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Mustajib, M. Imron, Teguh Prasetyo, Heri Awalul Ilhamsah, Rudy Soenoko, and Sugiono. "Optimizing Multi Response Green Machining Using Taguchi Method Based on Grey Relational Analysis." Applied Mechanics and Materials 747 (March 2015): 277–81. http://dx.doi.org/10.4028/www.scientific.net/amm.747.277.
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This paper presents an optimization of multi response green machining of aluminum 6061 valve. The research is started with study literature and early survey to identify various factors that may likely influence in the green machining.The next step is investigating and collecting experiment data of the control factors (working in 3 levels) for depth of cut, feeding, and cutting speed factor on two responses; power consumption and surface roughness (Ra). The data were evaluated using Taguchi method based on grey relational anaylisis. Statistic tools coupled together with Taguchi design to process the output of the experiment. Finally, the research has successfully to deliver knowledges of the cutting speed and feeding factors have a dominant influence in power consumption and surface roughness of the green machining process
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Naresh, N., M. P. Jenarthanan, and R. Hari Prakash. "Multi-objective optimisation of CNC milling process using Grey-Taguchi method in machining of GFRP composites." Multidiscipline Modeling in Materials and Structures 10, no. 2 (August 5, 2014): 265–75. http://dx.doi.org/10.1108/mmms-06-2013-0042.
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Purpose – In milling process the surface roughness and delamination are the most important performance characteristics, which are influenced by many factors like fibre orientation angle, helix angle, feed rate and spindle speed. The selection of these parameters at optimum level plays a vital role in getting minimum surface roughness and delamination factor. The purpose of this paper is to present multi-objective optimisation of Computer Numerical Control milling parameters using Grey-Taguchi method to get minimum surface roughness and delamination factor in machining of glass fibre reinforced plastics (GFRP) composites used in automotive, aircraft and manufacture of space ships. Design/methodology/approach – The experiments are designed and conducted based on Taguchi's L27 orthogonal array by taking fibre orientation angle, helix angle, feed rate and spindle speed at three levels and responses are surface roughness and delamination factor. Taguchi's signal-to-noise (S/N) ratio are determined based on their performance characteristics. A Grey relation grade is obtained by using S/N ratio. Based on Grey relational grade value, optimum levels of parameters have been identified by using response table and response graph. Findings – Optimum levels of parameters for GFRP composites have been identified by using response table and response graph and the significant contributions of controlling parameters are estimated using analysis of variance. Originality/value – The combined effect of fibre orientation angle and helix angle during milling of GFRP composites using Grey relational analysis has not been previously attempted for analysis.
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Cui, Hong, and Chen Shi. "Optimisation of Multi-Response Surface Parameters of the Roving Twist Factor and Spinning Back Zone Draft." Fibres and Textiles in Eastern Europe 27, no. 5(137) (October 31, 2019): 40–49. http://dx.doi.org/10.5604/01.3001.0013.2898.
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In order to obtain the optimal collocation of two important technological parameters in the spinning process, the multi-response surface method was used to optimise the experimental results. Through the orthogonal design of the two factors and four levels of factor encoding, 16 groups of orthogonal experiments were designed; the experimental results were fit using the curve fitting toolbox of Matlab; a regression equation of yarn quality indicators, and in addition to a three-dimensional surface chart, an optimal scheme of the roving twist factor and spinning drafting for a roving twist factor of 110 were established; a spinning back draft of 1.5 was obtained based on experimental results of the response surface analysis and variance regression analysis. Experiments on the optimal scheme were carried out to verify the practicability of the results obtained by this method. The results show that application of the multiple response surface method to the optimisation of process parameters is of practical significance. This method can be applied for the optimisation of other process parameters.
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Kumar, Sunil, and P. N. Rao. "Multi-Response Optimization of process Parameter in Vertical Milling Machine of EN 31 Using Taguchi Method." Journal of University of Shanghai for Science and Technology 23, no. 11 (November 12, 2021): 228–35. http://dx.doi.org/10.51201/jusst/21/11890.
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The purpose of this experimental research is to compare the effectiveness of using Taguchi approaches for multi-response optimization of process parameters in Vertical Milling Machine of EN 31 Material intending to minimize surface roughness and tool wear rate while maximizing material removal rate to improve the productivity of the process with coated carbide insert. Taguchi L9 and Annova have been applied for experimental design and analysis. This experiment shows that feed and depth of cut are factors that are important for tool wear, Depth of cut is a notable factor for Material Removal Rate and feed is the most notable factor for surface roughness. Spindle speed has little effect on tool wear rate, surface roughness, and material removal rate. Mathematical models for three response parameters i.e. tool wear rate, surface roughness, and material removal rate were obtained by regression analysis
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Moslemi, Amir, and Mirmehdi Seyyed-Esfahani. "A novel robust multivariate regression approach to optimize multiple surfaces." RAIRO - Operations Research 52, no. 4-5 (October 2018): 1233–43. http://dx.doi.org/10.1051/ro/2018016.
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Response surface methodology involves relationships between different variables, specifically experimental inputs as controllable factors, and a response or responses by incorporating uncontrollable factors named nuisance. In order to optimize these response surfaces, we should have accurate response models. A common approach to estimate a response surface is the ordinary least squares (OLS) method. Since OLS is very sensitive to outliers, some robust approaches have been discussed in the literature. Most problems face with more than one response which are mostly correlated, that are called multi-response problem. This paper presents a new approach which takes the benefits of robust multivariate regression to cope with the mentioned difficulties. After estimating accurate response surfaces, optimization phase should be applied in order to have proper combination of variables and optimum solutions. Global criterion method of multi-objective optimization has also been used to reach a compromise solution which improves all response variables simultaneously. Finally, the proposed approach is described analytically by a numerical example.
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Jung, B., K.-I. Jang, B.-K. Min, S. J. Lee, and J. Seok. "Parameter optimization for finishing hard materials with magnetorheological fluid using the penalized multi-response Taguchi method." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223, no. 8 (May 6, 2009): 955–68. http://dx.doi.org/10.1243/09544054jem1351.
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This paper presents a novel penalized multi-response Taguchi method that is used to determine the optimal conditions and parameters for a wheel-type magnetorheological (MR) finishing process that uses sintered iron-carbon nanotube (I-CNT) abrasives. The main goal of this study is to achieve the best compromise, within given boundary constraint conditions, between the maximum material removal rate and the minimum surface roughness. The proposed Taguchi method includes two main parameters, namely the weighting loss factor and the severity factor, that account, respectively, for the response weights and the constraint conditions and that control the optimality direction. The method is applied to the finishing of hard-disk slider surfaces made of Al2O3-TiC, and the effects of the weighting loss and severity factors, along with their significance and relative importance in optimizing the finishing process, are thoroughly examined.
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Vora, Jay, Yug Shah, Sakshum Khanna, Vivek K. Patel, Manoj Jagdale, and Rakesh Chaudhari. "Multi-Response Optimization and Influence of Expanded Graphite on Performance of WEDM Process of Ti6Al4V." Journal of Manufacturing and Materials Processing 7, no. 3 (June 7, 2023): 111. http://dx.doi.org/10.3390/jmmp7030111.
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Wire electrical discharge machining (WEDM) is widely preferred for machining difficult-to-cut materials like Ti6Al4V. In the present study, current, pulse-off-duration (Toff), and pulse-on-duration (Toff) were identified as vital input factors for the WEDM process of Ti6Al4V. Material removal rate (MRR) and surface roughness (SR) were selected as output measures for the study. The experiments were carried out by employing Taguchi’s L9 design at three levels. Empirical models were generated, which give the relationship between the input and output factors of the process. To check the acceptability of the model terms, analysis of variance (ANOVA) was used. The regression mode was observed to be significant for the output measures. For MRR, Toff was recorded as the highly significant factor affecting the response values with 74.95% impact, followed by Ton with 16.39%, and current with 6.56%. In the case of SR, Ton was found to be a highly significant factor with a 50.24% impact, followed by current with 43.99%, and Toff with 1.47%. Further, multi-objective optimization by using the HTS technique was performed. The effect of expanded graphite (EG) nano-powder has been studied on the output factors of MRR and SR. The use of EG nano-powder was found to improve WEDM operations as MRR was increased by 45.35%, and simultaneously, SR was reduced by 36.16%. Lastly, the surface morphology of the machined surface was investigated by employing SEM to understand the effect of EG nano-powder. The results have shown a reduction in surface defects by using EG nano-powder compared to the conventional WEDM process.
