Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : ANOVA

Prediction of Surface Roughness of Mild Steel Alloy in CNC Milling Process Using ANN and GA Technique

Hind H. Abdulridha

Engineering and Technology Journal, 2020, Volume 38, Issue 12, Pages 1842-1851
DOI: 10.30684/etj.v38i12A.1579

In this paper, Analysis Of Variance (ANOVA), Artificial Neural Network (ANN), and Genetic Algorithm (GA) have been studied to predict the effect of milling parameters on the Surface Roughness (Ra) during machining of mild steel alloy. The milling experiments carried out based on the Taguchi design of experiments method using (L16) orthogonal array with 3 factors and 4 levels. The influence of three independent variables such as spindle speed (910, 930, 960, and 1000 rpm), feed rate (93, 95, 98, and 102 mm/min), and Tool Diameter (8, 10, 12, and 14 mm) on the Surface Roughness (Ra) were tested and analyzed with (ANOVA) to predict the response which indicates that spindle speed was the most significant factor effecting on Surface Roughness (Ra). Artificial Neural Network (ANN) and numerical methods are used widely for modeling and predict the performance of manufacturing technologies. Neural Network technique with 2 hidden layers, 10 neurons size, 1000 epochs, and Trainlm transfer function is used to predict the result. The Genetic Algorithm (GA) has been utilized to find optimal cutting conditions during a milling process.
From the results, the optimal value of spindle speed is (930 rpm), feed-rate is (95 mm/min) and tool diameter is (8 mm). This network structure is capable of predicting the Surface Roughness (Ra) well to optimize the milling parameters. Artificial Neural Network (ANN) predicted results indicate good agreement between the experimental and the predicted values

The Effects of Process Parameters on Residual Stresses in Single Point Incremental Forming of A1050 Aluminum Using ANOVA Model

M. Kamal; S. Mohammed; A.S. Bedan

Engineering and Technology Journal, 2017, Volume 35, Issue 1, Pages 41-48

Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms and by this way the sheet with pure deformation stretching. The aim of the present work is to inspect, experimentally, the state of the residual stresses induced in SPIF parts made by A1050 aluminum. The forming surface was measured at four different angles using a ORIONRKS 6000 test (the X-ray diffraction technology was used to detect the residual stress) measuring instrument with the angles (0o, 15o, 30o and 45o) and the average residual stress value is recorded in (MPa), the residual stress in original blanks is (-6.29MPa). This specialized stress analysis system using the side-inclination method includes stress analysis software, the stress analysis sample stand and X-ray tube. A comparison study is made for tabulated values and experimental values for residual stress by using ANOVA model with the contribution of rotational speed, feed rate and forming depth with respect to residual stress is (63.7, 4.3 and 32)% respectively..

Investigation of Material Removal Rate and Surface Roughness for AISI 1015 Steel Rack Gear in Wire EDM Process

Mostafa Adel Abdullah; Safaa Kadhim Ghazi; Mustafa Mohamed

Engineering and Technology Journal, 2016, Volume 34, Issue 12, Pages 2361-2370

In this work an investigation of the effects of various process parameters of Wire-EDM like Servo Feed (SF), pulse off-time (TOFF), pulse on-time (TON), as inputs impact on surface roughness (Ra) and metal removal rate (MRR) as outputs on steel (AISI 1015) utilizing nine specimens. With servo feed (500, 600 and 700)mm/min, pulse-of time (10,30,50) μsec, pulse on-time (20,25,30) μsec.The characteristics of cutting variables were determined by implementing Taguchi experimental design method. The importance level of the cutting variables for metal removal rate and surface roughnessis determined by implementing the analysis of variance (ANOVA).

Fuzzy-TOPSIS Model for Optimization Hot Corrosion Resistance of Inconel718 Coated by Yttrium-doped Aluminizing-Siliconizing Process

Abbas Khammas Hussein; MajidHameedAbdulmajeed; HashimShareefNeamah

Engineering and Technology Journal, 2016, Volume 34, Issue 8, Pages 1564-1574

The objective of this study is to find out the optimum hot corrosion resistance and hardness for Inconel718 coated by simultaneous yttrium-doped aluminizing-siliconizingprocess. The hot corrosion parameters selected for the experiments are Na2SO4, NaCl, and V2O5. The optimization is carried out by choosing three input parameters at two levels. Multi objective optimization technique, TOPSIS optimization approach is used for maximizing the hot corrosion resistance (minimizing hot corrosion rate Kp),and hardness. ANOVA is performed to investigate the more influencing parameters on the multiple performance characteristics. It also helps to calculate percentage contribution of each parameter. Finally, accuracy of optimization was confirmed by conducting confirmations. Results indicate feasibility of TOPSIS analysis in continuous improvement in hot corrosion resistance.

