Orthogonal Experimental Design Research Articles

Investigation of Machining Parameters for Turning Process

Manufacturing industries mainly concentrates on how to minimize the cost of the products. The process planers have to prepare the process plan of the product based on the availability of the recourses. All the information is available in the plan including inspection and delivery date of the product. Based on the recommendation of the manufacturing and inspection methods, components are produced at affordable cost. Most of the research work concentrated on selection of machining parameters using optimization techniques and also prove that the machining time / cost were minimized for the particular components / operations. In this work, tool nomenclature is to be considered for the investigation for selection of machining parameters. Work presents an experimental investigation of the influence of the three most important machining parameters of depth of cut, feed rate and spindle speed on surface roughness during turning of aluminium alloy. In this study, the design of experiment which is a powerful tool for experimental design is used to optimize the machining parameters for effective machining of the work piece. L9 orthogonal array experimental design method as well as analysis of variance (ANOVA) is used to analyse the influence of machining parameters on MRR & Machining Time. Two different grade of aluminium alloy i.e. AL 6063 & AL 6068 were machined with input parameters of depth of cut and speed. The output parameters are MRR and machining time. Based on the results empirical equations are formed and optimized results are validation .The optimal results are recommended to manufacturing industries.

Multi-index fusion database and intelligent evaluation modelling for geostress classification

Accurate evaluation of geostress levels is crucial for the investigation, design, and construction of underground engineering. However, existing methods for geostress classification are limited by their reliance on singular indexes, leading to discrepancies between the evaluation results and the actual observations in engineering. The discrepancies have resulted in casualties and economic losses. To address the above issues, 204 sets of geostress levels data were collected from numerous documents in the study. Six indexes related to geostress levels have been identified by analyzing the collected data and traditional criteria. Additionally, an orthogonal experimental design was carried out on the range-based indexes to obtain a multi-index fusion database. Furthermore, an intelligent evaluation model for the geostress levels was established in combination with the AutoGluon automatic machine learning framework. Subsequently, software has been developed from this model for ease of use in practical engineering. After on-site data verification, the proposed model demonstrated an accuracy of 95%, outperforming five traditional criteria, with the highest accuracy among them being 70%. The research could provide an effective basis for geostress classification, thereby enhancing the safety of on-site construction personnel.

Numerical Simulation and Deformation Prediction of Deep Pit Based on PSO-BP Neural Network Inversion of Soil Parameters

The finite element numerical simulation results of deep pit deformation are greatly influenced by soil layer parameters, which are crucial in determining the accuracy of deformation prediction results. This study employs the orthogonal experimental design to determine the combinations of various soil layer parameters in deep pits. Displacement values at specific measurement points were calculated using PLAXIS 3D under these varying parameter combinations to generate training samples. The nonlinear mapping ability of the Back Propagation (BP) neural network and Particle Swarm Optimization (PSO) were used for sample global optimization. Combining these with actual onsite measurements, we inversely calculate soil layer parameter values to update the input parameters for PLAXIS 3D. This allows us to conduct dynamic deformation prediction studies throughout the entire excavation process of deep pits. The results indicate that the use of the PSO-BP neural network for inverting soil layer parameters effectively enhances the convergence speed of the BP neural network model and avoids the issue of easily falling into local optimal solutions. The use of PLAXIS 3D to simulate the excavation process of the pit accurately reflects the dynamic changes in the displacement of the retaining structure, and the numerical simulation results show good agreement with the measured values. By updating the model parameters in real-time and calculating the pile displacement under different working conditions, the absolute errors between the measured and simulated values of pile top vertical displacement and pile body maximum horizontal displacement can be effectively reduced. This suggests that inverting soil layer parameters using measured values from working conditions is a feasible method for dynamically predicting the excavation process of the pit. The research results have some reference value for the selection of soil layer parameters in similar areas.