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Mohamad, Najmiah Radiah, Mohd Farhanulhakim Mohd Razip Wee, Mohd Ambri Mohamed, Azrul Azlan Hamzah, and P. Susthitha Menon. "Multi-response optimization of chromium/gold-based nanofilm Kretschmann-based surface plasmon resonance glucose sensor using finite-difference time-domain and Taguchi method." Nanomaterials and Nanotechnology 10 (January 1, 2020): 184798042098211. http://dx.doi.org/10.1177/1847980420982119.
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Kretschmann-based surface plasmon resonance sensor utilizing chromium and gold nanofilms is ideal for label-free biomedical sensing. In this work, Taguchi’s L9 orthogonal array method was used to optimize the effects of three control factors and noise factor, which are the incident optical wavelength, chromium and gold nanofilm thicknesses, and their root-mean-square surface roughness, on the performance of the Kretschmann-based surface plasmon resonance sensor. The control factors were varied at three levels for a novel multi-response optimization of the Kretschmann-based surface plasmon resonance sensor for the minimum reflectivity, the full-width-at-half-maximum, and the sensitivity of 3% glucose detection, executed using Lumerical’s two-dimensional finite-difference time-domain method. Using Taguchi method, the best control factor setting in air was A3B2C2 corresponding to 785 nm optical wavelength, 0.5 nm chromium, and 50 nm gold layer thickness, respectively, with minimum reflectivity of 0.0017%, full-width-at-half-maximum of 0.4759°, and glucose-sensing sensitivity of 106.73°·RIU−1. The detection accuracy and quality factor were 0.01 and 224.26 RIU−1, respectively. It was also indicated that chromium nanofilm thickness of 0.5–3 nm and its root-mean-square surface roughness has a negligible factor effect compared to other control factors. Taguchi method’s factor effect analysis showed that for chromium layer thickness of 1–3 nm, the minimum reflectivity values are predominantly determined by the gold layer thickness with 75% factor effect, followed by optical wavelength with 11%. Factor effect of full-width-at-half-maximum is determined by optical wavelength (57%), followed by gold layer thickness (38%). Sensitivity is 88% determined by optical wavelength and 10% determined by gold layer thickness. The Kretschmann-based surface plasmon resonance glucose sensor with the best glucose-sensing sensitivity was at optical wavelength of 632.8 nm with a higher sensitivity value of 163.415°·RIU−1 but lower detection accuracy and quality factor values of 0.001 and 24.86 RIU−1, respectively, compared to near-infrared wavelength of 785 nm. In conclusion, finite-difference time-domain and Taguchi method is suitable for multi-response optimization of control and noise factors of Kretschmann-based surface plasmon resonance sensors.
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Debnath, Shantanu, and Soumya Ghosh. "Experimental investigation of Electro discharge machining process by AHP-MOORA technique." Journal of Industrial Engineering and Decision Making 2, no. 1 (May 4, 2021): 1–7. http://dx.doi.org/10.31181/jiedm200201001d.
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In the current study, Analytic Hierarchy Process (AHP) combined with Multi-objective optimization by ratio analysis (MOORA) was adopted to find the efficiency of optimizing multiple performance characteristics for EDM of Al-4.5%Cu- SiC composite using a cylindrical copper electrode. The influence of three machine process parameter pulse on (TON), peak current, duty cycle, and one material variable weight fraction on the response variables material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR) have been investigated using multi-attribute decision- making model. The response surface methodology (RSM) central composite designs (CCD) have been used as the experiment's design. The weight factors for the output responses assigned by the AHP method and the most desirable significant factor levels determined by the MOORA method. The method implemented in this paper is advantageous in various real-life decision-making problems in the manufacturing environment.
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Wang, Feng, Hong Nan Li, and Ting Hua Yi. "Research on Inelastic Response Spectra for Asymmetric Plan Systems Subjected to Bi-Directional Earthquake Motions." Applied Mechanics and Materials 166-169 (May 2012): 2332–36. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.2332.
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The limitations of traditional inelastic response spectra are discussed. Considering a one-storey asymmetric plan system subjected to perpendicular bi-directional earthquake motions, the inelastic multi-dimensional strength reduction factor spectra is presented. The yield rule of the asymmetric plan system is determined by two-dimensional yield-surface plasticity function. The spectral equation is simplified by the relationship of strength reduction factors between x-direction and y-direction.The multi-dimensional spectra are analyzed based on 30 pair strong earthquake motion records for hard soil site, intermediate soil site and soft soil site. Analytic results shows that the strength reduction factor mean spectra for each soil site has its own characteristics, and the strength reduction factor spectra is affected strongly by ductility, normalized stiffness eccentricity, period and rotation frequency ratio.
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An, Zhi Guo, and Yu Zhang. "Multi-Objective Optimization for High Strength Steel Sheet Metal Forming Process Based on Response Surface Methodology." Advanced Materials Research 154-155 (October 2010): 1223–27. http://dx.doi.org/10.4028/www.scientific.net/amr.154-155.1223.
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In sheet metal forming process, the input process parameters scatter and considerably result in unreliablity in practical production. Optimization for sheet metal forming process is often considered as a multi-objective problem. An optimizition strategy for high strength steel (HSS) sheet metal forming process was suggested based on response surface methodology (RSM). Latin Hypercube Sampling (LHS) method was introduced to design the rational experimental samples; the objective function was defined based on cracking factor wrinkle factor and severe thinning factor; the accurate response surface for sheet metal forming problem was built by Least Square Method; Multi-objective Genetic Algorithm(MOGA) was adoped in optimization and Pareto solution was selected. The strategy was applied to analyze a HSS auto-part, the result has proved this method suitable for optimization design of HSS sheet metal forming process.
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Kumar, Dhiraj, and Suhasini Gururaja. "Abrasive waterjet machining of Ti/CFRP/Ti laminate and multi-objective optimization of the process parameters using response surface methodology." Journal of Composite Materials 54, no. 13 (November 5, 2019): 1741–59. http://dx.doi.org/10.1177/0021998319884611.
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In present work, abrasive waterjet machining has been used to machine adhesively bonded titanium-carbon fiber-reinforced plastics-titanium hybrid laminate with varying traverse speed, jet pressure, and stand-off distance. The effect of varying abrasive waterjet machining parameters on cut quality has been quantified by material removal rate, metal composite interface damage factor, taper ratio ( T r), and surface roughness (Ra). Response surface methodology along with central composite design has been used to analyze the influence of process parameters on output responses. Additionally, analysis of variance was performed to identify the significant parameters on the output responses. For better abrasive waterjet cut quality, the optimal values of process parameters obtained were 200 MPa jet pressure, 237.693 mm/min traverse speed, and 1 mm stand-off distance. The corresponding material removal rate, metal composite interface damage factor, taper ratio, and surface roughness are 5.388 mm3/s, 1.41, 1.16, and 3.827 µm, respectively. Furthermore, validation tests have been performed with obtained optimal parameters that deliver satisfactory outcomes with an error of 5.35%, 3.07%, 2.29%, and 0.39% for material removal rate, metal composite interface damage factor, taper ratio, and surface roughness, respectively.
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Fan, Shu-Kai S., and Kuo-Nan Huang. "AMSE optimal design using generalized estimation for multi-factor response surfaces." Journal of Chemometrics 21, no. 3-4 (2007): 126–32. http://dx.doi.org/10.1002/cem.1049.
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An, Zhi Guo, and Yu Zhang. "Blank Optimization of Sheet Metal Forming Based on Response Surface Methodology." Advanced Materials Research 189-193 (February 2011): 2851–55. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.2851.
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The thickness variation of drawing part is usually very complicated, which causes the accurate calculation of the surface area of drawing part to be very difficult. Blank optimization of sheet metal forming is often considered as a multi-objective problem. A blank optimization strategy of sheet metal forming process was suggested based on Response Surface Methodology (RSM). Latin Hypercube Sampling (LHS) method was introduced to design the rational experimental samples; the objective function was defined based on crack factor and wrinkle factor; the accurate response surface for sheet metal forming problem was built by Least Square Method; Genetic Algorithm (GA) was adopted in optimization and Pareto solution was selected. The strategy was applied in blank optimization of an auto-part, this method was proved suitable for blank optimization of sheet metal forming.
