and analysis time. For a thorough examination, this review included white analytical chemistry-based RGB models and different green analytical chemistry-based tools.ConclusionIn allowing the simultaneous estimate of teneligliptin and pioglitazone, the devised approach demonstrated robustness, eco-friendliness, and cost-effectiveness.

Selection methodology for additive manufacturing processes considering design, material, and manufacturability

PurposeOne of the critical reasons for the nonacceptance of additive manufacturing (AM) processes is the lack of understanding and structured knowledge of design for additive manufacturing (DfAM). This paper aims to assist designers to select the appropriate AM technology for product development or redesign. Using the suggestion provided by the design assist tool, the user’s design alterations depend on their ability to interpret the suggestion into the design without affecting the design’s primary objective.Design/methodology/approachThis research reports the development of a tool that evaluates the efficacy values for all seven major standard AM processes by considering design parameters, benchmark standards within the processes and their material efficacies. In this research, the tool provides analytical and visual approaches to suggestion and assistance. Seventeen design parameters and seven benchmarking standards are used to evaluate the proposed product and design quality value. The full factorial design approach has been used to evaluate the DfAM aspects, design quality and design complexity.FindingsThe outcome is evaluated by the product and design quality value, material suit and material-product-design (MPD) value proposed in this work for a comparative assessment of the AM processes for a design. The higher the MPD value, the better the process. The visual aspect of the evaluation uses spider diagrams, which are evaluated analytically to confirm the results’ appropriateness with the proposed methodology.Originality/valueThe data used in the database is assumed to make the study comprehensive. The output aims to help opt for the best process out of the seven AM techniques for better and optimized manufacturing. This, as per the authors’ knowledge, is not available yet.

Preparation of low-cost activated carbon from Doum fiber (Chamaerops humilis) for the removal of methylene blue: Optimization process by DOE/FFD design, characterization, and mechanism

Within the context of a circular economy, this work aims to valorize local lignocellulosic biomass of Doum fiber (Chamaerops humilis), as a highly promising adsorbent material for the removal efficiency of methylene blue (MB) dye via the adsorption process. Thus, this study investigates the potential of both raw (RDF) and activated carbon from Doum fiber (ACDF) as adsorbents. The first task was to enhance the adsorption efficiency of MB onto activated carbon by systematically optimizing its synthesis conditions. To achieve this, a full factorial design (FFD) approach of four factors (activation time, activation temperature, contact time, and concentration of H3PO4) at two levels was employed, using H3PO4 as the activating agent. A series of batch experiments were performed to characterize the adsorption properties of MB onto RDF and ACDF by describing the adsorption conditions, determining the kinetic and isotherm models, and evaluating the thermodynamic parameters. The results obtained revealed that ACDF had significantly higher surface affinity for MB than RDF, with an adsorption capacity of 83.82 mg. g−1. The adsorption process was found to be spontaneous and endothermic for ACDF, while for RDF, it was exothermic. The adsorption data for both ACDF and RDF exhibited a good fit to the Langmuir isotherm model, indicating monolayer adsorption. Furthermore, the kinetic data demonstrated excellent agreement with the pseudo-second-order model, suggesting a three-step rate-controlling mechanism. According to the results of density functional theory (DFT) calculations, the adsorption mechanism of MB mainly involves electrostatic interactions, hydrogen bonds, and n-π, π-π interactions with the two adsorbents.

Two-Level Full Factorial Design Approach for the Analysis of Multi-Lane Highway Section under Saturated and Unsaturated Traffic Flow Conditions

