DOE Method Research Articles

Non-Contact Evaluation of Deformation Characteristics on Automotive Steel Sheets

Non-Contact Evaluation of Deformation Characteristics on Automotive Steel Sheets

Optimization and Simulation Parameters of the Resistance Spot Welding for Commercial Aluminium (AA1050) at Low Power Welding Machine

This study aims to find the best conditions of resistance spot welding in commercial Aluminium AA1050 to obtain the maximum tensile shear strength of the joint using a low-power supply welding machine. The chosen parameters for this study were welding current, welding time, and electrode force using a 90 kVA welding machine. The investigation used the DoE method with Taguchi’s technique to reduce the number of experiments where two sheet thicknesses (1 mm and 2 mm) were used in this work. The software program Minitab 18 analyzed the results using the main effects plots and the interaction plots to identify the most significant parameters and their effect on the joint strength. The best conditions for maximum tensile shear force were 14.85 kA welding current and 0.79 kN electrode force for both thicknesses and two cycles and 12 cycles welding time for 1 mm and 2 mm sheet thickness, respectively. The maximum tensile strength obtained was 250 N and 225 N for 1mm and 2mm sheet thickness, respectively. A mathematical equation was developed to predict the shear force with 19.9 % and 17.9 % error for 1 mm and 2 mm thicknesses, respectively. The best conditions were applied in ANSYS 2022R1 multi-physics to obtain the temperature distribution with time history, where the result shows the nugget size according to the molten temperature. The percentage of discrepancy between actual and numerical nugget size was 8 %.

Peningkatan Literasi Membaca Al-Quran Siswa Pemula Melalui Program Tilawah di Pondok Pesantren Perguruan Darulfunun El-Abbasiyah

As a center for learning about the Islamic religion, Pondok Pesantren is the best place to read and study the Quran, which is the main source and reference for Muslim behaviour. However, not all beginners who study religious knowledge at Pondok Pesantren have the ability and fluency to read the Quran. The location of this research is at the Pondok Pesantren Perguruan Darulfunun El-Abbasiyah, Limapuluh Kota Regency. This research is a report on the implementation of increasing Quran reading literacy with a recitation program for early students at the Tsanawiyah or Aliyah formal education level. Research on the implementation of this recitation program uses the DOE method, also using observation, interview and continuous evaluation techniques. Implementation is evaluated repeatedly against the targets achieved by students in each semester. The results of the implementation of this program show that the implementation of the recitation program is considered effective in increasing students' Quran reading literacy. This is because the application of the recitation program is very appropriate as an effort to speed up the fluency of reading the al-Quran for students who experience delays in reading the Al-Quran. This report is useful for the institution in particular and the development of Al-Quran reading skills for the entire community in general.

Design and experimental study of electromechanical braking unit based on DOE method

Design and experimental study of electromechanical braking unit based on DOE method

Design and experimental study of electromechanical braking unit based on DOE method

Design and experimental study of electromechanical braking unit based on DOE method

Proposal and optimization of a novel biomass-based tri-generation system using energy, exergy and exergoeconomic analyses and design of experiments method

A novel trigeneration system of cooling, heating and power based on biomass is designed in current study. This system consists of five parts: biomass gasification subsystem, steam turbine subsystem (Rankin cycle), gas turbine subsystem (Brayton cycle), Kalina subsystem and ejector refrigeration subsystem. Energy, exergy and exergy-economic analysis were performed on the whole system and the effects of different key parameters on energy efficiency and exergy and economic factors are investigated. The designed cycle has been qualitatively optimized using DOE method and the interaction effects of parameters on cycle performance has been investigated. The results show that the highest exergy destruction is related to the combustion chamber with 56.14 %. Also, the lowest exergy destruction is assigned to the separator of the Kalina cycle with a nearly zero value. The highest investment, operating and maintenance costs are related to air compressor, gas turbine and steam generator, respectively. The results of parametric analysis showed that with increasing the mixing ratio of natural gas to syngas the thermal and exergy efficiencies, the rate of total system cost and the unit cost of power generation increase. Also, with increasing gasification temperature, the thermal and exergy efficiencies of this system vary slightly and can be considered constant, but the total cost of system increases. The results of DOE analysis showed that among the main effects of the parameters, the isentropic efficiency of the gas turbine and the temperature of the air entering the combustion chamber have the greatest effect on the system efficiency, and the GMR has the greatest effect on the LCOE of the system, and among the interaction effects of the parameters, the interaction between the temperature of the air entering the combustion chamber has the greatest effect on the system efficiency and LCOE.