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Neeli, Naresh, M. P. Jenarthanan, and G. Dileep Kumar. "Multi-response optimization for machining GFRP composites using GRA and DFA." Multidiscipline Modeling in Materials and Structures 14, no. 3 (September 3, 2018): 482–96. http://dx.doi.org/10.1108/mmms-08-2017-0092.
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Purpose The purpose of this paper is to optimise the process parameters, namely, fibre orientation angle, helix angle, spindle speed, and feed rate in milling of glass fibre-reinforced plastic (GFRP) composites using grey relational analysis (GRA) and desirability function analysis (DFA). Design/methodology/approach In this work, experiments were carried out as per the Taguchi experimental design and an L27 orthogonal array was used to study the influence of various combinations of process parameters on surface roughness and delamination factor. As a dynamic approach, the multiple response optimisation was carried out using GRA and DFA for simultaneous evaluation. These two methods are best suited for multiple criteria evaluation and are also not much complicated. Findings The process parameters were found optimum at a fibre orientation angle of 15°, helix angle of 25°, spindle speed of 6,000 rpm, and a feed rate of 0.04 mm/rev. Analysis of variance was employed to classify the significant parameters affecting the responses. The results indicate that the fibre orientation angle is the most significant parameter preceded by helix angle, feed rate, and spindle speed for GFRP composites. Originality/value An attempt to optimise surface roughness and delamination factor together by combined approach of GRA and DFA has not been previously done.
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Singh, Kalyan Kumar, and Dhiraj Kumar. "Experimental investigation and modelling of drilling on multi-wall carbon nanotube–embedded epoxy/glass fabric polymeric nanocomposites." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 232, no. 11 (December 20, 2016): 1943–59. http://dx.doi.org/10.1177/0954405416682277.
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The primary objective of this research is to investigate the effect of multi-wall carbon nanotubes on drilling of multi-wall carbon nanotube–embedded epoxy/glass fabric polymeric nanocomposites. The experiments were conducted on composites with varying the weight percentage of multi-wall carbon nanotubes content to analyse drilling-induced delamination and surface roughness, which affect the quality and property of the drilled holes. The drilling parameters considered are spindle speed, feed rate and drill diameter. The microstructure of the holes was characterized using field emission scanning electron microscopy methods. For correlating the effect of the weight percentage of carbon nanotubes with the referred drilling parameters, a mathematical model was used, based on response surface methodology. For development of the mathematical model, four factors, namely, spindle speed, feed rate, diameter of drill and weight percentage of carbon nanotubes, were taken into account. The result established that delamination and surface roughness are reduced as multi-wall carbon nanotubes’ content increases. Maximum improvement in delamination factor was observed in the case of 1.0 wt% multi-wall carbon nanotube–embedded epoxy/glass fabric polymeric nanocomposite, which is 25% and 31.09% at the entrance and exit sides of the hole, respectively. With an increase in the feed rate and the drill diameter, delamination factor increases; however, with an increase in spindle speed, delamination factor decreases. Lower value of surface roughness (1.113 µm) was observed in 1.5 wt% of multi-wall carbon nanotube–embedded epoxy/glass fabric polymeric nanocomposite. However, surface roughness increases with an increase in feed rate and drill diameter.
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Singh, Talwinder, J. S. Dureja, Manu Dogra, and Manpreet S. Bhatti. "Multi-response optimization in environment friendly turning of AISI 304 austenitic stainless steel." Multidiscipline Modeling in Materials and Structures 15, no. 3 (May 7, 2019): 538–58. http://dx.doi.org/10.1108/mmms-07-2018-0139.
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Purpose The purpose of this paper is to investigate the influence of turning parameters such as cutting speed, feed rate and depth of cut on tool flank wear and machined surface quality of AISI 304 stainless steel during environment friendly turning under nanofluid minimum quantity lubrication (NMQL) conditions using PVD-coated carbide cutting inserts. Design/methodology/approach Turning experiments are conducted as per the central composite rotatable design under the response surface methodology. ANOVA and regression analysis are employed to examine significant cutting parameters and develop mathematical models for VB (tool flank wear) and Ra (surface roughness). Multi-response desirability optimization approach is used to investigate optimum turning parameters for simultaneously minimizing VB and Ra. Findings Optimal input turning parameters are observed as follows: cutting speed: 168.06 m/min., feed rate: 0.06 mm/rev. and depth of cut: 0.25 mm with predicted optimal output response factors: VB: 106.864 µm and Ra: 0.571 µm at the 0.753 desirability level. ANOVA test reveals depth of cut and cutting speed-feed rate interaction as statistically significant factors influencing tool flank wear, whereas cutting speed is a dominating factor affecting surface roughness. Confirmation tests show 5.70 and 3.71 percent error between predicted and experimental examined values of VB and Ra, respectively. Research limitations/implications AISI 304 is a highly consumed grade of stainless steel in aerospace components, chemical equipment, nuclear industry, pressure vessels, food processing equipment, paper industry, etc. However, AISI 304 stainless steel is considered as a difficult-to-cut material because of its high strength, rapid work hardening and low heat conductivity. This leads to lesser tool life and poor surface finish. Consequently, the optimization of machining parameters is necessary to minimize tool wear and surface roughness. The results obtained in this research can be used as turning database for the above-mentioned industries for attaining a better machined surface quality and tool performance under environment friendly machining conditions. Practical implications Turning of AISI 304 stainless steel under NMQL conditions results in environment friendly machining process by maintaining a dry, healthy, clean and pollution free working area. Originality/value Machining of AISI 304 stainless steel under vegetable oil-based NMQL conditions has not been investigated previously.
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Amanuel, Tarikayehu, and Manish Mishra. "Thermohydraulic optimization of triple concentric-tube heat exchanger: A multi-objective approach." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 233, no. 3 (May 31, 2018): 589–600. http://dx.doi.org/10.1177/0954408918779232.
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In the present study, optimization of heat transfer and pressure drop characteristics in a triple concentric tube heat exchanger has been done using the results of numerical simulation. A commercial CFD software ANSYS Fluent v17.0 has been employed for simulating the flow and heat transfer, while optimization has been done by Response surface methodology (RSM) and Genetic algorithm (GA). The effective parameters in the study are Reynolds number (2500 ≤ Re ≤ 10,000) and Length to hydraulic diameter ratio (100 ≤ L/Dh ≤ 220). The optimum values, as well as the functional relationship between the design factors (Re and L/Dh) and response variables (Nu and f), have also been developed. It has been found that both the design factors (Re and L/Dh) have a strong influence on the response variables (Nu and f). With the increase in Re (flow rate), a large growth in Nusselt number and decline in friction factor has been observed. However, with the increase in L/Dh, an enormous decrease in both Nusselt number and friction factor has been found.
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Chaudhary, Tina, Arshad Noor Siddiquee, Arindam Kumar Chanda, Mustufa Haider Abidi, and Abdulrahman Al-Ahmari. "Multi-response optimization for Nimonic alloy miniature gear fabrication using wire electrical discharge machining." Advances in Mechanical Engineering 12, no. 10 (October 2020): 168781402096758. http://dx.doi.org/10.1177/1687814020967580.
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Generally, gear is an essential component in various electro-mechanical devices, but its manufacturing at the micro-level is challenging. The non-conventional manufacturing processes, such as electro-discharge machining (EDM), is suitable in gear fabrication. Although miniature gears have strict accuracy requirements, the optimization of the EDM process parameters, especially for advanced materials and alloys, is critical. In this paper, Nimonic alloy miniature gears are manufactured using wire-EDM and the effect of process parameters, such as peak current, pulse-off (POFF) time, pulse-on (PON) time, wire tension, and dielectric fluid on the response factors are analyzed. The primary response factors, such as surface roughness, machining time, material removal rate, kerf width (KW), surface microhardness, and depth of microhardness are considered. Also, different dielectric fluids are prepared, which include ethylene glycol mixed demineralized water, oxygen mixed demineralized water, ethylene glycol and alumina powder mixed demineralized water, and ethylene glycol alumina powder and oxygen mixed demineralized water. Furthermore, the effect of process parameters on the multi-response using Pareto ANOVA has been analyzed. The results demonstrate that ethylene glycol mixed demineralized water, as a dielectric fluid, is the most influencing parameter to reduce the surface roughness, machining time, KW, and improve micro-hardness. Thus, dielectric fluid is an essential factor obtained from multi-response optimization followed by peak current, POFF time, wire tension, and PON time.