Numerical analysis and process optimization of electron beam melting for superalloys

This study aims to determine the optimal parameters for the electron beam melting process by employing a modified transient three-dimensional thermal model. The validity of the thermal model is confirmed through experimental results. Moreover, the proposed method establishes mathematical relationships between the resulting molten pool temperature and process parameters. A broader range of process parameters for a new Ni-Co-based superalloy was achieved by investigating the effects of scanning velocities (10-100 mm/s), scanning radius (20-60 mm), and melting mass (1500-3100 g) on temperature at various electron beam power levels (10-30 kW). Regression models were established between scanning velocities-temperature, and scanning radius-temperature under different electron beam power levels. These models laid the foundation for real-time automatic control of molten pool temperature. Significantly, orthogonal experimental design and response surface method are employed to conduct a multi-objective optimization based on sixteen experiments and three parameters. The results of multi-objective optimization indicate that with a smelting mass of 1.5 kg, an electron beam power of 11 kW, a scanning radius of 60 mm, and a scanning velocity of 75 mm/s, the energy consumption is 34.95 kW·h, and the theoretical mass loss of Ni element is 0.002 kg. The desirability is 91.2 %.

Ultra-thin FeCoNi-LDH hollow nanoflower as solid-phase microextraction coating for targeted capture of six pesticides by electrostatic adsorption

Pesticides are common pollutants that cause detriment to the ecological environmental safety and health of human due to their toxicity, volatility and bioaccumulation. In this work, an ultra-thin polymetallic layered double hydroxide (FeCoNi-LDH) with hollow nanoflower structure composite was synthesized using ZIF-67 as a self-sacrificial template, which was used as solid-phase microextraction (SPME) coating for the targeted capture pesticides, which could be combined with high-performance liquid chromatography (HPLC) to sensitive inspection pesticides in real water samples. Orthogonal experimental design (OAD) was applied to ensure the best SPME condition. Additionally, the adsorption properties were evaluated by chemical thermodynamics and kinetics. Under the optimized conditions, high adsorption capacity was obtained (117.0 ∼ 21.5 mg g-1). A wide linear range (0.020 ∼ 1000.0 μg·L-1), low detection limit (0.008 ∼ 0.172 μg·L-1) and excellent reproducibility were obtained under the established method. This research provided a new strategy for designing hollow materials with multiple cations for the adsorption of anion or organic pollutants.

Influence of design parameters on sustained drug release properties of 3D-printed theophylline tablets

The application of three-dimensional printing (3DP) in the pharmaceutical industry brings a broad spectrum of benefits to patients by addressing individual needs and improve treatment success. This study investigates the sustained release properties of 3DP tablets containing Theophylline (TPH), which is commonly used to treat respiratory diseases and recently having a comeback due to its potential in the treatment of conditions like Covid-19. Since TPH is a narrow therapeutic window (NTW) drug with serious side effects in the event of overdose, the release properties must be observed particularly closely. We employed a state-of-the-art single screw extrusion 3D printer, which is fed with granules containing the drug. By employing a Taguchi orthogonal array design of experiments (DOE), tablet design parameters and factor related process stability were sought to be evaluated fundamentally. Following this, examinations regarding tailored TPH dosages were undertaken and a relationship between the real printed dose of selected tablet designs and their sustained drug release was established. The release profiles were analyzed using different mathematical model fits and compared in terms of mean dissolution times (MDT). Finally, in-vivo/in-vitro correlation (IVIVC) and physiologically based pharmacokinetic (PBPK) modeling showed that a paradigm patient group could be covered with the dosage forms produced.

Effect of parameter optimization on the flow characteristics of venturi-self-excited oscillation mixer based on response surface model and multi-island genetic algorithm

The present study focuses on the development of a novel venturi-based self-excited oscillation mixer that effectively utilizes the venturi effect to facilitate efficient abrasive intake while simultaneously ensuring effective prevention of backflow through the utilization of the systolic section within the venturi tube. It not only ensures uniform mixing of water and abrasive but also transforms the continuous jet into a pulsed one, thereby significantly enhancing exit velocity. The orthogonal experimental design method and single factor experiment method were employed to investigate the effects of inlet water pressure, water nozzle diameter, abrasive inlet angle, aspect ratio of the self-excited oscillation mixer, and abrasive pipe inlet diameter on the inlet pressure of the abrasive pipe and the velocity of the jet exit in the new mixing device. Approximate response surface models for these parameters were constructed using lsight optimization software, combining the results of orthogonal experimental simulation. By employing a multi-island genetic algorithm, we have globally optimized this innovative mixing device to determine its optimal performance parameters. Subsequently, comparative experiments were conducted to validate the performance of different mixing devices in descaling applications. Through experimental verification, it was found that the venturi-self-excited oscillation mixer exhibits excellent rust removal capabilities in steel plate tests compared to traditional self-excited oscillation mixers. These findings provide valuable guidance for the subsequent design and enhancement of abrasive water jet mixers.

