Optimal Level Combination Research Articles

Enhancing real-time cell culture monitoring: Automated Raman model optimization with Taguchi method.

Raman spectroscopy has found widespread usage in monitoring cell culture processes both in research and practical applications. However, commonly, preprocessing methods, spectral regions, and modeling parameters have been chosen based on experience or trial-and-error strategies. These choices can significantly impact the performance of the models. There is an urgent need for a simple, effective, and automated approach to determine a suitable procedure for constructing accurate models. This paper introduces the adoption of a design of experiment (DoE) method to optimize partial least squares models for measuring the concentration of different components in cell culture bioreactors. The experimental implementation utilized the orthogonal test table L25(56). Within this framework, five factors were identified as control variables for the DoE method: the window width of Savitzky-Golay smoothing, the baseline correction method, the order of preprocessing steps, spectral regions, and the number of latent variables. The evaluation method for the model was considered as a factor subject to noise. The optimal combination of levels was determined through the signal-to-noise ratio response table employing Taguchi analysis. The effectiveness of this approach was validated through two cases, involving different cultivation scales, different Raman spectrometers, and different analytical components. The results consistently demonstrated that the proposed approach closely approximated the global optimum, regardless of data set size, predictive components, or the brand of Raman spectrometer. The performance of models recommended by the DoE strategy consistently surpassed those built using raw data, underscoring the reliability of models generated through this approach. When compared to exhaustive all-combination experiments, the DoE approach significantly reduces calculation times, making it highly practical for the implementation of Raman spectroscopy in bioprocess monitoring.

Investigation on passenger car CRDI engine for optimization of its fuel and operating parameters for lower emissions fuelled with diesel, biodiesel and higher alcohol blends

In the present examination it was attempted to analyse the influence of jatropha methyl ester along with butanol and operating parameters of a three-cylinder automotive passenger car common rail direct injection (CRDI) engine on its performance and emission features. Design of experiments methodology was adopted to design the experiments for the present work. NOx, smoke and brake thermal efficiency were the responses and torque, speed, percentage biodiesel in the diesel/biodiesel blend and percentage of higher alcohol blend were the factors for the work. Percentage influence of each factor on the responses and the optimum combination levels of factors was obtained through Taguchi parametric design. From the analysis it was observed that among the torque and speed, the influence of torque is more in the performance and emission features of the tested engine. Also, addition of butanol influences the engine characteristics when compared with that of biodiesel. Among the operating and fuel parameters tested, operating parameters of the engine show their dominant role in lowering the NOx and smoke emission with better BTE with a percentage contribution of 76 when compared to the fuel parameters contribution of 24%

Study of optimization and prediction methods for PEMEC performance considering the effects of multiple operating parameters

The influence of operating parameters on the hydrogen production performance of the proton exchange membrane electrolysis cell (PEMEC) is crucial. In this paper, we first investigate the effect of a single operating parameter on the performance of PEMEC, and find the law of single operation effect. After that, the orthogonal experimental methods are used to investigate the effect of cross-coupling of combined operating parameters on the performance of PEMEC and the optimal combination of levels of operating parameters is obtained. Finally, the LSTM neural network is used to predict the PEMEC performance under the multiple operating parameters. The results showed that the weights of voltage, temperature, water flow rate, and bolt torque on PEMEC performance were 68.72 %, 20.63 %, 6.17 %, and 4.48 %, respectively. The optimal combination of operating parameters for the experiment is a torque of 3.5 N m, temperature of 70 °C, voltage of 2.0 V, and the water flow rate of 40 mL/min. It is also found that the long short term mermory (LSTM) neural network is able to predict the performance of PEMEC well, and that the experimental data-driven approach is an effective method for predicting the experimental performance.