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Jenarthanan, M. P., R. Gokulakrishnan, B. Jagannaath, and P. Ganesh Raj. "Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with principal component analysis." Multidiscipline Modeling in Materials and Structures 13, no. 1 (June 12, 2017): 58–70. http://dx.doi.org/10.1108/mmms-02-2016-0007.
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Purpose The purpose of this paper is to find out the optimum machining parameters using Taguchi technique with principal component analysis (PCA) during end milling of GFRP composites. Design/methodology/approach In multi-objective optimization, weight criteria of each objective are important for producing better and accurate solutions. This method has been employed for simultaneous minimization of surface roughness, cutting force and delamination factor. Experiments were planned using Taguchi’s orthogonal array with the machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate and depth of cut were optimized with considerations of multiple response characteristics, including machining force, surface roughness and delamination as the responses. PCA is adopted to find the weight factors involved for all objectives. Finally analysis of variance concept is employed on multi-SN ratio to find out the relative significance of machining parameter in terms of their percentage contribution. Findings The multi-SN ratio is achieved by the product of weight factor and SN ratio to the performance characteristics in the utility concept. The results show that a combination of machining parameters for the optimized results has helix angle of 35°, machining speed of 4,000 m/min, feed rate of 750 mm/rev and depth of cut of 2.0 mm. Originality/value Effect of milling of GFRP composites on delamination factor, surface roughness and machining force with various helix angle solid carbide end mill has not been analysed yet using PCA techniques.
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Choudhuri, Bikash, Ruma Sen, Subrata Kumar Ghosh, and Subhash Chandra Saha. "Modelling and multi-response optimization of wire electric discharge machining parameters using response surface methodology and grey–fuzzy algorithm." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 10 (December 14, 2015): 1760–74. http://dx.doi.org/10.1177/0954405415607382.
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Wire electric discharge machining is a non-conventional machining wherein the quality and cost of machining are influenced by the process parameters. This investigation focuses on finding the optimal level of process parameters, which is for better surface finish, material removal rate and lower wire consumption for machining stainless steel-316 using the grey–fuzzy algorithm. Grey relational technique is applied to find the grey coefficient of each performance, and fuzzy evaluates the multiple performance characteristics index according to the grey relational coefficient of each response. Response surface methodology and the analysis of variance were used for modelling and analysis of responses to predict and find the influence of machining parameters and their proportion of contribution on the individual and overall responses. The measured values from confirmation experiments were compared with the predicted values, which indicate that the proposed models can be effectively used to predict the responses in the wire electrical discharge machining of AISI stainless steel-316. It is found that servo gap set voltage is the most influential factor for this particular steel followed by pulse off time, pulse on time and wire feed rate.
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Xie, Eric, Colin Cook, L. Grayson-Warren, and Jason Benkoski. "Novel surfactant self-assembly process generates multi-scale surface topographies for stem cell growth and differentiation." Chemical Industry 72, no. 2 (2018): 69–80. http://dx.doi.org/10.2298/hemind170508020x.
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Topographical features on a substrate can greatly influence stem cell fate through contact guidance. While the response of stem cells to topography at the nano-, micro-, and meso-scale has been studied extensively, little is known about the interplay of surface features acting simultaneously across multiple length scales. A limiting factor has been the availability of high throughput methods for probing the potentially unlimited parameter space. Herein we describe a facile method for rapidly generating a hierarchy of multi-scaled topographical features on polymer substrates via the self-assembly of surfactants at the monomer/water interface. Having previously assembled polydimethylsiloxane-diacrylate (PDMS-DA) into surfaces resembling multiple tissue morphologies, the current study refines this method to produce biocompatible substrates. To manage the large parameter space, we limit the scope of this study to surface features spanning nanometer (< 1 ?m) and micrometer (1-50 ?m) length scales, which arise both individually and in combination. Adipose-derived stem cells were plated onto five surface types and their morphology, proliferation, and osteogenic differentiation were assessed after non-inductive and osteogenic culture. We observed statistically significant differences in cellular responses to each surface. Among our observations, the increased osteogenesis of cells on surfaces with nano-scaled features superimposed over micro-scaled features suggests that such hierarchical surface structure mediates the osteogenic properties of a surface.
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Zhou, Lingmin, Yongfeng Sui, Jibin Lan, Peng Chu, Yujun Liu, Bin Feng, and Liheng Du. "Optimum design for wavy fin tube in an air cooler with genetic algorithm." Journal of Physics: Conference Series 2369, no. 1 (November 1, 2022): 012028. http://dx.doi.org/10.1088/1742-6596/2369/1/012028.
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A strategy by multi-objective genetic algorithm (MOGA) combined with Kriging response surface is proposed for optimum design of wavy fin tube in an air cooler, while minimum pressure loss factor, maximum heat transfer factor and overall performance factor as three objective functions. The results show that the effects of fin height and fin density on the overall performance are positive and the wave number and wave angle are negative; The overall performance of parallel fin is higher than staggered fin; The overall performance of small pipe diameter of wave fin is higher than big pipe diameter; The overall performance reaches the optimum as fin height is 20.7 mm, fin density is 9.9, wave number is 11, wave angle is 4°; The multi-objective genetic algorithm combined with Kriging response surface eliminates the dependence on empirical relation. The results can be used to guide the optimum design of wavy fin tube.
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Aydin, Cem Savas, Senim Ozgurler, Mehmet Bulent Durmusoglu, and Mesut Ozgurler. "Response surface approach to robust design of assembly cells through simulation." Assembly Automation 38, no. 4 (September 3, 2018): 450–64. http://dx.doi.org/10.1108/aa-08-2017-093.
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Purpose This paper aims to present a multi-response robust design (RD) optimization approach for U-shaped assembly cells (ACs) with multi-functional walking-workers by using operational design (OD) factors in a simulation setting. The proposed methodology incorporated the design factors related to the operation of ACs into an RD framework. Utilization of OD factors provided a practical design approach for ACs addressing system robustness without modifying the cell structure. Design/methodology/approach Taguchi’s design philosophy and response surface meta-models have been combined for robust simulation optimization (SO). Multiple performance measures have been considered for the study and concurrently optimized by using a multi-response optimization (MRO) approach. Simulation setting provided flexibility in experimental design selection and facilitated experiments by avoiding cost and time constraints in real-world experiments. Findings The present approach is illustrated through RD of an AC for performance measures: average throughput time, average WIP inventory and cycle time. Findings are in line with expectations that a significant reduction in performance variability is attainable by trading-off optimality for robustness. Reductions in expected performance (optimality) values are negligible in comparison to reductions in performance variability (robustness). Practical implications ACs designed for robustness are more likely to meet design objectives once they are implemented, preventing changes or roll-backs. Successful implementations serve as examples to shop-floor personnel alleviating issues such as operator/supervisor resistance and scepticism, encouraging participation and facilitating teamwork. Originality/value ACs include many activities related to cell operation which can be used for performance optimization. The proposed framework is a realistic design approach using OD factors and considering system stochasticity in terms of noise factors for RD optimization through simulation. To the best of the authors’ knowledge, it is the first time a multi-response RD optimization approach for U-shaped manual ACs with multi-functional walking-workers using factors related to AC operation is proposed.
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Bisono, Rahayu Mekar, and Rifky Maulana Yusron. "Optimization Multi Response on Electrical Discharge Machining Sinking Process Using Taguchi-Grey-Fuzzy Methods." International journal of science, engineering, and information technology 4, no. 2 (July 22, 2020): 209–14. http://dx.doi.org/10.21107/ijseit.v4i2.6705.