Optimization Design of a Winch Suction Underwater Dredging Robot Using Orthogonal Experimental Design

In marine engineering and water conservancy projects, dredging often occurs due to silt accumulation, which can impede the long-term development of water ecosystems and water storage systems. To enhance dredging efficiency and the performance of dredging machines, a novel type of winch suction underwater dredging robot was designed. Computational fluid dynamics software was utilized to establish a fluid model of the robot’s winch suction dredging device and conduct model simulation experiments. The simulation test results were used to investigate the factors influencing dredging performance and their impact laws. Five key factors—namely, the reamer rotational speed, reamer arrangement angle, water flow rate, inlet pipe diameter, and outlet pipe diameter—were selected for consideration. By setting up various sets of factor levels, the significant influence of different factors on dredging efficiency was examined. Analysis of variance was employed to analyse the results of the orthogonal experimental design, leading to the identification of optimal factor levels and the establishment of an optimal scheme group. The results of the optimal scheme were verified, demonstrating a 13.049% increase in dredging efficiency and a 19.23% decrease in power consumption of the sludge pump compared to the initial experimental setup. The performance of the optimal program surpassed that of all the experimental designs and met the design requirements.

Multi-objective optimization of the hydrogen fuel production of a solar-based cobalt-chlorine (Co–Cl) thermochemical cycle with grey relational analysis

In this paper, multi-objective optimization of the hydrogen production (m˙H2) of a solar-based cobalt-chlorine (Co–Cl) thermochemical cycle with grey relational analysis (GRA) has been performed. Monthly total irradiance averages (A), wind velocity (B), receiver height (C), receiver radius (D) and number of heliostats (E) are considered to achieve the highest the useful energy absorbed by the solar receiver (Q˙abs), efficiency of the receiver (ηrec), the overall efficiency of the system (ηoverall) and hydrogen production (m˙H2). Orthogonal experimental design is planned according to L18 orthogonal array created by Taguchi method. The percent contribution rates (PCR) on the Q˙abs, ηrec, ηoverall and m˙H2 are determined with the help of ANOVA analysis. The optimal parameters are identified as monthly total irradiance average of 143.8 kW h (A3), wind velocity of 5 m/s (B2), receiver height of 8 m (C1), receiver radius of 3 m (D1) and number of heliostats of 850 (E3), respectively. The highest Q˙abs, ηrec, ηoverall and m˙H2 values corresponding to A3B2C1D1E3 are obtained as 50.2 GW; 64.1%; 22.2% and 122.59 (tons/month), respectively. The PCR of the A, B, C, D and E parameters influencing the f-factor are determined to be 12.6 %, 1.92 %, 0.48 %, 15.03 %, and 53.20 %, respectively. Also, empirical equations are developed with regression analysis (RA) to estimate the Q˙abs, ηrec, ηoverall, m˙H2 values. The statistical coefficients (R2-value) for training and testing data's are determined in the range of 0.771167–0.99608 for Q˙abs, ηrec, ηoverall and m˙H2, respectively.

Research on the preparation and quality control process of cattle liquid tallow

Liquid butter is a special process with unique flavor, which has strong commercial value in the deep processing of animal fat. In this paper, the preparation of liquid butter was based on centrifugal supernatant as the main raw material, and the process of preparing liquid butter by ultrasonic-assisted transesterification method was used to optimize the preparation of liquid butter by single factor and orthogonal experimental design according to the sensory, freezing point and iodine value of the product. The experimental results showed that the optimal formula of liquid butter was as follows: liquid-to-material ratio of 1:1, ultrasonic temperature of 50°C, and ultrasonic time of 50min. Using this ratio, the sensory score of liquid butter prepared from centrifugal supernatant was 87 points, the freezing point was 22.9°C, and the iodine value was 67.5g/100g. The liquid butter prepared by this process is clear and translucent, with unique flavor, and has certain nutritional and health care effects, which has certain reference value for future application in the field of deep processing of animal fat.