Modelling of Carburization Parameters Process for Low Carbon Steel

Abbas Khammas Hussein; Laith Kais Abbas; Jamal Jalal Dawood; Nadeen Jaafar Ismae

Engineering and Technology Journal, 2016, Volume 34, Issue 6, Pages 1069-1079

This paper representsthe carburization parameters for steel (1020) using Desirability Function Analysis-DFA. The experiments were conducted using Taguchi (L9) orthogonal array. Carburization parameters such as carburization temperature, carburization time and tempering temperature were optimized by multi - response considerations depending onmicrohardnessand were rate measurements. The optimal carburizing parameters had been determined by composite desirability value obtained from desirability function analysis while significant contribution of parameter was determined by analysis of variance (ANOVA). The analyses results showed that optimal combination for higher hardness and lower wear rate were at (A2=920 oC, B2= 3 hours and C3=120 oC). Confirmation test was also conducted to validate the test results. Mathematical models for composite desirability, microhardness and rate wear were determined. Experimental results showed that the carburization performance can be improved effectively through desirability approach.

Effect of Powder Concentration in PMEDM on Machining Performance for Different Die steel Types

Maan Aabid Tawfiq; Azzam Sabah Hameed

Engineering and Technology Journal, 2015, Volume 33, Issue 9, Pages 2174-2186

Electric discharge machining(EDM) is one of the nonconventional machining process which has been used in manufacturing complex shapes on hard material that are difficult to cut by conventional processes, especially, die casting, parts of aircraft, medical equipment, automobile industries. Powder mixed electric discharge machining(PMEDM), has emerged as one of the advanced techniques in the direction of the enhancement of the capabilities of EDM. The objective of the present research is to study the influence of process parameters such as peak current, pulse on time, manganese,aluminum, and aluminum-manganese mixing powder concentration on machining performance of different types of die steel (AISID3,AISID6,H13)with round copper electrode(20 mm diameter) on machining performance. Experiments have been designed using Taguchi method. Taguchi L27 orthogonal array has been selected for five factors 3 levels design. The machining performance has evaluated in terms of metal removal rate (MRR).It is found that manganese powder concentration mixed in dielectric fluid significantly affect the machining performance, maximum (MRR) is obtained at a high peak current(12 A), pulse on(200µs), and (4g/L) concentration of manganese powder,the optimum MRR is 17.56mm3/min with percent of error about 5.61% compared with the Experimental value.

Study the Effect of the Graphite Powder Mixing Electrical Discharge Machining on Creation of Surface Residual Stresses for AISI D2 Die Steel Using Design of Experiments

Ahmed Naif Al-Khazraji; Samir Ali Amin; Saad Mahmood Ali

Engineering and Technology Journal, 2015, Volume 33, Issue 6, Pages 1399-1415

This paperattempted to study the induced surface residual stressesduethe effect of Electrical discharge machining (EDM) input parameters, (the pulse current,the pulse-on time and the type of electrode).The work includedthe use of two types of electrode, the copper and graphite as well as using or without using the graphite powder mixing with the kerosene dielectric (PMEDM) for machining AISI D2 dies steel. The response surface methodology (RSM) was usedfor design the experimental work matrices. The analysis of variance (ANOVA) was used, and models were builtto predict the surface residual stresses.The obtained results showed that the minimum tensile surface residual stresses obtained when using the copper electrodeswith pulse current (22 A) and pulse on duration (40 µs) when working with kerosene dielectric alone and (8 A) with (120 µs) when working with graphite powder mixing. The results concluded that the using of graphite electrodes and kerosene dielectric alone or with powder mixing induced minimum residual stresses with pulse current (22 A) and pulse on duration (120 µs). The copper elec-trodes with kerosene dielectric and graphite powder mixing improved the induced tensile residual stresses by about (80 %) lower than when using kerosene dielectric alone and about (50%) lower than with graphite electrodes and the kerosene dielectric alone or with graphite mixing powder.