Novel Algebraic Matrix Method Used to Generate Linear Equation for Surface Roughness and Material Removal Rate during Wet/Dry Turning Operation on MMCs Al6061-T6/SiC

Stir casting process is well known for reinforcement of ceramic particle in aluminium. Due to improved properties of Al6061-T6/SiC particulate metal matrix composites have attracted by industry as well as received wider attention of material expertise. The purpose of this study is to evaluate the turning process parameters through algebraic matrix which is unique approach. Also studied effects of spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius on modifier element for instance surface roughness Ra and material removal rate MRR in both dry and wet condition. In addition to optimize the turning process parameters are on Al6061-T6/SiC 3% and 6% with a coated tungsten tool. The experimental runs are designed using the taguchi based multiple factorial design DOE and their outcomes are analyzed using Analysis of Variance ANOVA. Mathematical models are established using algebraic matrix to represent the relationship among turning process parameters as independent variables, surface roughness and material removal rate as dependent variables. For every experimental run, a same cutting insert was used to encourage accurate reporting of the surface roughness and material removal rate. The statistical variations revealed that the main effect of spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius are influenced the surface roughness and material removal rate. Moreover, Built-up-edge BUE formation was observed at every combinations of machining parameters such as spindle speed, feed, SiC silicon carbide-3% and 6%, depth of cut and nose radius which affected the surface quality negatively. The proximity of predicted results and experimental results provide proof that the algebraic matrix – DOE method has successfully established the predictive models. It is strongly suggested SiC silicon carbide 3% and 6% are successfully reinforced in Al6061 as well as optimize turning process parameters in wet condition than dry condition. Mathematical models for surface roughness and material removal rate are found to be statistically significant in wet condition.

Aircraft engine nozzle guide vane surface temperature optimization

An optimization method based on the sensitivity of global and local geometric parameters is proposed to improve the cooling efficiency of E3 engine nozzle guide vane. For 29 geometric parameters that affect the vane maximum temperature in the cooling design, the sensitivity ranking of them is firstly obtained by the DOE method. Then the most influential parameters including the diameter or location of the film cooling hole are selected as the optimization variables to decrease the maximum surface temperature of the nozzle guide vane. On this basis, to further reduce the local temperature downstream the pressure side, a new duck-paw type film cooling hole is applied. The duck-paw type film cooling hole was produced with the adjoint method through identifying the sensitivity of the geometric boundary parameters of the film cooling holes. Compared to the cylindrical holes, the duck-paw shaped film cooling hole can greatly improve the cooling efficiency under the same conditions. The duck-paw type film cooling holes are applied to the last two rows of film cooling holes located on the pressure side of nozzle guide vane. Three-dimensional conjugate flow and heat transfer analysis results show that the maximum temperature of the optimized cooling structure vane is reduced by 39K, and the average temperature decreases by nearly 20K.

Surgical cases assignment problem using a multi-objective squirrel search algorithm

Surgical cases assignment problem (SCAP) is among the most investigated interests in operating room planning. The studies related to the SCAP are mainly focused on the single objective optimization. To concern multiple criteria in the management, this paper reformulates a multi-objective SCAP with minimizing total operating cost and maximizing scheduled surgeries number, simultaneously. Although dozens of multi-objective methods have been introduced in recent years, these cannot be applied into the multi-objective SCAP directly considering the characteristics of the problem. To tackle the multi-objective SCAP, a problem-specified multi-objective squirrel search algorithm (MOSSA) is presented. First, a targeted single-list scheme is devised to encode individuals and an efficient decoding scheme integrating a repair strategy is proposed to construct feasible scheduling plan. Second, two simple heuristics are incorporated into the algorithm to imitate the behaviors of squirrels and improve the search ability. Third, an addition archive is employed to store the non-dominated solutions. Moreover, a DOE method is performed to investigate the influence of parameter settings. The performance of the MOSSA is assessed by a representative benchmark dataset with three different evaluating indicators. Extensive experiments and analysis results demonstrate the effectiveness of the proposed algorithm and the superiority over compared approaches in addressing the multi-objective SCAP.