Differential evolutionary particle swarm optimization with orthogonal learning for wind integrated optimal power flow

This study develops a novel variant of particle swarm optimization (PSO), which improves its balance of exploration and exploitation by modifying neighborhood topology, self-adaptive parameter strategies and deep search, namely differential evolutionary evolution PSO with orthogonal learning (OL), i.e., DEEPSO-OL in short. Evolutionary computing can explore the solution space efficiently because of its self-evolving attribute as iteration continues. The OL enhances its exploitation by focusing on deeper search for promising solutions. It utilizes the concept of orthogonal experimental design (OED) which predicts the best combination of control variables without exhaustive evaluation of all possible combinations. In addition, to avoid premature convergence in a local optimum, a stochastic star topology for particles is proposed. Such topology ensures just enough communication among the best performing particles, while encouraging them to explore other spaces. The efficacy of the algorithm is evaluated through real-world scenarios such as optimal power flow (OPF) and wind integrated OPF, which are hard to solve with classical mathematical methods. The proposed algorithm is run on a modified IEEE 30-bus test system and compared to the state-of-the-art evolutionary computing algorithms for a variety of cost objective functions with high levels of non-linearity and non-convexity. The DEEPSO-OL demonstrates its performance to generate more accurate feasible solutions and construct promising and efficient search method for real-world complex optimization problems.

Synthesis of terpinyl acetate from α-pinene catalyzed by α-hydroxycarboxylic acid-boric acid composite catalyst.

To enhance the yield of the one-step synthesis of terpinyl acetate from α-pinene and acetic acid, this study evaluated α-hydroxycarboxylic acid (HCA)-boric acid composite catalysts based on orthogonal experimental design. The most important factor affecting the terpinyl acetate content in the product was the HCA content. The catalytic performance of the composite catalyst was related to the pKa1 of HCA. The tartaric acid-boric acid composite catalyst showed the highest catalytic activity. The α-pinene conversion reached 91.8%, and the terpinyl acetate selectivity reached 45.6%. When boric acid was replaced with B2O3, the HCA composite catalyst activity was enhanced, which reduced the use of HCA. When the lactic acid and B2O3 content accounted for 10% and 4% of the α-pinene mass content, respectively, the α-pinene conversion reached 93.2%, and the terpinyl acetate selectivity reached up to 47.1%. In addition, the presence of water was unfavorable to HCA-boric acid composite catalyst. However, a water content less than 1% of the α-pinene mass content improved the catalytic activity of HCA-B2O3. When the tartaric acid-B2O3 was used as catalyst, and the water content was 1% of the α-pinene mass content, the α-pinene conversion was 89.6%, and the terpinyl acetate selectivity was 47.5%.

Optimization Design of Mix Proportion for Fly Ash-Silica Fume-Basalt Fiber-Polypropylene Fiber Concrete under Steam Curing Condition.

To enhance the physical and mechanical characteristics of steam-cured concrete, an orthogonal experimental design was utilized to examine the effects of varying contents of fly ash (0 wt%, 10 wt%, 15 wt%, 20 wt%), silica fume (0 wt%, 5 wt%, 10 wt%, 15 wt%), basalt fiber (0 vol%, 0.05 vol%, 0.1 vol%, 0.2 vol%), and polypropylene fiber (0 vol%, 0.05 vol%, 0.1 vol%, 0.2 vol%) on its mechanical properties. Utilizing range and variance analyses, this study identified four preliminary optimized compositions of concrete incorporating fly ash, silica fume, basalt fiber, and polypropylene fiber. On this basis, in order to determine the optimal mix proportion, the mechanical performances, the pore characteristics, and the microstructure of four optimized mix proportions were analyzed. According to the results of macroscopic, fine, and microscopic multi-scale tests, the addition of 15 wt% fly ash, 10 wt% silica ash, 0.2 vol% basalt fiber, and 0.1 vol% polypropylene fiber to the steamed concrete is the best to improve the performance of the steamed concrete. Compared to ordinary concrete, the compressive strength increases by 28%, the tensile strength increases by 40%, and the porosity decreases by 47.2%.

Steam Explosion-Assisted Extraction of Polysaccharides from Pleurotus eryngii and Its Influence on Structural Characteristics and Antioxidant Activity.