Experimental optimization on mechanical properties of 18Ni-300 maraging steel produced by direct metal laser sintering

Maraging steel material characteristics are greatly affected by build orientation and scanning strategies during manufacturing. This research aims to examine the effect of various build orientations and scan strategies on the ultimate strength and microhardness of 18 Ni-300 grade maraging steel. The maraging steel is made using a technology called direct metal laser sintering. Using the Analysis of Variance approach, the effects of processing factors like build orientation, scan techniques, and type of process on ultimate strength, microhardness, and roughness are optimized. The properties tend to be greater in the horizontal orientation when using the XY scan strategy as a result of thermal history variations,. The mechanical performances of maraging steel components in terms of strength values observed were lower in the vertical position compared to all other orientations. The tests are carried out using an L27 orthogonal array and a Taguchi design of experiment. Build orientation XZ, scan method XY, and Solution-aging-aging(SAAT) has the most significant influence on the final ultimate strength, microhardness, and roughness of all the input factors. A2B2C3 is the optimal combination level of control factors. Additionally, a percentage inaccuracy was identified after conducting confirmation tests on the most prominent experimental data.

Solder die attach lifetime characterization of SOT-227 power MOSFET module in a 3-phase inverter under power cycling

Abstract This study aims to assess the power cycling lifetime of the solder die attach of the silicon power metal-oxide-semiconductor field-effect transistor modules in an SOT-227 package in a 3-phase bridge inverter. This goal is achieved through a loose one-way coupling framework that incorporates a thermal computational fluid dynamics model for temperature estimation and a transient thermal-mechanical finite element model that accounts for the time-dependent viscoplastic behavior of the solder die attach through the Anand viscoplastic constitutive model for thermal-mechanical responses assessment. To facilitate an accurate prediction of the solder die attach lifetime during power cycling, a physical lifetime prediction model is constructed through the strain-based Coffin-Manson Eq. together with the experimental lifetime data and the corresponding calculated equivalent viscoplastic strain increments. Furthermore, parametric study via the coupling framework is conducted to examine the effect of cooling, operating, and structural parameters on the solder die attach lifetime, and also to identify the most crucial design parameters. At last, experimental design using a Taguchi method is conducted to seek the optimal level combination of design parameters for enhanced power cycling lifetime of the solder die attach.

Investigation and Optimization of Fast Cold Start of 18650 Lithium-Ion Cell by Heating Film-Based Heating Method

In this paper, based on the multi-scale multi-domain (MSMD) battery modeling approach, the NTGK model was used to model the 18650 cylindrical lithium-ion single battery on the electrochemical sub-scale. The model was successful, as it was able to fit the experimental voltage and temperature of the battery at different temperatures. Lithium-ion battery discharge capacity and energy output can be improved during cold starting by preheating and insulation, as demonstrated by a comparison of the impacts of heat transfer coefficient and preheating duration at −20 °C ambient temperature. For the traditional heating method, the heating model of heating film (HF) and liquid-cooled plate (LCP) is constructed in this paper, and the heating performance of both is compared by Fluent. Analysis of the energy balance of Li-ion battery at low temperatures has been presented, showing that Li-ion battery requires a suitable start-up temperature to maximize energy output. Taking care of the problem of excessive temperature difference inside the battery due to excessive heating power, we investigated the effects of axial thermal conductivity, heating power, and heating area on the heating uniformity of the battery in this paper. Finally, a multi-stage stepped power (MSP) heating method was proposed to improve the temperature control accuracy of HF. A level orthogonal test L16(43) without interaction was designed to determine the degree of influence of each parameter on the temperature control performance and the optimal level combination, revealing that the optimized maximum temperature and temperature control rate were reduced by 4.09% and 40.53%, respectively, when compared to direct heating.

Comprehensive effect of the three-dimensional spatial distribution pattern of buildings on the urban thermal environment

The three-dimensional spatial distribution pattern of buildings is an important factor causing the spatial differences in the urban thermal environment. The study units were divided based on the urban road network, DEM, and building big data in Jinan. The Landsat 8 remote sensing images were used to invert the land surface temperature (LST), and Kriging interpolation was used to obtain the spatially continuous air temperature (AT). The integrated LST and AT represented the urban thermal environment. By constructing three-dimensional spatial distribution indicators of buildings and using analysis of variance and multiple correspondence analysis methods, the influence of the three-dimensional spatial distribution pattern of buildings on the urban thermal environment was comprehensively investigated. The results showed that all the indicators of the three-dimensional spatial distribution of buildings were factors that have prominent influence on the urban thermal environment. The interaction of mean DEM respectively with building density, volume ratio, mean building height, and mean building volume demonstrated significant effects on both LST and AT, and the analysis of variance results of these indicators with each temperature reached a significance level of ≤0.05. The types and levels of the main strongly correlated indicators varied with increasing temperature levels. The optimal combination of levels corresponding to the lower LST depended on the terrain, while the lower AT was affected by a combination of buildings and terrain. The height indicators contributed more to LST than to AT.