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Electronic Discharge Machining (EDM) sinking applied widely in advance material manufacturing, every process parameter will count on this company. Their performance evaluated by some parameters such as surface roughness and tool wear ratio. Then they will be a dependent variable on this research. Independent variables on this research are electrode polarization, gap voltage, duty factor and pulse current. Every variable has three levels, except electrode polarization has two levels. This research conducting using Taguchi matrix orthogonal L18 (21×33) methods. The aim of this experiment is to evaluate optimization parameter process on EDM sinking, using Taguchi-Grey-Fuzzy methods. Characteristics response optimal applied are ‘smaller better’ for surface response roughness and tool wear ratio. This research using DAC tool steel as work-piece. DAC is most widely used as die for aluminum and zinc die-casting. The aim of this research is finding contribution of variable in EDM sinking parameter. Result of this research show contribution from variable process to reduce variance total observed response simultaneously, in order are electrode polarization on 49,53%, gap voltage on 23,52%, duty factor on 5,45% and pulse current on 9,92%. From validated optimization in confirmation experiment, to conclude combination variable process optimal response value is electrode polarization on positive, gap voltage at 50V, duty factor at 0.5 and pulse current at 12A.
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Singh, Dhirendra Pratap. "Optimization of Electric Discharge Machining of Al/Al2O3 Metal Matrix Composites using MOPSO." International Journal of Engineering Research in Mechanical and Civil Engineering (IJERMCE) 9, no. 5 (May 18, 2022): 39–47. http://dx.doi.org/10.36647/ijermce/09.05.a007.
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In this article, Response Surface Methodology (RSM) and Multi-objective Particle Swarm Optimization (MOPSO) were used to optimize the output response of Material Removal Rate (MRR) and Surface Roughness(SR) of die-sinking Electrical discharge machining (EDM). An aluminum based metal matrix composites, reinforced with alumina, prepared by stir casting, was used for machining on EDM by Copper (Cu) and Titanium (Ti) tool. Box- Behnken Design (BBD) approach of RSM was used to design the experiment by considering four input factors at three levels. This developed model for multi-objective optimization by MOPSO and an RSM-based multi-objective optimization was also designed for input parameters. And it was found that the MOPSO technique was easy and valuable for parametric optimization of EDM. From MOPSO, optimized input parameters for machining of AMMC using Cu tool are current 4A, Voltage 60V, pulse on-time 100 µs, and duty factor 6. From MOPSO, optimized input parameters for machining of AMMC using Ti tool are current 4.241658A, Voltage 60V, pulse on-time 100 µs, and duty factor 4. The confirmatory test found that MRR and SR decreased by 63.86 % and 53.083% for the Cu tool, respectively, for MOPSO compared to RSM optimize value.
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Wibowo, Yohanes T., Nurhadi Siswanto, and Mokh Suef. "Response surface methodology approach in achieving multi-response setup optimization in the machining process." Salud, Ciencia y Tecnología 2, S2 (December 31, 2022): 190. http://dx.doi.org/10.56294/saludcyt2022190.
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A machining cost is constructed on many factors. All aspects potentially raise the additional charges resulting from not achieving dimension due to tool wear level. The accuracy of parameters determines the effectiveness of the machining process. However, these parameters are sensitive, so the different machines may not provide the same performance. The specific machining parameters become less suitable for others. This experimental approach is proposed to obtain the parameter used on other machines without reducing the performance. This multi-response study used a response surface methodology by selecting the material removal area, feed rate, spindle speed, and the number of repetitions as input have a dominant influence on the tool wear and the dimension deviation. A comprehensive range with the specified target is obtained by applying different weights. Testing on 11 units of machines from 3 other countries provides the same performance and contributes to saving 15 % of machining time.
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Kasim, Mohd Shahir, Che Hassan Che Haron, Jaharah Abd Ghani, E. Mohamad, Raja Izamshah, Amran Ali Mohd, and J. B. Saedon. "Multi-Objective Optimization Using Box-Behken of Response Surface Methodology for High-Speed Machining of Inconel 718." Applied Mechanics and Materials 629 (October 2014): 487–92. http://dx.doi.org/10.4028/www.scientific.net/amm.629.487.
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This study was carried out to investigate how the high-speed milling of Inconel 718 using ball nose end mill could enhance the productivity and quality of the finish parts. The experimental work was carried out through Response Surface Methodology via Box-Behnken design. The effect of prominent milling parameters, namely cutting speed, feed rate, depth of cut (DOC), and width of cut (WOC) were studied to evaluate their effects on tool life, surface roughness and cutting force. In this study, the cutting speed, feed rate, DOC, and WOC were in the range of 100 - 140 m/min, 0.1 - 0.2 mm/tooth, 0.5 - 1.0 mm and 0.2 - 1.8 mm, respectively. In order to reduce the effect of heat generated during the high speed milling operation, minimum quantity lubrication of 50 ml/hr was used. The effect of input factors on the responds was identified by mean of ANOVA. The response of tool life, surface roughness and cutting force together with calculated material removal rate were then simultaneously optimized and further described by perturbation graph. Interaction between WOC with other factors was found to be the most dominating factor of all responds. The optimum cutting parameter which obtained the longest tool life of 60 mins, minimum surface roughness of 0.262 μm and resultant force of 221 N was at cutting speed of 100 m/min, feed rate of 0.15 mm/tooth, DOC 0.5 m and WOC 0.66 mm.
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Yang, Guo Hao, Jun Jun Guan, Jin Shui Wang, and Feng Jia. "Optimization of Multi-Strain Solid State Fermentation to Improve the Content of Soybean Meal Protein by Response Surface Analysis." Advanced Materials Research 690-693 (May 2013): 1234–38. http://dx.doi.org/10.4028/www.scientific.net/amr.690-693.1234.
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The aim of this study was to optimize the variables which affect the protein content of fermented soybean meal (FSBM) with multi-strain in solid state condition. Response surface methodology (Box-behnken design) was used to design the experiments. Also, the effects of each factor and their interactions on protein content were analyzed. Regression equation between the influencing factors (moisture content, inoculation ratio and fermentation period) and the response value (protein content) was established and the results revealed that the optimal conditions were 56% moisture content, 9.5% inoculation ratio and fermentation periods was 43.5 h. Under these conditions, the actual protein content of FSBM reached 56.96%, which was very close to the predicted value (57.08%). The good correlation between predicted and actual values proved the validity of the response model.
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Gopu, P., M. Dev Anand, and . "RSM And ANFIS Based Parameters Prediction of Robot Using GRA." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 604. http://dx.doi.org/10.14419/ijet.v7i4.36.24208.
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Ability of robot arm manipulation must be highly accurate and repeatable one. Performance uncertainty is causes by some noise factor. The effects of these factors were model to reduce the uncertainty of the robotic arm performance. In this paper highlights the prediction of output parameters robot cell data like X, Y and Z axis through Response Surface Methodology (RSM) and Adaptive Neuro Fuzzy Inference System (ANFIS) for reduce the performance variation of the robot. The input kinematic parameters like θ1, θ2, θ3, θ4, θ5 has been considered and the output multi objective parameters X, Y and Z axis has been converted in to single objective parameter. The graph which plots between parameters and the output response indicates the influence of the every single parameter for the performance output contribution. From the simulated values of Response Surface Methodology and Adaptive Neuro Fuzzy Inference System, the percentage of error obtained in Adaptive Neuro Fuzzy Inference System has minimum one when compared with Response Surface Methodology of prediction.
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Chen, Lin. "Dynamic Interaction Between Rigid Surface Foundations on Multi-Layered Half Space." International Journal of Structural Stability and Dynamics 16, no. 05 (April 27, 2016): 1550004. http://dx.doi.org/10.1142/s0219455415500042.
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A numerical approach is presented to calculate the dynamic response of a group of rigid surface foundations. The formulation is unconditionally stable and has the computational simplicity with only the algebraic calculations involved. It imposes no limit to the foundation shape, foundation separations, thickness of the layered medium and magnitude of frequency. In the analysis, the foundation–ground interface is discretized into a number of sub square-regions. The Green’s function, which is obtained by the Fourier–Bessel transform and precise integration method, is employed to calculate the dynamic response of each sub-region. Finally, a system of linear algebraic equation in terms of the contact forces within each sub-region is observed, which leads to the desired dynamic impedance functions of the foundations. Comparison is carried out between the proposed method and the solutions available in the literature. Parametric studies on the dynamic interaction between adjacent foundations are also described. Addressed in this study are the effects of the distance and direction of foundation alignment. Several conclusions are drawn the significance of each factor. Illustrative results for a case of several closely-spaced foundations are also presented. Although the dynamic interaction analysis of foundations is concerned here, further applications of this approach can be extended to the interaction analysis of structures.