Pleurotus eryngii (PE) has been sought after for its various health benefits and high content of phenolic compounds. This study explored the feasibility of steam explosion (SE)-assisted extraction of polysaccharides with high antioxidant capacities from PE. An orthogonal experimental design (OED) was used to optimize the SE-assisted extraction of PE. The influence of the optimized SE-assisted extraction on the physicochemical properties of PE polysaccharides was determined by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), monosaccharide compositional analysis and antioxidant capacity assays. Under optimal SE conditions, SE-assisted extraction increased the polysaccharide yield by 138% compared to extraction without SE-assistance. In addition, SEM demonstrated that SE-assisted extraction markedly altered the spatial structure of Pleurotus eryngii polysaccharides (PEP), and monosaccharide compositional analysis revealed that this pretreatment significantly increased the proportions of some monosaccharides, such as glucose, rhamnose and arabinose, in the isolated PEP. FTIR spectra indicated no change in the major chemical functional groups of PEP. PEP extracted by SE-assisted extraction had significantly increased free radical scavenging and antioxidant capacities. In conclusion, SE-assisted extraction appears to be a novel polysaccharide extraction technology, which markedly increases extraction yields and efficiency and can increase the biological activity of polysaccharide extracts.

Optimal tartaric acid pretreatment of reed for bioethanol production by fed batch semi-synchronous saccharification fermentation

This study investigated the pretreatment of reed by tartaric acid in ethanol and the fed batch semi-synchronous saccharification fermentation of the pretreated reed to produce bioethanol. An orthogonal experimental design was used to optimize the reaction temperature with sugar yield as the target value. The results showed that 97.4 % of glucan was retained while 99.9 % of xylan recovered as xylose when reed was pretreated with 25 % tartaric acid in ethanol at 170 °C for 30 min. The pretreated reed achieved 95.2 % of cellulose-to-glucose conversion through the enzymatic saccharification. The spent tartaric acid can be recycled for reuse at least four times. The pretreated reed achieved a 55.5 % bioethanol yield by a semi-synchronous saccharification fermentation process.

Design and test of an efficient seedling pick-up device with a combination of air jet ejection and mechanical action

Low degree of transplanting automation will affect production efficiency and planting quality in vegetable cultivation. A new seedling pick-up device was designed and constructed to reduce direct grasping damages to seedlings and improve transplanting efficiency. The pick-up device consists of an air jet loosening device, a flexible pick-up manipulator, a parallel feeding device, and a multi-axis motion control system. Its working principle is to use air jet ejection to assist in loosening of seedling roots from the tray cells, grasp their stems for extracting with the pick-up manipulator, and finally transfer them to the delivery device for feeding into the planting device as needed. The mechanical structure and working parameters of each component were designed, and the control system was constructed according to the working requirements of ejecting, extracting, transferring, and discharging operations. A prototype of the new pick-up device was constructed, and its performance evaluation was conducted using an orthogonal experimental design using cucumber, pepper and caluiflower as test objects. The results showed that the test object, the root lump's moisture content and the loosening way (either as a whole or individual loosening of seedlings) had significant effects on the success ratio in picking up seedlings. Overall, the success in picking up seedlings from the cell was found to be influenced by horticultural and mechanical factors. Under the optimal level group, the maximum success ratio for automatic picking up seedlings was up to 94.49% for pepper while that of cucumber and cauliflower recorded 90.75% and 92.62%, respectively. The seedling pick-up performance was satisfactory for efficient transplanting requirements.

Research on explosion hazard and prevention of ultrafine aluminium powder based on orthogonal matrix analysis

This study investigated the coupled effects of multiple factors, namely dust mass concentration, dust particle size, and oxygen volume concentration, on the explosion intensity of ultrafine aluminium powder (UAP); the study determined the weight of each factor by using an orthogonal experimental design. Explosion intensity was evaluated using the maximum explosion pressure (MEP) and MEP rise rate (MEPR) of UAP. Explosion tests were performed using a 20 L standard spherical explosive device. A weight matrix for the explosion intensity was calculated. The results revealed that the MEP and MEPR increased most with the oxygen volume concentration. They also increased with the dust mass concentration to a lesser extent. The dust particle size had the smallest effect; the MEP and MEPR initially increased and then decreased as the particle size increased. The weights for oxygen volume concentration, dust mass concentration, and dust particle size were 69.191%, 18.761%, and 13.038%, respectively. The optimal factor combination for minimizing intensity was a dust mass concentration of 500 g/m3, an oxygen volume concentration of 9 vol%, and a dust particle size of 0.172 µm. On the basis of these findings, the study proposes industrial explosion-proofing countermeasures to increase the safety of production in aluminium-related enterprises.