APPLICATION OF TAGUCHI METHOD TO OPTIMIZE ULTRASONIC VIBRATION ASSISTED FUSED DEPOSITION MODELING PROCESS PARAMETERS FOR SURFACE ROUGHNESS

This paper presents the findings on the process parameters for surface roughness optimization of an open-source ultrasonic vibration assisted fused deposition modeling (FDM) printed specimen. Acrylonitrile Butadiene Styrene (ABS) material for the specimens and the printing temperature, layer thickness, and surface layer were determined as the control parameters that influenced the surface roughness. Experimental design with Taguchi level 9 (3*3) Orthogonal Arrays (OA) was designed with nine experimental runs. Three levels of each control factor was identified. In addition, data for multi-responses of build time and surface roughness was obtained by utilizing and conducting the nine-requirement experimental run for Taguchi Method. The specimens were printed using an open-source ultrasonic vibration assisted FDM printer with a 20kHz ultrasonic vibration supplied to the printing platform of the printer. Analysis of variance (ANOVA) was conducted to determine whether p-values are significant with the model or otherwise. The experiments examined the build time and surface roughness, the responses were collected and optimized by using the grey relational grade (GRG). The result shows no correlation between build time and surface roughness in the grey relational grade, and the p-value was higher than 0.05 significant level. However, the surface roughness for optimal level combination setting showed the obvious result, which the settings consist of printing temperature (level 1), layer thickness (level 1), and surface layer (level 1).

Preparation of high-performance thermal insulation composite material from alkali-activated binders, foam, hollow glass microspheres and aerogel

• Physical foaming, hollow glass microspheres and aerogel were used for AAB. • CMC minimized foam and slurry delamination and improved foaming effect. • KH550 treated hollow glass microspheres showed enhanced the interfacial bonding. • PE100-hydrophobic aerogel had extern hydrophilic and internal hydrophobic effect. Herein, a high-performance thermal insulation composite material was prepared by adding physical foaming agent (FA), hollow glass microspheres (HGMs) and aerogel (AG) with alkali-activated binders (AABs) as the matrix. The results of orthogonal experiments revealed that AG has the greatest effect on thermal conductivity, followed by the effect of FA and HGMs. The thermal conductivity value of AABs was reduced from 0.6057 to 0.0870 W/(m·K) at an AG dosage of 4 g (42.48 kg/m 3 ) in the single factor experiments. The effect of compressive strength followed an order of: HGMs < FA < AG. Under the temperature condition of 400–800 °C, the FA exacerbated the linear shrinkage of the sample, HGMs inhibited the linear shrinkage at 400 °C and 600 °C, and exacerbated it at 800 °C, while AG inhibited the linear shrinkage. X-ray diffraction and scanning electron microscopy analyses revealed that the sample maintained stable performance below 800 °C. Orthogonal experiment results concluded that the optimal level combination was 6 g FA, 6 g HGMs and 3 g AG (A6B6C3) and exhibited the minimal thermal conductivity (0.0434 W/(m·K)). The compressive strength of A6B6C3 at 30 °C was 0.38 MPa, which gradually increased with temperature, reaching the maximum of 0.79 MPa at 800 °C. This composite can meet the thermal insulation, mechanical and high temperature resistance properties. In addition, accredited to simple preparation process, short curing period, and low cost, this approach can be deemed of great significance for applications in composite thermal insulation materials in nuclear power plants and other key areas.

Research on the strength of selective laser sintering core

Taking the tensile strength as the inspection index, the single-factor influence experiment was carried out on the addition of phenolic resin and the four factors of laser power, laser scanning rate and sand thickness in the sintering process, and the optimal level combination of each factor was obtained: the addition of phenolic resin. 5%, laser power 38W, laser scanning rate 3400mm/s, sand thickness 0.25mm.