Oversaturation of highways occurs due to their inadequate assessment and design. In this paper, we propose both a mathematical queuing model and a Discrete-Event Simulation (DES) framework based on Newell’s triangular flow-density relationship for the performance analysis of a multi-lane highway section. The proposed framework is a finite capacity queuing system, which captures an increase in the flow with the vehicle density up to the capacity of the section in an unsaturated condition and a decrease in the flow in the case of a saturated condition, depicting the actual traffic conditions on the highway section. First, the Birth–Death Process is used to build the mathematical queuing model (BDP), and the average number of vehicles (average queue length) and blocking probability on the highway section are estimated. Then, the accuracy of the mathematical queuing model is verified by the proposed DES framework. The “significance and effects” of different design factors are evaluated using the two-level full factorial design technique. The analysis of the experimental results reveals that the length of the highway section and the number of lanes are the most significant factors affecting the average queue length and blocking probability, while the jam density only has a significant effect on the average queue length and does not affect the blocking probability. In case of a two-way interaction, the combined effect of the “length-lanes” significantly affects the average queue length. In the end, a multiple-factor linear regression model is also developed for the prediction of the average number of vehicles on the highway section based on the design factors.

Factorial design analytics on effects of material parameter uncertainties in multiphysics modeling of additive manufacturing

A bottleneck in Laser Powder Bed Fusion (L-PBF) metal additive manufacturing (AM) is the quality inconsistency of its products. To address this issue without costly experimentation, computational multi-physics modeling has been used, but the effectiveness is limited by parameter uncertainties and their interactions. We propose a full factorial design and variable selection approach for the analytics of main and interaction effects arising from material parameter uncertainties in multi-physics models. Data is collected from high-fidelity thermal-fluid simulations based on a 2-level full factorial design for 5 selected material parameters. Crucial physical phenomena of the L-PBF process are analyzed to extract physics-based domain knowledge, which are used to establish a validation checkpoint for our study. Initial data visualization with half-normal probability plots, interaction plots and standard deviation plots, is used to assess if the checkpoint is being met. We then apply the combination of best subset selection and the LASSO method on multiple linear regression models for comprehensive variable selection. Analytics yield statistically and phyiscally validated findings with practical implications, emphasizing the importance of parameter interactions under uncertainty, and their relation to the underlying physics of L-PBF.

Active Biohybrid Nanocomposite Films Made from Chitosan, ZnO Nanoparticles, and Stearic Acid: Optimization Study to Develop Antibacterial Films for Food Packaging Application.

Chitosan is a biopolymer with great potential as food packaging due to its ability to create a film without additives and its better mechanical and antibacterial qualities compared to other biopolymers. However, chitosan film still has limitations due to its high moisture sensitivity and limited flexibility. Incorporating ZnO nanoparticles (ZnO-NPs) and stearic acid (SA) into chitosan films was expected to improve tensile strength, water vapor barrier, and antibacterial capabilities. This study aims to find the optimal formula for biohybrid nanocomposite films composed of chitosan, ZnO-NPs, and SA. The full factorial design approach-4 × 2 with 3 replicates, i.e., two independent variables, namely %ZnO-NPs at 4 levels (0%, 0.5%, 1%, and 3%, w/w) and %SA at 2 levels (0% and 5%, w/w)-was utilized to optimize chitosan-based biohybrid nanocomposite films, with the primary interests being antibacterial activities, water vapor barrier, and tensile strength. The incorporation of ZnO-NPs into chitosan films could increase antibacterial activity, while SA decreased it. The addition of SA had a good effect only in decreasing water vapor transmission rate (WVTR) values but a detrimental effect on other film properties mentioned above. The incorporation of ZnO-NPs enhanced all functional packaging properties of interest. The suggested solution of the optimization study has been validated. As a result, the formula with the inclusion of 1% ZnO-NPs without SA is optimal for the fabrication of active antibacterial films with excellent multifunctional packaging capabilities.