Effect of plasma sprayed flyash based composite coatings on corrosion resistance

With the aim of exploring the possibility of achieving a low-cost thermal spray coating to prevent wear, erosion and corrosion. In the current study, flyash-Al2O3 and flyash-SiC composite coatings were effectively created using the air plasma spray process on substrates of Al6061 alloy. NiCr material is used as the bond coat to improve the bond strength between the coat and the substrate. Taguchi's DoE method is applied to for spray process parameters optimization. In addition, the developed coating is subjected to microstructure analysis and long-term immersion corrosion testing (1 year) in an aqueous environment to assess corrosion properties.The results revealed that the over a certain test period, the developed flyash-SiC coating has greater corrosion resistance than the uncoated and flyash-Al2O3 coated Al6061. It is noticed that the corrosion resistance of the flyash-Al2O3 coating shifts to a negative value with respect to the uncoated substrate. The uncoated sample is extensively pitted and locally corroded, as shown by the SEM image of the corroded surface. Flyash-corroded Al2O3's surface exhibits extensive degradation in the form of peeling, breaking, and cracking of the splats. With flyash-SiC composite coating a very minor corrosion splat deterioration is seen.

Optimization of Welding Process Parameters Using the VIKOR MCDM Method

Optimization of welding process parameters These welding parameters are welding current, welding voltage, gas flow rate, wire feed rate, etc. They affect welding strength, weld pool geometry of steel material during welding. By using the DOE method, the parameters can be optimized and have the best combination of parameters for the target quality. The VIKOR (VIšekriterijumsko Kompromisno Rangiranje) Optimal replacement Select method is used Biomass product, Catalyst, Solvent, Temperature/ K. in Evaluation. Alternatives Wood, Bio-oil, Lignin, Glucose, Saccharine is the Best and Worst Value. Saccharides is got the first rank whereas is the Glucose is having the Lowest rank.

DoE-based formulation, physicochemical properties, and anti-inflammatory investigation of a topical patch preparing by partially neutralized polyacrylate-based adhesive hydrogel

A capsaicin patch was formulated by optimizing the adhesion, the release behavior of the patch, and the pharmacological effect. The aims of study were to 1) apply the design of experiments approach for investigating the simultaneous effect of Viscomate (partially neutralized polyacrylate)-based adhesive, glycerin plasticizing excipient and permeation enhancers on patch adhesion, and the permeation rate of model drug (capsaicin) and then 2) compare the optimal formulation with the reference product (Wellpatch®, Metholatum, U.S.A.) in terms of pharmacological effect. The topical patch was prepared by casting the drug-loaded adhesive hydrogel on the backing layer. The adhesive ability of patches was determined by testing a 90° peel rig on a texture analyzer, and the permeation rate of capsaicin (CAP) through mouse skin was evaluated using Franz diffusion cells. The effects of these critical factors on patch adhesion, CAP flux, and permeation enhancer interaction with the stratum corneum were analyzed using ANOVA and ATR-FTIR/skin hydration tests, respectively. Accordingly, Viscomate (adhesion excipient) and glycerin (plasticizing excipient) had a significant impact on patch adhesion (p < 0.05). Meanwhile, N-methyl pyrrolidone, the permeation enhancer, had a better permeation rate and higher hydration level of the stratum corneum than did Transcutol. The partially neutralized polyacrylate-based optimal formulation had a higher permeation rate of CAP, equal adhesion and comparable anti-inflammatory effects to those of the reference product which was also in agreement with the analysis of anatomical images of tissue structure and inflammatory cells. This study successfully integrated DoE method, release behavior and pharmacological research to develop a stable and highly effective topical product containing capsaicin.

DOE-MARCOS: A new approach to multi-criteria decision making

Choosing the best among the available alternatives seems to be expected in all fields. As each alternative is considered by multiple criteria, the selection of the best alternative must take into account all of those criteria. MCDMs are methods that have been widely used to solve problems of this type. However, if only a certain MCDM is applied, the ranking of alternatives must be done from the beginning as adding/removing one or more alternatives from the option list. This paper presents a probably new approach to deal with this situation. DOE method was used in combination with the MARCOS method to build a relationship between the scores of the options and the criteria. This mix is called DOE-MARCOS. Based on this, the calculation of the scores of the alternatives may be faster and less complicated than only using the MCDM. A simple example was made to evaluate the effectiveness of the proposed method when an alternative was added to the list. Two other examples were also conducted to assess the performance of the proposed method (DOE-MARCOS) in ranking cutting tools. The results of ranking options using the DOE-MARCOS are compared with other methods. Sensitivity analysis in each example under different scenarios was also carried out. Its results show that the proposed method is highly effective for multi-criteria decision making.