Optimization of the Hydrodynamic Performance of a Double-Vane Otter Board Based on Orthogonal Experiments

An orthogonal experiment was conducted to study the effects of the aspect ratio, camber of the fore wing, and gap ratio of front and rear wing panels on the hydrodynamic performance of double-vane otter boards. The design of the orthogonal experiment comprised three factors (each having three levels), namely the aspect ratio (1.0, 1.5, and 2.0), camber (0.12, 0.14, and 0.16), and gap ratio (0.25, 0.30, and 0.35), the drag coefficient Cx and the lift coefficient Cy of nine otter board models obtained in a wind tunnel experiment, and the lift–drag ratio K obtained by calculation. The lift–drag ratio for a working angle of attack of 30° was selected as the inspection index, and the experimental data were analyzed in an orthogonal design-direct analysis. Analysis of each factor revealed that the optimal level combination of factors was A3B3C3 and that the decreasing order of the effects of the factors was A (aspect ratio) &gt; B (gap ratio) &gt; C (camber). The orthogonal experiment thus obtained an optimal otter board in terms of the aspect ratio (2.0), fore wing camber (0.16), and gap ratio (0.35), with the aspect ratio having the greatest effect on performance. The hydrodynamic performances of the otter board with the optimized structure and another otter board model were compared in numerical simulation, which verified the correctness of the analysis results. The experimental results provide a reference for the optimal design of the double-vane otter board.

Experimental Study on Reinforced Aluminium Metal Matrix Composites with B&lt;sub&gt;4&lt;/sub&gt;C through Different Techniques

Recently, aluminum alloys are extensively used in automobile and aeronautical industries due to its low density and excellent mechanical properties. The aim of this research work is to focus on develop an aluminum matrix composite reinforced with boron carbide particulates under different weight percentages by squeeze casting route. To obtain better results, it is essential to control the process variables involved in the process. The primary work focused to optimize the process variables involved in the fabrication of the composites using full factorial design. The experiments were carried out with various input parameters like squeeze pressure of 50, 100 and 150Mpa, melting temperature of 700, 750 and 800°C and weight fraction of reinforcement of 6, 8 and 10% using L27 orthogonal array. The significant parameters were identified by analysis of variance table and regression analysis was used to model the mathematical relationship for obtaining better mechanical properties. Final results reveal that, mechanical properties of 218VHN hardness and 412MPa tensile strength had been obtained based on the optimum combination levels. Also AA7075-B4C composites produced through this route with enhanced properties could be used as an alternative material for high strength structural applications like connecting rod, control arms, steering knuckle and other parts.

Operating parameters optimization for lower emissions in diesel engine with PCCI-DI mode using Taguchi and grey relational analysis

Searching for ultra-low emission engines particularly for automotive applications is still ongoing. Even though LTC combustion mode results a prominent advantages in terms of reducing both NOx and PM and also lowering the consumption of fuel, it mainly faces with the challenge of excess emissions of HC and CO. This study aimed to optimize the operating control factors for low emissions in PCCI-DI engine under LTC mode. Parameters include injection timing, EGR level, dieseline ratio and engine load. Computation of analyzing the grey relation with hybrid of Taguchi was applied. In designing of experiments and conducting tests Taguchi's L9 matrix was applied. Air-blast of methanol intake port supply and dieseline application instead of diesel was implemented aiming emission reductions. Optimum combinations were found using GRA and ANOVA. Following the optimization work; advanced injection timing of 25o before TDC, 25% EGR, dieseline 90:10 in % and load 75 % (A2B1C3D3) was found optimal combination level for the proposed aim of emission reductions. Key findings of the results following the experiment conducted using this optimal combination includes; reduction of 68.02% NOx and 62.37% in smoke comparing with the base-line conventional diesel combustion mode. Rankings and ANOVA indicated another findings that injection timing being most influential with a contribution of 69.35% followed by load, dieseline ratio and EGR level respectively. This study confirmed dieseline direct injection with methanol port injection is capable of reducing emissions and better NOx with HC and CO trade-offs in PCCI-DI engines.