Surface engineered palmitoyl-mesoporous silica nanoparticles with supported lipid bilayer coatings for high-capacity loading and prolonged release of dexamethasone: A factorial design approach

The use of dexamethasone (DEX) as a mainstay drug for controlling inflammation is hampered by its unfavorable pharmacokinetics and systemic side effects. Mesoporous silica nanoparticles (MSNs) have been identified as a viable delivery strategy due to their unique features, such as tunable pore size, shape, and surface area, as well as biocompatibility, and surface function ability, and stability. In the present study, amine-functionalized MSNs with an average diameter of 88 nm, mean specific surface area of 498 m2/g, and mean pore size of 2.4 nm were fabricated and modified first with palmitoyl chloride (MSN-PALM) to improve drug loading. The impact of different degrees of MSN palmitoylation was explored on the DEX loading and particle size distribution. To avoid unfavorable interactions of MSN silanol groups with bio-membranes, as well as to improve colloidal dispersion and to sustain drug release, DEX-loaded MSN and MSN-PALM were combined with lipid bilayers containing PEG-phospholipids and then probe sonicated to obtain MSN-LC or MSN-PALM-LC, respectively. The preparations were characterized using DLS, FE-SEM, TGA, FTIR, XRD, and BET techniques, and then optimized by modifying the degree of palmitoylation, and lipid bilayer composition, and the weight ratio of phospholipids to the carrier using a full factorial design approach. Equilibrium surface adsorption of DEX was evaluated by comparing different isotherms including Langmuir, Freundlich, and Temkin. In-vitro release profiles of DEX from MSN, MSN-PALM, MSN-LC, and MSN-PALM-LC in phosphate buffer (pH = 7.4) were evaluated, and the drug release data were fitted to various kinetic models. Drug loading (%) reached to 35% (w/w) in 1:1 drug/carrier ratio in MSN-PALM13. Initial fast drug release from MSN-NH2 and MSN-PALM13 continued for 12 h, resulting in a drug release of about 61% and 47%, respectively. After lipid coating, initial fast release of DEX decreased to about 26% and 19%, respectively. The hemolysis test indicated that palmitoylation in high ratios and supported lipid coating to a greater extent improved hemocompatibility. Finally, surface engineered MSNs have shown high-capacity DEX loading, long-term release, and hemocompatibility, suggesting their potential application in chronic inflammatory diseases.

Effects of process parameters on preparation of Ti@SiO2 particles during fluidized bed chemical vapor deposition via design of experiments

Fluidized bed chemical vapor deposition (FBCVD) is a promising technology for preparing photocatalysts. However, the photocatalyst performance depends on numerous parameters, and the effects of process parameters on photocatalyst performance are not well understood. In this work, the effects of deposition time, fluidization number, reactant molar ratio and deposition temperature on photocatalysts prepared by FBCVD are investigated via a full factor factorial design approach, which is a kind of Design of Experiments. The results show that the deposition time, reactant molar ratio and deposition temperature are the main factors affecting the photocatalytic performance, while the fluidization number and the interactions between different parameters are insignificant factors. The characterization of the elemental content, elemental distribution and crystalline structure of Ti-deposited SiO2, Ti@SiO2, particles reveals that the formation of Ti-O-Si bonds and Ti-based nanoparticles on the Ti@SiO2 surface enhances the photocatalytic performance of the particles. Finally, the formation mechanisms of Ti@SiO2 particles are summarized which can be distinguished into two stages. At around 120 °C, intermediates such as Ti(OH)4 are generated and reactions consist of homogeneous and heterogeneous reactions. At around 400–600 ℃, the Ti@SiO2 particles are formed, which is dominated by heterogeneous reactions. The results of this study can improve understanding and control of photocatalyst preparation.

Functionalization of Bacterial Cellulose With Bacterial Pigments: Optimization Using a Full Factorial Design Approach

Pigments from natural sources, such as bacterial pigments, have gained increased attention in recent years due to their biodegradability, non-toxicity, and noncarcinogenicity. The intention to replace synthetic and oil-derived compounds is not restricted to synthetic dyes; other applications include the replacement of oilderived polymers for more environmentally friendly options, such as biopolymers. In this work, the functionalization of a bacterial cellulose (BC) biopolymer with bacterial pigments was explored using a full factorial design methodology to evaluate the best functionalization conditions to produce colored BC. From the factors and interactions evaluated, it was possible to conclude that the variable duration of the functionalization procedure could be reduced to a low level without significantly affecting the functionalization of the BC samples with bacterial pigments. Moreover, BC is a product with high industrial applicability, versatility, and sustainability. Hence, the multifunctional colored BC can be applied in the packaging, paper, and textile industries, among others.
 Keywords: bacterial pigments, bacterial cellulose, full-factorial design, optimization