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Auysakul, Jutamanee, Apidet Booranawong, Nitipan Vittayaphadung, and Pruittikorn Smithmaitrie. "An Optimized Design of the Soft Bellow Actuator Based on the Box–Behnken Response Surface Design." Actuators 12, no. 7 (July 24, 2023): 300. http://dx.doi.org/10.3390/act12070300.
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Soft actuator technology is extensively utilized in robotic manipulation applications. However, several existing designs of soft actuators suffer from drawbacks such as a complex casting process, a multi-air chamber configuration, and insufficient grasping force. In this study, we propose a novel soft bellow design featuring a single air chamber, which simplifies the fabrication process of the actual model. To enhance the performance of the proposed design, we employ the Box–Behnken response surface design to generate a design matrix for implementing different levels of design factors in the finite element model. The FEA response is then subjected to an analysis of variance to identify significant factors and establish a regression model for deformation and stress response prediction. Among the considered responses, the wall thickness emerges as the most influential factor, followed by the divided ratio of radians and the number of bellows. Validation of the optimized soft bellow actuator’s deformation response is performed through comparison with experimental data. Moreover, the soft bellow actuator is capable of exerting a pulling force of 8.16 N when used in conjunction with a simple gripper structure design, enabling effective object manipulation. Additionally, the soft bellow design boasts cost-effectiveness and easy moldability, facilitating seamless integration with different gripper frames for diverse applications. Its simplicity and versatility make it a promising choice for various robotic manipulation tasks.
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Jenarthanan, M. P., Venkata Sai Sunil Gujjalapudi, and Venkatraman V. "Multi-objective optimization in end-milling of glass fiber reinforced polymer composites using desirability functional analysis and grey relational analysis." Multidiscipline Modeling in Materials and Structures 13, no. 3 (October 9, 2017): 391–408. http://dx.doi.org/10.1108/mmms-11-2016-0059.
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Purpose The purpose of this paper is to originate a statistical model for delamination factor, surface roughness, machining force and also to determine and compare the effects of machining parameters (spindle speed, fiber orientation angle, helix angle and feed rate) on the output responses during end-milling of glass fiber reinforced polymers (GFRP) by using desirability functional analysis (DFA) and grey relational analysis (GRA). Design/methodology/approach Based on Taguchi’s L27 orthogonal array, milling experiments were carried on GFRP composite plates employing solid carbide end mills with different helix angles. The machining parameters were optimized by an approach based on DFA and GRA, which were useful tools for optimizing multi-response considerations, namely, machining force, surface roughness and delamination factor. A composite desirability index was obtained for multi-responses using individual desirability values from DFA. Based on this index and grey relational grade the optimum levels of parameters were identified and significant contribution of parameters was ascertained by analysis of variance. Findings Fiber orientation angle (66.75 percent) was the significant parameter preceded by feed rate (15.05 percent), helix angle (7.76 percent) and spindle speed (0.30 percent) for GFRP composite plates. Originality/value Multi-objective optimization in end-milling of GFRP composites using DFA and GRA has not been performed yet.
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Kluz, Rafał, Witold Habrat, Magdalena Bucior, Krzysztof Krupa, and Jarosław Sęp. "Multi-criteria optimization of the turning parameters of Ti-6Al-4V titanium alloy using the Response Surface Methodology." Eksploatacja i Niezawodnosc - Maintenance and Reliability 24, no. 4 (October 10, 2022): 668–76. http://dx.doi.org/10.17531/ein.2022.4.7.
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The paper depicts an application of Response Surface Methodology (RSM) for predicting selected parameters in turning of Ti-6Al-4V titanium alloy using polycrystalline diamond tool. Response surface plots that are generated by the model helps in determining the optimum combination of input factors (cutting speed vc and feed rate f) for best possible surface roughness (Sa), cutting force (Fc)and temperature (T) for dry and cooling turning. The methodology of multi-criteria optimization was used to establish the interaction between input parameters and given responses
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Priyadarshini, Manisha, and Kamal Pal. "A Comparative Study for Machining of Ti–6Al–4V Alloy for Multi-Criteria Response." Journal of Advanced Manufacturing Systems 17, no. 04 (October 10, 2018): 515–31. http://dx.doi.org/10.1142/s0219686718500294.
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Nowadays, it has become very difficult for the manufacturer to satisfy all its customers with satisfactory products, as they have different demands considering the responses. However, hard-to-machine materials are difficult to manufacture. This study explores the application of electro-discharge machining (EDM) of Ti–6Al–4V alloy with pulse duration (Ton), duty factor ([Formula: see text], peak current (Ip) and gap voltage (Vg) as the control parameters using pure copper electrode. Machining effects are evaluated by performance characteristics including material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) by considering the multi-criteria preference of the customers that vary with the preference of responses. For the experiment, proper orthogonal arrays are found out using Taguchi methodology. The optimum parametric settings were obtained by utility-concept-based Taguchi method which were compared with desirability-approach-based Taguchi. It was found that utility-concept-based Taguchi optimization methodology results in more feasible parametric setting which has also been confirmed by the validation experiments. The optimum values of process variables obtained were pulse duration of 30[Formula: see text][Formula: see text]s, duty factor of 9%, peak current of 10[Formula: see text]A and gap voltage of 6[Formula: see text]V to achieve maximum MRR and lower TWR with better surface finish to satisfy multi-user criteria.
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Fedai, Yusuf, and Hediye Kirli Akin. "Optimization of machining parameters in face milling using multi-objective Taguchi technique." Tehnički glasnik 12, no. 2 (June 28, 2018): 104–8. http://dx.doi.org/10.31803/tg-20180201125123.
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In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique.
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Mullen, Steven F. "Toward a predictive theoretical model for osmolality rise with non-humidified incubation: a randomized, multivariate response-surface study." Human Reproduction 36, no. 5 (February 9, 2021): 1230–41. http://dx.doi.org/10.1093/humrep/deab015.
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Abstract STUDY QUESTION What factors associated with embryo culture techniques contribute to the rate of medium osmolality change over time in an embryo culture incubator without added humidity? SUMMARY ANSWER The surface area-to-volume ratio of culture medium (surface area of the medium exposed to an oil overlay), as well as the density and height of the overlaying oil, all interact in a quantitative way to affect the osmolality rise over time. WHAT IS KNOWN ALREADY Factors such as medium volume, different oil types, and associated properties, individually, can affect osmolality change during non-humidified incubation. STUDY DESIGN, SIZE, DURATION Several experimental designs were used, including simple single-factor completely randomized designs, as well as a multi-factor response surface design. Randomization was performed at one or more levels for each experiment. Osmolality measurements were performed over 7 days, with up to 8 independent osmolality measurements performed per treatment group over that time. For the multi-factor study, 107 independent combinations of factor levels were assessed to develop the mathematical model. PARTICIPANTS/MATERIALS, SETTING, METHODS This study was conducted in a research laboratory setting. Commercially available embryo culture medium and oil was used. A MINC incubator without water for humidification was used for the incubation. Osmolality was measured with a vapor pressure osmometer after calibration. Viscometry and density were conducted using a rheometer, and volumetric flasks with an analytical balance, respectively. Data analyses were conducted with several commercially available software programs. MAIN RESULTS AND THE ROLE OF CHANCE Preliminary experiments showed that the surface area-to-volume ratio of the culture medium, oil density, and oil thickness above the medium all contributed significantly (P < 0.05) to the rise in osmolality. A multi-factor experiment showed that a combination of these variables, in the form of a truncated cubic polynomial, was able to predict the rise in osmolality, with these three variables interacting in the model (P < 0.05). Repeatability, as measured by the response of identical treatments performed independently, was high, with osmolality values being ± 2 of the average in most instances. In the final mathematical model, the terms of the equation were significant predictors of the outcome, with all P-values being significant, and only one P-value > 0.0001. LIMITATIONS, REASONS FOR CAUTION Although the range of values for the variables were selected to encompass values that are expected to be encountered in usual embryo culture conditions, variables outside of the range used may not result in accurate model predictions. Although the use of a single incubator type and medium type is not expected to affect the conclusions, that remains an uncertainty. WIDER IMPLICATIONS OF THE FINDINGS Using this predictive model will help to determine if one should be cautious in using a specific system and will provide guidance on how a system may be modified to provide improved stability during embryo culture. STUDY FUNDING/COMPETING INTEREST(S) This study was funded by Cook Medical. The author is a Team Lead and Senior Scientist at Cook Medical. The author has no other conflicts of interest to declare TRIAL REGISTRATION NUMBER N/A.