Optimasi Taguchi Menggunakan Metode Vikor dalam Pemilihan Ban Mobil

The main functions of tire are to withstand the vehicle’s load, continue the steering function and control the vehicle’s direction, transmit the driving force and vehicle’s braking on the road surface and reduce shock vibrations from the road surface. Therefore, optimal tire selection is something that needs to be considered for driving perfection. Taguchi methods is one of experimental design methods that is often used because of considerations of effectiveness and efficiency. However, Taguchi methods only can be used to solve a single response optimization problem. When dealing with multi-response problems, the responses are analyzed separately. This study aims to optimize Taguchi design using VIKOR method in production of car tires. The experimental design and responses used in this study were derived from car tire production data which analyzed using VIKOR methods and selected based on the optimum value to obtain the optimal combination of factors levels. The results of Taguchi's analysis are the first and third responses indicating the 16th experiment and second response indicating the 14th experiment which is the optimal combination. It can be concluded that Taguchi methods is inconsistent to producing optimal combination of levels of factors when dealing with multi-response problems, so additional methods are needed as Taguchi optimization methods in solving multi-response problems, including using VIKOR methods which results in the 2nd experiment being optimal combination.

Optimization of fused deposition modelling process parameters and the effect on residual stresses of built parts

Fused deposition modelling (FDM) is one of the most used additive manufacturing techniques for the fabrication of functional parts from composite filaments. Despite the widespread application spectra, FDM is still limited in its applicability due to inherent problems, one of which is the significant accumulation of residual stresses during part building. Residual stresses are generated due to thermo-cyclic loading in subsequent layers. The effect of residual stresses is significant for the mechanical integrity of the manufactured parts. Since it is impossible to manufacture parts without internal residual stresses, it is prudent to optimize the process parameters that would result in minimal residual stresses. In this study, Digimat additive manufacturing 2020 software with Taguchi design of experiment was used to predict the effect of printing temperature, layer thickness, and print speed on the generated residual stresses. Generic algorithm was used to determine the optimum combination levels for the minimum residual stresses. Results showed a near convergence between simulation and experimental residual stress values with an error of 3.7 %. The mechanical properties of 3D printed carbon fiber composite products were found to have tensile strength; 71.48 MPa, compressive strength; 135.8 MPa, Young’s Modulus; 7.6 GPa, and percentage elongation; 1.86 %. These properties fell within the acceptable range for the actual parts to be replaced. The results of this study will serve as a pragmatic approach to 3D printing of components devoid of trial and error strategies that have currently slowed the adoption of the FDM technique as a rapid prototyping tool for enhanced manufacturing.

Improvement in the Resistance to Wear of Work-Rolls Used in Finishing Stands of the Hot Strip Mills

Work-rolls manufactured through the Indefinite Chill Double Poured (ICDP) method present an exterior work layer manufactured in a martensitic white cast iron alloyed with 4.5 %Ni, 1.7 %Cr, and 0.7 %Nb (wt.%). In its microstructure, there are abundant carbides of the type M3C and MC, which give high resistance to wear, and graphite particles which improve the service behaviour of the rolls against thermal cycling. The core of the rolls is manufactured in grey cast iron of pearlitic matrix and spheroidal graphite. These work-rolls are used in the finishing stands in Hot Strip Mills for rolling slabs proceeding from continuous casting at 1200 °C. Through the application of a Design of Experiments (DoE), an attempt has been made to identify those manufacturing factors which have a significant effect on resistance to wear of these rolls and to find an optimal combination of levels of these factors which allow for improvement in resistance to wear. To increase resistance to wear, it is recommended to situate, simultaneously, the liquidus temperature and the percentage of Si in the respective ranges of 1250–1255 °C and 1.1–1.15 (wt.%). Higher liquidus temperatures favour the presence of the pro-eutectic constituent rather than the eutectic constituent. The outer zone of the work layer, in contact with the metal sheet, which is being rolled, does not show the graphitising effect of Si (0.8–1.15 wt.%). On the contrary, it confirms the hardening effect of the Si in solid solution of the ferrite. The addition of 0.02% of Mg (wt.%) and the inoculation of 6 kg/T of FeB tend to eliminate the graphitising effect of the Si, thus favouring that the undissolved carbon in the austenite is found to form carbides in contrast to the majority formation of graphite.