LIPASE PRODUCTION FROM SOLID STATE FERMENTATION OF COPRA WASTE ASSOCIATED FUNGUS Aspergillus niger

Lipases are enzyme with versatile industrial applications can be produced by the solid-state fermentation (SSF) method and is an economical alternative for enzyme production assisted by fungus. In Malaysia, 5 million of copra waste were generated annually. Large amount of copra waste produced will cause an increasing amount of the waste dumped to the landfill. Copra waste is one of the potential substrates to produce lipase enzyme through SSF. Thus, the aim of this study is to optimize the lipase production by SSF associated by Aspergillus niger using the 23 full factorial design approach. In this study the factors affecting parameters that involved in the production of lipase enzyme such as temperature (25˚ and 35˚), substrates concentration (40% and 60%) and inoculum size of Aspergillus niger (1 and 9 petri dish) were determined. The maximum production of lipase was obtained after 120-hour incubation in SSF. The optimum condition for inoculum size of Aspergillus niger was 9 plates, 30°C of incubation temperature and 60 % moisture contents. The range of the concentration of lipase enzyme produced varied from 105 U/ml to 170 U/ml. When applied to the wastewater treatment, the reducing percentage of fat, oil and grease (FOG) in food processing wastewater is reduced from 219.4925mg/l to 169.467mg/l accounted to the amount of 34 % FOG removal. Lipase produced using copra waste as a substrate using SSF has the potential value to be developed in the future for various industry including wastewater treatment industry.

The Full Factorial Design Approach to Determine the Attitude of University Lecturers towards e-Learning and Online Teaching due to the COVID-19 Pandemic

The purpose of this study was to determine faculty members' attitudes toward online learning in Kurdistan region universities. The study examined the biographic and personal characteristics of the lecturer towards e-learning. The data was collected among faculty members at Cihan University-Sulaimaniya, and to analyze the data, a full factorial design with five main factors at two levels and no central points was applied for this specific purpose. The study's findings indicated that there was no significant relationship between gender and lecturer attitude towards e-learning. In comparison to teachers with an MSc degree, those with a PhD have a more negative attitude toward e-learning. Furthermore, full-time faculty members have a greater positive effect on teachers' attitudes than part-time lecturers. Likewise, the results indicate that lecturers who earned their most recent education degrees outside of Iraq have a more favorable attitude. Similarly, lecturers in the sciences are more favorable to e-learning than those in the arts and social sciences. In addition, the findings demonstrated that the interaction factors (Gender) and (Education Degree) have a negative effect on lecturers' attitudes when they are combined. Besides that, the interaction of factors (Country of Last Education Degree) and (Faculty Member Types) improves attitudes toward e-learning. Based on the results, it is suggested that academic staff receive e-learning training to deepen their knowledge and understanding of such a modern teaching system. There is also a need to enhance factors related to positive attitudes towards e-learning among university lecturers. The findings of this study are necessarily significant to both teachers and educational organizations in Kurdistan Region universities.

HPLC-PDA identification and resolution of rufinamide forced degradation impurities: A congregated chemometric expedite optimization coupled with factorials and desirability.

Rufinamide is used presently to treat Lenaux-Gastaut syndrome. A full factorial design and desirability approach was investigated for the optimization of hydrolytic stress via response surface curves (RSCs). The degradation impurities were identified and resolved using reversed-phase high-performance liquid chromatography (RP-HPLC) on the Qualisil® BDS C8 column. Acetonitrile-water (29:71, v/v) was optimized for the mobile phase and used at a flow rate of 1.0ml/min with detection at a wavelength of 230 nm. Rufinamide showed appreciable susceptibility to hydrolysis under acidic and alkaline stress, and substantial degradation in the neutral condition. It degraded much less under oxidative stress. Exposure towards thermal and photolytic stress conditions indicated appreciable stability. The developed method was subjected to validation as per the recommendations of the International Conference on Harmonization. The proposed method showed no influence from the excipients and the degradation products. As well as good precision and accuracy in determination, the method showed a linear response between 2 and 12 μg ml-1 . The method was extended for determination in a human plasma sample, which resulted in excellent recovery without interference from matrix effects. The combined use of desirability and design for the optimization of acidic and alkaline hydrolytic stress led to simple and rapid analysis.