Prediction of Bead Width In Submerged ArcWelding of Low Carbon Steel (AISI 1005)

Husham Jawad Kadhim; Ahmed Ali Akbar Akbar

Engineering and Technology Journal, 2015, Volume 33, Issue 2, Pages 451-462

This paper used Taguchi technique to determine the optimal SAW parameters, an effort has been made to study the effect of SAW process parameters (current I, voltage V, speed S) on the weld bead width (W) of low carbon steel AISI 1005. S/N ratios are computed to determine the optimum parameters. Statistical model was checked by used multiply regression method; the adequacy and significance of the model were checked by using ANOVA technique. The model employed easily in form of executed program designed by using visual basic 6 software, the objective of designed program is to predict and control weld bead width, which enable to put in the desired weld parameters and select the weld bead width. Main and Interaction effects of the process parameters on bead width were presented graphically. The experimental results were analyzed by using Minitab 16 software.

Influence of some Relevant Process Parameters on The Surface Roughness of Surfaces Produced by ISMF Proce

Wisam K. Hamdan; Jamal H. Mohamed; Nareen Hafudh Obaeed

Engineering and Technology Journal, 2014, Volume 32, Issue 8, Pages 1942-1957

Incremental Sheet Metal Forming (ISMF) is a novel sheet metal forming technology where the deformation of the thin sheet metal blank occurs locally and progressively by using the CNC milling machine which control the movement of a simple forming tool. The surface quality is of vital importance in any manufacturing process. Therefore, the present study is focused on the surface quality of parts formed by single point incremental forming (SPIF) process. Consequently, the objective of this study is to investigate the effect of five forming parameters (number of forming stages, feed rate type, tool overlapping, rotational speed, and state of initial blank) on the dimensional accuracy and surface roughness of parts. Each control factor is studied based on two levels (low level and high level). To study the effects of these control factors, a D-optimal Design of Experiment is used to develop the experimental plan and analyze data. The ANOVA results show that the tool overlapping and the number of forming stages are the most important factors affecting the surface roughness. These two factors are proportional to the surface roughness. The maximum and minimum surface roughness, which is achieved from all the 16 experiments is (Ra = 4.06 & Ra = 2.04 µm) respectively. The qualitative assessment reveals that the surface roughness decreases radialy as the tool moves towards the center of the blank.

Studying the Parameters of EDM Based Micro- Cutting Holes Using ANOVA

Shukry H. Aghdeab; Laith A. Mohammed

Engineering and Technology Journal, 2013, Volume 31, Issue 15, Pages 2876-2884

Micro -EDM is one of an important method in machining holes which is used in wide
applications to fabricate medical devices and small dies. This work study the process of
producing micro holes for copper alloy workpieces using, stainless steel electrode
and dielectric solution (tap water), using DC current and low voltage (70V) to cut
(0.7mm) thickness of copper (Cu) alloy workpieces in order to obtain the micro holes.
This work included an experimental work for electrical discharge machining
(EDM) to produce micro holes with different diameters (400, 300, 210, 200, 120,
100, 85, 75, 70) μm.
The objective of this work is to obtain an optimal setting of EDM parameters to
produce micro holes in copper alloy to achieve the optimal values of required holes
A regression model has been developed to represent this process. An approach
has been made to optimize the process parameters (current, gap distance, machining
time) using ANOVA analysis. This analysis was performed to obtain the most
significant factors influencing the production of micro holes.

Optimization of Cyclic Oxidation Parameters in Steel-T21 for Aluminization Coating Using Taguchi-ANOVA analysis by MINITAB13

Abbas Khammas Hussein

Engineering and Technology Journal, 2009, Volume 27, Issue 12, Pages 2367-2384

The increasing demands for high quality coatings has made it inevitable that
the surface coating industry would put more effort into precisely controlling the
coating process relative to media for which is subjected. Statistical design of
experiments is an effective method for finding the optimum cyclic oxidation
parameters for aluminization coating. In the present investigation, an attempt is made
to produce high-quality aluminization coating by optimizing the cyclic oxidation
parameters following a (L9-33) Taguchi-design approach. (L9-33) Taguchi orthogonal
array has been used to determine the signal to noise ratio (S/N). The oxidation
parameters that were varied include the Temperature (600,700,800oC), Time
(15,20,25hr at 5hr cycle) and Media (Air,CO2,H2O). The coating characteristics were
qualitified with respect to parabolic oxidation rate constant (KP). The performance of
the coating was qualitatively evaluated using cyclic oxidation testing. Analysis of the
experiments using Taguchi method indicated that 800oC,25hr and CO2 media are to be
the optimum cyclic oxidation conditions for pack aluminization. The contribution of
each of these parameters to the parabolic oxidation rate constant (KP) was determined
employing an analysis of variance (ANOVA) and the effect of the level of each
parameter was determined using Taguchi analysis. ANOVA results show that
temperature and media are the parameters that most significantly affect the parabolic
oxidation rate constant (KP) compared to time.