The Effect of 3D Printing Process Parameters on the Mechanical Properties of PLA Parts

Taking the PLA molded by FDM as the research object, the influence of various process parameters on mechanical properties is investigated through comparative experiments, which provides reference and help for the promotion and application of FDM molding technology. During the molding process, the PLA material undergoes the process of melting to solidification, thus the performance of the molded part is worse than the original due to thermal shrinkage and other reasons. To improve the quality and mechanical properties of the molded parts, the experiment is designed using an orthogonal test method in parallel with nine different sets of process parameters (layer thickness, build direction, filling speed, and infill density, etc.). Ultimately, the mechanical properties of PLA are tested and the results are analyzed respectively to determine the main factors affecting the mechanical properties and their optimal level combination. Among them, fill rate is the crucial factor in compressive property, while build direction has a significant effect on surface roughness, tensile property and bending property.

Parameter optimization during single roller burnishing of AA6061-T6 alloy by design of experiments

Roller burnishing is a surface finishing process that involves plastic deformation of the surface without any removal of the material. The level of surface finish that can be attained in roller burnishing operation depends on several process parameters. Processing at the optimum combination of process parameters is critical for achieving a higher yield during manufacturing. Hence, the present study is carried out to obtain the optimized process parameters during roller burnishing of aluminium alloy AA6061-T6, with an objective to produce a high level of surface finish. The Taguchi method has been used to assess the role of burnishing speed, feed rate, and load on the surface finishing of the alloy. Analysis of variance (ANOVA) and signal-to-noise ratio (S/N) have been employed to analyze, obtain significant parameters, and find out optimum combination levels of the process parameters. The results show that the surface quality of the specimens is significantly improved with burnishing parameters. The analysis of the results shows that the burnishing feed rate has the highest impact on the surface roughness with a contribution of 54.51%, followed by load and burnishing speed.

Multi-Performance Optimization in Electrical Discharge Machining of Al2O3 Ceramics Using Taguchi Base AHP Weighted TOPSIS Method

The main application of electrical discharge machining in ceramic processing is limited to conductive ceramics. However, the most commonly used non-conductive potteries in modern industry, such as aluminum oxide (Al2O3), also reveal the limitations of choosing a suitable process. In this study, Taguchi based TOPSIS coupled with AHP weight method to optimize the machining parameters of EDM on Al2O3 leads to better multi-performance. The results showed that the technique is suitable for tackling multi-performance machining parameter optimization. The adhesive foil had a significant impact on material removal rate, electrode wear rate, and surface roughness, according to the findings. In addition, the response graph of relative closeness is used to determine the optimal combination levels of machining parameters. A confirmation test revealed a good agreement between predicted and experimental preference values at an optimum combination of the input parameters. The suggested experimental and statistical technique is a simple, practical, and reliable methodology for optimizing EDM process parameters on Al2O3 ceramics. This approach might be utilized to optimize and improve additional process parameters in the future.

An integrated identification approach of agile engineering characteristics considering sensitive customer requirements

Under the effects of internal factors and the external environment, some customer requirements can be extremely sensitive to change; these are known as sensitive requirements. These requirements drive the identification and design of the relevant engineering characteristics. This study defines such characteristics as agile engineering characteristics (AECs), which are crucial for redesigning products and prolonging their service life but attract limited research and practice attention. The research question of identifying the product AECs is answered in this study, and three key issues are solved in the proposed methodology. First, the contribution of product engineering characteristics to customer requirements is calculated using an orthogonal experimental design, and the optimal level combination of engineering characteristics to satisfy the customer requirements is determined through the analysis of variation. Subsequently, the relative importance of engineering characteristics is calculated based on data envelopment analysis. Next, an agility index is defined by integrating the customer satisfaction degree, the relative importance degree of engineering characteristics, and the variation of the level of engineering characteristics, to identify the AECs. Finally, based on the identification of the AECs of an electric vehicle air-conditioning heat pump scroll compressor, the results are analysed and compared to illustrate the feasibility and effectiveness of the proposed method.