Microwave assisted biodiesel production: Assessment of optimization via RSM techniques

This paper is targeted on the assessment of response surface methodology (RSM) based optimization techniques for biodiesel synthesis from waste cooking oil/used cooking oil via CaO catalyzed microwave irradiated process. The biodiesel yield was optimized using following parameters: MeOH: Oil molar ratio (A), CaO amount (w/w %) (B), reaction interval (C). These parameters have an effect on the biodiesel yield which is analyze by various statistical plots. By employing Full Factorial Design (FFD), Box-Behnken Design (BBD) and Central Composite Design (CCD) method, the determined optimum results for A is 9.6:1, 9.33:1, and 9.63:1, for B(w/w %) is 1.33, 1.37 and 1.34, for C (min) is 9.7, 9.28 and 9.87, respectively. Based on Analysis of variance (ANOVA) analysis and analysis of statistical plots, BBD and CCD approach is best fitted to the model and may select over FFD approach.

Adsorption of Cu(II) ve Zn(II) ions by alginate-based composites: Full factorial design approach

Groundnut biochar (GHB) encapsulated in calcium-alginate (CA) beads (GHB-CA) was synthesized as a novel composite adsorbent for the removal of copper (II) and zinc (II) from an aqueous solution. BET, SEM, EDS, FTIR, TGA were used to characterize the adsorbents. The data obtained were used to establish the adsorption isotherm using the models of two-, three- and four-parameter isotherms. To study the kinetics of adsorption of heavy metals adsorption on CA and GHB-CA, the pseudo-first-order model, the pseudo-second-order model, Esquivel, Avrami and Bangham were used. The adsorption performance showed that they could use low-cost and effective alginate-based composites for heavy metal removal. To obtain maximum adsorption, applied a full factorial design of three factors (metal ion type, adsorbent type and adsorbent dose) at two levels. It statistically optimized the influence of main variables on copper and lead removal using the synthesized novel adsorbent.

Mathematical modeling and optimization by the application of full factorial design and response surface methodology approach for decolourization of dyes by a newly isolated Photobacterium ganghwense

Dyes are chemicals found in industrial water discharge, which may harm aquatic life and humans. In this study, halophilic bacteria was isolated from sea water in Jeddah, KSA, and then identified using 16SrDNA sequencing technique. Mathematical modeling has been achieved to predict the number of runs needed to reach the maximum of dye removal. Then the effect of four independent variables (NaCl concentration, Peptone concentration, temperature and agitation) was studied using full Factorial Design (FFD) for the determination of optimal abiotic and biotic condition, which reaches a maximum percentage of colour removal (% of decolourization) in artificial seawater (ASW). A model was proposed for the statistical analysis of colour removal prediction. Analytical techniques (UV–vis and FTIR) was also used to determining the degradation mechanisms. The active strain was then genetically characterized to identify genes related to chemical and dyes biodegradation.The isolated strain was identified as Photobacterium ganghwense. Our results revealed that P. ganghwense (5.106 CFU/ mL) was able to decolourize four tested dyes (Methyl orange, Congo red, Crystal violet and Malachite green) in modified ASW with different degrees and the maximum of decolourization was attributed to malachite green (79.61%). The biodegradation capability of the selected strain was confirmed by UV–Vis spectrum and FTIR analysis. Experimental data and model predictions were found to be in good agreement. Genomic analysis confirm the presence of several enzymes (reductase, dehydrogenase, oxidase, kinase, hydrolase, and transferase) associated with dyes and xenobiotic degradation, indicating its possible use in biotechnology applications.