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Zhi, Pengpeng, Yonghua Li, Bingzhi Chen, Meng Li, and Guannan Liu. "Fuzzy optimization design-based multi-level response surface of bogie frame." International Journal of Structural Integrity 10, no. 2 (April 8, 2019): 134–48. http://dx.doi.org/10.1108/ijsi-10-2018-0062.
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Purpose In a structural optimization design-based single-level response surface, the number of optimal variables is too much, which not only increases the number of experiment times, but also reduces the fitting accuracy of the response surface. In addition, the uncertainty of the optimal variables and their boundary conditions makes the optimal solution difficult to obtain. The purpose of this paper is to propose a method of fuzzy optimization design-based multi-level response surface to deal with the problem. Design/methodology/approach The main optimal variables are determined by Monte Carlo simulation, and are classified into four levels according to their sensitivity. The linear membership function and the optimal level cut set method are applied to deal with the uncertainties of optimal variables and their boundary conditions, as well as the non-fuzzy processing is carried out. Based on this, the response surface function of the first-level design variables is established based on the design of experiments. A combinatorial optimization algorithm is developed to compute the optimal solution of the response surface function and bring the optimal solution into the calculation of the next level response surface, and so on. The objective value of the fourth-level response surface is an optimal solution under the optimal design variables combination. Findings The results show that the proposed method is superior to the traditional method in computational efficiency and accuracy, and improves 50.7 and 5.3 percent, respectively. Originality/value Most of the previous work on optimization was based on single-level response surface and single optimization algorithm, without considering the uncertainty of design variables. There are very few studies which discuss the optimization efficiency and accuracy of multiple design variables. This research illustrates the importance of uncertainty factors and hierarchical surrogate models for multi-variable optimization design.
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Wang, Jun-Bo, Yu Wang, Lei Wang, and Shu-Guo Liang. "Study on the Peak Factor of the Wind-Induced Response of Super-High-Rise Buildings." Atmosphere 14, no. 2 (February 15, 2023): 379. http://dx.doi.org/10.3390/atmos14020379.
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The wind-induced responses of tall buildings are stochastic processes, and the peak factor is an important parameter to evaluate the extreme value of the wind-induced response in wind-resistant design. The existing research on the peak factor mainly focuses on the wind pressure on the building surface, but rarely concerns the wind-induced response peak factor of the structures. In view of this, the peak factor of the wind-induced response of super-high-rise buildings was studied in this paper. Firstly, a series of wind tunnel tests of the multi-degree-of-freedom aero-elastic models (MDOF) were carried out, wherein the along-wind and cross-wind responses were measured. Thereafter, the peak factor of wind-induced response was calculated using the peak factor method, classical extreme value theory, and the improved peak factor method. It was found that the peak factor calculated by the improved peak factor method is in good agreement with classical extreme value theory, which indicates that the improved peak factor method is applicable to calculate the peak factor of the wind-induced response of high-rise buildings. The results calculated using the improved peak factor method show that the peak factor of cross-wind response varies significantly with the wind speed, varying from about 2.5 to 5.5. The peak factor of cross-wind response first increases and then decreases with the increase in the wind speed, reaches the minimum near the critical wind speed of vortex-induced vibration (VIV), and increases again when the wind speed is larger than the VIV wind speed. Finally, an empirical formula for the cross-wind response peak factor was proposed as a function of the reduced wind speed, aspect ratio, and damping ratio of the structure.
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Cromwell, Evan, Ori Hoxha, Matthew Hammer, and Oksana Sirenko. "Multi-parametric Human Cell-Based Inflammation Assay for Cytokines and Cell Surface Antigens." Journal of Immunology 200, no. 1_Supplement (May 1, 2018): 42.15. http://dx.doi.org/10.4049/jimmunol.200.supp.42.15.
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Abstract Inflammation is a complex event in which cells respond to various endogenous and exogenous stimuli. Factors such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and interferon (IFN)-γ activate signaling pathways leading to the expression of cytokines and cell-surface antigens. The ability to monitor up-regulation of these molecules provides an important physiological read-out for cell-based models of inflammation. We present results from a multiparametric cell-based assay that uses immunoassays for secreted cytokines and fluorescence read-outs of cell surface markers to evaluate the effect of different mediators on inflammatory response. Primary human umbilical vein endothelial cells (HUVEC) were stimulated with inflammation cytokines (TNF-α, IFN-γ, and IL-1β) for 20 hours. Then, a newly developed microfluidic-based assay system, PuMA, was used to quantify amount of MCP-1, IL-8, and IL-6 in cell supernatants. Expression of adhesion molecules VCAM and HLADR was quantified by measurement of total fluorescence intensity after staining cells with directly conjugated antibodies using an ImageXpress Nano Automated Imaging System. Concentration dependent inhibition of the inflammation responses by the compounds AG126 and MG132 were measured. Clear differences in cytokine expression were seen between the compounds consistent with their reported mechanisms of action. The combination of imaging and microfluidic-based assays provides an efficient multiparametric assay system that can be used to test the efficacy of anti-inflammatory compounds versus toxicity and also provide significant insight into the mechanism of action by selective inhibition of markers triggered by different signaling pathways.
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Bharti, Pushpendra S., S. Maheshwari, and C. Sharma. "Multi-Objective Optimization of Die-Sinking Electric Discharge Machining." Applied Mechanics and Materials 110-116 (October 2011): 1817–24. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.1817.
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— Parametric optimization of electric discharge machining (EDM) is a challenging task. Many researchers have employed different multi-objective optimization techniques for the same. This work employs multi-response signal-to-noise (MRSN) technique to find the optimum factor/level combination of input parameters. Experiments have been conducted on die-sinking EDM by taking heat treated D2 steel as work piece and copper as tool electrode. Experiments have been designed as per Taguchi’s L36 orthogonal array. Two cases v.i.z. high cutting efficiency and high surface finish have been taken. Analysis of variance (ANOVA) is employed to indicate the level of significance of machining parameters in both the cases. Finally, results have been verified experimentally and a significant improvement in material removal rate and surface roughness is observed.
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Ali, Raneen, Mozammel Mia, Aqib Khan, Wenliang Chen, Munish Gupta, and Catalin Pruncu. "Multi-Response Optimization of Face Milling Performance Considering Tool Path Strategies in Machining of Al-2024." Materials 12, no. 7 (March 27, 2019): 1013. http://dx.doi.org/10.3390/ma12071013.
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It is hypothesized that the orientation of tool maneuvering in the milling process defines the quality of machining. In that respect, here, the influence of different path strategies of the tool in face milling is investigated, and subsequently, the best strategy is identified following systematic optimization. The surface roughness, material removal rate and cutting time are considered as key responses, whereas the cutting speed, feed rate and depth of cut were considered as inputs (quantitative factors) beside the tool path strategy (qualitative factor) for the material Al 2024 with a torus end mill. The experimental plan, i.e., 27 runs were determined by using the Taguchi design approach. In addition, the analysis of variance is conducted to statistically identify the effects of parameters. The optimal values of process parameters have been evaluated based on Taguchi-grey relational analysis, and the reliability of this analysis has been verified with the confirmation test. It was found that the tool path strategy has a significant influence on the end outcomes of face milling. As such, the surface topography respective to different cutter path strategies and the optimal cutting strategy is discussed in detail.
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Gugulothu, Srinu, and Vamsi Krishna Pasam. "Optimizing Multi-Response Parameters in Turning of AISI1040 Steel Using Desirability Approach." International Journal of Mathematical, Engineering and Management Sciences 4, no. 4 (August 1, 2019): 905–21. http://dx.doi.org/10.33889/ijmems.2019.4.4-072.