Study on empirical model and CFD about pressure rising in Cab during door closure

Aiming at the problem that there is a strong eardrum pressure in the passenger car during the closing process, two analysis and prediction methods, fast formula prediction and CFD simulation based on accurate models, are proposed. The regression model of ear pressure comfort was established by DOE method and multiple linear regression; The simulation software star-CCM+ is applied to simulate and analyze the dynamic characteristics of the flow field in the cockpit during the closing process by using the overlapping grid technology, and the pressure change curve near the ear is obtained. Finally, the CFD numerical simulation model is established by comparing and analyzing the regression prediction analysis results and the real vehicle test data. The results show that the effects of closing speed, effective opening area of pressure relief valve and air tightness of the whole vehicle on the pressure of passengers’ eardrums decrease in turn, and the prediction error of multiple linear regression equation is 17 %; The analysis error of the internal flow field dynamic characteristic model based on refined modeling is 8 %. This study provides a theoretical basis for solving the problem of rapid prediction of eardrum pressure and optimization of engineering structure.

Holistic Design of Experiments Using an Integrated Process Model.

Statistical experimental designs such as factorial, optimal, or definitive screening designs represent the state of the art in biopharmaceutical process characterization. However, such methods alone do not leverage the fact that processes operate as a mutual interplay of multiple steps. Instead, they aim to investigate only one process step at a time. Here, we want to develop a new experimental design method that seeks to gain information about final product quality, placing the right type of run at the right unit operation. This is done by minimizing the simulated out-of-specification rate of an integrated process model comprised of a chain of regression models that map process parameters to critical quality attributes for each unit operation. Unit operation models are connected by passing their response to the next unit operation model as a load parameter, as is done in real-world manufacturing processes. The proposed holistic DoE (hDoE) method is benchmarked against standard process characterization approaches in a set of in silico simulation studies where data are generated by different ground truth processes to illustrate the validity over a range of scenarios. Results show that the hDoE approach leads to a &gt;50% decrease in experiments, even for simple cases, and, at the same time, achieves the main goal of process development, validation, and manufacturing to consistently deliver product quality.

다목적 함수 최적화를 통한 사출 금형의 카트리지 히터 배치 방법 연구

The multi-objective optimization method is used to define the standard deviation (SD) of temperature and average temperature of a product as objective functions to optimize the arrangement of cartridge heaters in an injection mold. We intend to shorten the mold heating time by maximizing the average temperature and minimizing the deformation of the product by reducing the SD of temperature. The design variables were defined as the depth and distance of the heater. After creating an approximate model using the DOE method, multi-objective optimization was performed using the generated approximate model to calculate the Pareto front. The developed method was applied to a square specimen for verification and then applied to a commercial model. Overall, the average temperature improved by at least 2% and SD of temperature improved by approximately 8% compared to the initial design.

A Design of Experiment Approach for Development of Electron Beam Powder Bed Fusion Process Parameters and Improvement of Ti-6Al-4V As-Built Properties

Additive manufacturing is a novel and breakthrough technology by which parts can be manufactured for various purposes and services. As in any production process, the desired properties of additively manufactured components, particularly in electron beam melting processes, ultimately depend on the manufacturing process parameters. Process parameters should be designed accordingly to manufacture parts with specific and desired characteristics. This study focuses on examining the effect of process parameters, such as beam current and velocity, focus offset, and line offset, at three different values each, on the properties of Ti-6Al-4V alloy. The study on the effect of the process parameters on the as-built material’s performance was performed using the Taguchi approach using an L9 (34) orthogonal array. The properties of printed parts (density, surface roughness, elastic moduli, hardness, tensile characteristics, fractography, and microstructure) were tested. A wide range of properties was obtained and analyzed; namely, porosity varied from 8% to almost fully dense materials with density higher than 99.9% and a range of yield and ultimate tensile strength values and brittle samples with less than 1% elongation to ductile samples with an elongation greater than 16%. The overall performance of printed parts was determined based on an evaluation criterion. Several parameter combinations were found and yielded the fabrication of parts with high density and relatively fine microstructure. The comparison of the best parameter combinations determined in this study and the parameters recommended by the machine manufacturer showed that improved results were obtained, and even when using the optimal parameters, they can be improved even more. This result highlights the ability of the proposed DOE method to further develop existing results and even for development of manufacturing parameters for new materials.