Effect of Floating Support Parameters on the Load-Sharing Performance of EDPGS Based on Mathematical Statistical Methods

The encased differential planetary gear system (EDPGS) allows power to be distributed among multiple output paths, enhancing efficiency and reducing weight. Uniform load distribution ensures stable system operation and prolongs service life. However, stochastic manufacturing errors leading to uneven load distribution pose challenges in engineering practice. To investigate the impact of floating support parameters on the load-sharing performance within an acceptable tolerance band, a dynamic model of the EDPGS considering time-varying meshing stiffness and random errors is established using the Monte Carlo method. This study employs the orthogonal experimental design method to analyze the effects of floating support stiffness and clearance on the load-sharing characteristics. The findings indicate that a larger sample size leads to a probability distribution of load-sharing coefficients closer to the Gaussian distribution, with minimal influence on the expectation and variance. Furthermore, this study highlights the significant influence of floating structure parameters on load-sharing characteristics in the encased stage systems compared to the differential stage. Decreasing floating support stiffness or increasing floating clearance proves beneficial in enhancing the load-sharing performance of the system.

Study on the dyeing properties of Chinese fir with Cinnamomum camphor pigment by premordant dyeing

ABSTRACT Wood staining can improve the quality of Chinese fir. In this study, Cinnamomum camphora natural plant pigment was used as a substitute for synthetic dyes to stain Chinese fir, and the staining performance was enhanced through pre-mordanting with alum. The dyeing effects of direct dyeing and mordant dyeing were compared, and the factors and levels influencing color difference, wash fastness, and light fastness were investigated through an orthogonal experimental design. The results showed that mordanting time had the greatest influence on color difference and lightfastness, while mordanting temperature had the greatest influence on washfastness. After pre-mordanting, the washfastness of Chinese fir improved to a level of 2–3, while the improvement in lightfastness was not significant. Pre-mordanting increased the dye uptake rate by 6.67%. Scanning electron microscopy revealed that NaOH pretreatment opened the wood pores and increased the flow channels for dye liquor. Infrared analysis indicated that O-H in wood fibers formed complexes with Al3+ in the mordant, resulting in a decrease in the characteristic peak intensity of O-H. X-ray diffraction analysis showed that the attractive effect of Al3+ vacant orbitals on O-H partially influenced the ordered arrangement structure in the crystalline region.

Numerical investigation and parameter optimization on a rib-grooved liquid-cooled plate for lithium battery thermal management system

To increase the effectiveness of liquid-cooled battery thermal management systems (BTMS) in electric vehicles, a unique liquid-cooled plate with a discrete, inclined, and alternating arrangement of ribs and grooves inside the plate was invented during this study. A numerical study was carried on to analyze the thermal performance between this rib-grooved liquid-cooled plate and a conventional straight-channel one. Firstly, a battery module's 1D/3D electrochemical-thermal coupled model was constructed to analyze the thermal performance in the case of actual electrochemical heat production. Then numerical results were obtained by solving this coupled model with different plates. The results indicated that ribs effectively equalize the flows between different channels and multiple longitudinal swirl flows are formed due to grooves, which improves the liquid-cooled system's temperature control performance with a small increase in pressure drop. The maximum battery temperature is 0.74 °C lower, the temperature standard deviation of the contact surface is 0.18 °C lower, and the pressure drop is 55.37 Pa higher in the BTMS with the rib-grooved liquid-cooled plate than it is in the conventional one. After that, an orthogonal design of experiments was used to investigate the effect of four features, including rib-groove tilt angle, column spacing, row spacing, and rib-groove length, on the thermal performance and energy consumption of the battery module. The optimum structure of the rib-grooved liquid-cooled plate is obtained through range analysis: the rib-groove inclination angle is 45°, the row spacing is 13.5 mm, the column spacing is 11.5 mm, and the rib-groove length is 9 mm. This research on the rib-grooved liquid-cooled plate offers a fresh concept that considerably enhances its capacity to regulate the temperature of the liquid-cooled BTMS.