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In this study, an attempt is made to examine the machining response parameters in turning of AISI 1040 steel under different lubrication environment. Subsequently, design of experiment technique Response surface methodology (RSM) is used for analyzing machining performance by varying cutting conditions with the use of 2wt% of CNT/MoS2(1:2) HNCF. Regression models are developed for multiple machining responses. Optimization is performed for these models by using desirability function, which converts multi-objective into single objective. Then the optimal setting parameters for single objective is found. Significant reduction in main cutting force (Fz), cutting temperature (T), surface roughness(Ra) and tool flank wear (Vb) are found with the use of 2wt% of CNT/MoS2(1:2) HNCF compared to other lubrication environment. Significant factors that affect the main cutting force (Fz), the temperature in the cutting zone are cutting speed, feed rate and depth of cut. Parameter depth of cut has an insignificant effect on tool flank wear and surface roughness (Ra). The optimal cutting conditions for four multi-objective optimization of main cutting force (Fz), cutting temperature, surface roughness (Ra) and tool flank wear are found to be cutting speed 70.25 m/min, feed 0.13 mm/rev and doc 0.5mm at desirability value of 0.907.
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Shunmugesh, K., and K. Panneerselvam. "Optimization of Machining Process Parameters in Drilling of CFRP Using Multi-Objective Taguchi Technique, TOPSIS and RSA Techniques." Polymers and Polymer Composites 25, no. 3 (March 2017): 185–92. http://dx.doi.org/10.1177/096739111702500301.
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Carbon Fiber Reinforced Polymer (CFRP) are widely used in many engineering applications as replacement for various other elements to make use of the advantage of its high strength-weight ratio, durability and high corrosion resistance. The paper herein is an attempt to evaluate the drilling characteristics of CFRP by means of three different drill bit types (HSS, TiAlN and TiN) using Taguchi L27 (313) orthogonal array under dry condition. Firstly, the machining process parameters (cutting speed and feed rate) are optimized with multiple performance characteristics using Multi-objective Taguchi technique and TOPSIS. Secondly, mathematical model is developed to correlate the machining process parameters and the performance characteristics (surface roughness, circularity and cylindricity) using response surface analysis. ANOVA is used to validate the developed mathematical model of the responses. The investigation reveals that the results of TOPSIS technique are in good agreement with the multi-objective Taguchi technique and also feed rate is the most predominant factor which affects the responses.
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Wang, Chun Neng, and Xi Ying Fan. "Status Analysis of Quality Prediction for Automotive Injection Molded Parts." Advanced Materials Research 998-999 (July 2014): 534–37. http://dx.doi.org/10.4028/www.scientific.net/amr.998-999.534.
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Injection molding is a very complex multi-factor coupling effect and a nonlinear dynamic process. Therefore, under the influence of nonlinear and multi-factor, injection molding goal is to effectively predict and guarantee the quality of injection molded parts. In this paper, the common methods used to predict the quality of injection molded parts are introduced, including: Taguchi method, artificial neural network, response surface method, radial basis function method and Kriging model method. Research progresses as well as application examples of forecasting methods at home and abroad is summarized. Besides, the development trend of the injection molding quality prediction is discussed.
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Ghattas, Badih, and Diane Manzon. "Machine Learning Alternatives to Response Surface Models." Mathematics 11, no. 15 (August 4, 2023): 3406. http://dx.doi.org/10.3390/math11153406.
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In the Design of Experiments, we seek to relate response variables to explanatory factors. Response Surface methodology (RSM) approximates the relation between output variables and a polynomial transform of the explanatory variables using a linear model. Some researchers have tried to adjust other types of models, mainly nonlinear and nonparametric. We present a large panel of Machine Learning approaches that may be good alternatives to the classical RSM approximation. The state of the art of such approaches is given, including classification and regression trees, ensemble methods, support vector machines, neural networks and also direct multi-output approaches. We survey the subject and illustrate the use of ten such approaches using simulations and a real use case. In our simulations, the underlying model is linear in the explanatory factors for one response and nonlinear for the others. We focus on the advantages and disadvantages of the different approaches and show how their hyperparameters may be tuned. Our simulations show that even when the underlying relation between the response and the explanatory variables is linear, the RSM approach is outperformed by the direct neural network multivariate model, for any sample size (<50) and much more for very small samples (15 or 20). When the underlying relation is nonlinear, the RSM approach is outperformed by most of the machine learning approaches for small samples (n ≤ 30).
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Awode, E. I., S. A. Lawal, K. A. Olaiya, and J. Abutu. "Characterization of eco-friendly cutting fluid developed from neem seed oil." Nigerian Journal of Technology 41, no. 4 (November 3, 2022): 700–711. http://dx.doi.org/10.4314/njt.v41i4.8.
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Cutting fluid is a key component in retaining workpiece quality, tool life and overall high productivity in machine operations. It is needed as input for minimal surface roughness, minimal tool wear and better machining finished product. This study addressed tool wear and surface roughness by evaluating optimal factor effectiveness of the surface roughness and tool wear during turning of AISI 304 alloy steel using an environmentally friendly fluid. The non-biodegradable and non-recyclable nature of conventional cutting fluids as mineral oils have raised serious concerns with the research community and prompted the renewal of research in this area with focus on replacing the mineral based cutting fluids with environmentally friendly cutting fluids such as neem seed prepared cutting fluid (N-PCF). The neem seed oil (NSO) was sourced locally and characterized by investigating the physiochemical properties as well as it’s fatty acid composition (FAC). The cutting fluid formulation was 1:9 of oil to water in the ratio. The cutting fluids which aided surface roughness and tool wear reduction during turning of the austenitic stainless steel AISI 304 and improved the carbide insert tool was evaluated and compared with mineral oil-based cutting fluid. Also, the response surface method (RSM) of experimental design and Grey relational analysis (GRA) multi-response optimization were employed respectively. The experimental results revealed that the formulated oil showed 8.67 pH value, 0.50 mm2/s viscosity, resistant to corrosion, stable and deep yellowish colouration. The multi-response optimal factor combination obtained from GRA showed multi-response effect of the formulated Neem seed prepared cutting fluid at feed rate of 0.82 mm/rev, depth of cut of 0.65 mm and cutting velocity of 800 rev/min while that of Mineral prepared cutting fluid (M-PCF) was achieved with feed rate (0.82 mm/rev), depth of cut (0.65 mm) and cutting velocity (500 rev/min). GRA and RSM results showed acceptable parameters that contribute to the science of machining and this is in good agreement when compared with those obtained from other cutting fluids used for turning operation.
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Lin, Chendi, Xingyan Cao, Zhirong Wang, Jianshu Wei, and Jianjun Xu. "Research on quenching performance and multi-factor influence law of hydrogen crimped-ribbon flame arrester using response surface methodology." Fuel 326 (October 2022): 124911. http://dx.doi.org/10.1016/j.fuel.2022.124911.
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Zhai, Mingyang, Dongying Wang, Zilin Zhang, Liaoyuan Zhang, Feng Yang, Bo Huang, Anhai Zhong, and Lianchong Li. "Numerical simulation and multi-factor optimization of hydraulic fracturing in deep naturally fractured sandstones based on response surface method." Engineering Fracture Mechanics 259 (January 2022): 108110. http://dx.doi.org/10.1016/j.engfracmech.2021.108110.
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Tasca, Andrea Luca, Gemma Mannarino, Riccardo Gori, Sandra Vitolo, and Monica Puccini. "Phosphorus recovery from sewage sludge hydrochar: process optimization by response surface methodology." Water Science and Technology 82, no. 11 (October 9, 2020): 2331–43. http://dx.doi.org/10.2166/wst.2020.485.
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Abstract Hydrothermal carbonization can play an innovative role in sewage sludge (SS) treatment and valorization, as well as in phosphorus recovery. In this study, leaching tests using nitric acid were performed on hydrochar from SS and the influence of pH (1–3.5), leaching time (30–240 min), and solid/liquid (S/L) ratio (5–20 wt%) was analyzed and optimized according to the Design of Experiments method, under the Response Surface Methodology approach. The highest phosphorus extraction yield (59.57%) was achieved at the lowest pH and the lowest S/L ratio, while an increase in temperature from 20 to 60 °C negatively affected the phosphorus recovery. Quadratic models, with the addition of semi-cubic terms, were found to best represent both phosphorus yield and ash content of the hydrochar after leaching. As observed by 3-dimensional surface responses, phosphorus yield increases as the pH decreases. The pH is the factor that most influences this response, while time has little influence. At pH 1, the yield increases as the S/L ratio decreases, while the S/L ratio only slightly affects the response at pH 3.5. At an S/L ratio of 12.5%, multi-objective optimization indicates that pH 1 and a leaching time of 135 min are the parameters that allow both maximum phosphorus yield and minimum ash content.