APPLICATION OF BOX-BEHNKEN, ANN, AND ANFIS TECHNIQUES FOR IDENTIFICATION OF THE OPTIMUM PROCESSING PARAMETERS FOR FDM 3D PRINTING PARTS

Fused Deposition Modeling, among the various 3D printing approaches, is becoming more and more popular because of its capacity to produce complicated parts quickly. The tensile strength of parts printed with polylactic acid (PLA) showed a significant variation of many factors such as printing speed, printing temperature, printing angle and infill pattern. This study presented an experimental investigation of collecting data with four input factors namely printing speed, printing temperature, printing angle and infill pattern with the tensile strength response. The research methodology of the RSM Box-Behnken DOE method, ANN (Artificial neural network), and ANFIS (Adaptive neuro-fuzzy inference systems) has been used to determine the optimum process 3D printing parameters. The obtained results based on RSM, ANN and ANFIS methods are used to predict the tensile strength of 3D printed FDM details. The best tensile value is 7,03303 MPa corresponding to print speed of 30,0003 mm/s, printing temperature of 211,594℃, printing angle of 90° with Honeycomb” infill printing pattern. Moreover, the results also highlighted that ANFIS is potential approach for forecasting the tensile strength of 3D printing parts more competitively.

Parametric optimization of in-situ heavy oil upgrading using simultaneous microwave radiation and magnetic nanohybrids via Taguchi approach

This study investigated the effect of Fe3O4, Fe3O4-MWCNT, and Fe3O4-NiO nanohybrids on the in-situ heavy oil upgrading using microwave radiation through the Taguchi DOE method. The nanohybrids were synthesized via a co-precipitation method and were characterized using different analyses. Three numerical parameters, including the concentration of nanohybrids, power and time of microwave radiation, and a categorical factor including the type of the nanohybrids, were considered in a DOE plan. Results showed that electrical permeability, loss tangent, and electrical conductivity of Fe3O4-MWCNT nanohybrids are higher than other nanoparticles. Nanoparticle’s concentration (at 0.5 wt%) had the most significant effect on reducing the viscosity and increasing the API degree of crude oil. All three system responses, including viscosity, API, and oil sample temperature, were raised by increasing the power of microwaves from 400 W to 1200 W. The lowest viscosity of crude oil was obtained at low irradiation times (8 min.). The optimal conditions for achieving the greatest reduction in crude oil viscosity were a combination of using 0.5 wt% of Fe3O4-MWCNT nanohybrid under 8 min of 400 W microwave radiation. Finally, it found that microwave radiation has made the oil sample lighter and reduced the sulfur content in the crude oil. So, the use of Fe3O4-MWCNT nanohybrid has reduced the sulfur content in the primary crude oil sample by 16.6%.

Adaptive Design of Experiments for Automotive Engine Applications Using Concurrent Bayesian Optimization

Abstract Most practical automotive problems require the design of experiments (DoEs) over a number of different operating conditions to deliver optimal calibration parameters. DoE is especially crucial for automotive engine calibration problems due to its increasing complexity and nonlinearity. As the complexity of the system increases, the DoE applications require a significant amount of expensive testing. However, only a limited number of testings are available and desired. The current work addresses this issue by presenting an adaptive DoE method based on Bayesian optimization to find optimal parameter settings with a significantly reduced number of physical testings (or function evaluations). To further improve optimization efficiency, this work presents a new approach: concurrent Bayesian optimization, which searches for optimal DoE under multiple operating conditions simultaneously. The method utilizes a surrogate model and a novel concurrent evolutionary multi-objective optimization method: concurrent non-dominated sorting genetic algorithm-II, to solve adaptive DoE in multiple operating conditions with a limited number of function evaluations. The experimental study is carried out on a gasoline engine calibration problem using a high-fidelity GT-SUITE™ engine model. The experimental results demonstrate the effectiveness of the algorithm by optimizing engine performance with a significantly reduced number of expensive testings to achieve accurate optimal solutions. The method simultaneously performs engine calibration at eight different operating conditions using only 500–600 testings, compared to the traditional approach, where each operating condition requires 300–500 testings independently to achieve optimal results.