hiba khalid hussein

@uobaghdad.edu.iq

Assistant Professor, AL-Khwarizmi College of Engineering
Department of Automated Manufacturing Engineering / Al- Khwarizmi College of Engineering/ University of Baghdad

hiba khalid hussein


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https://researchid.co/hibakhalid

RESEARCH, TEACHING, or OTHER INTERESTS

Industrial and Manufacturing Engineering, Mechanical Engineering, Mechanical Engineering, Mechanics of Materials
12

Scopus Publications

126

Scholar Citations

7

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Investigation the thermal effects on tensile strength in welding of carbon steel sheets
    Salah Sabeeh Abed Al Kareem, Hiba K. Hussein, Osamah Fadhil Abdulateef
    Aip Conference Proceedings, 2026
  • The Influence of Cutting Parameters on the Surface Hardness in Turning of 6061 Aluminum Alloy
    Basma L. Mahdi, Abduljabar H. Ali, Hiba K. Hussein, Osamah F. Abdulateef
    Engineering Technology and Applied Science Research, 2024
    The primary design property necessary to ensure the longevity and durability of manufactured materials is the material hardness. The primary objective of this study was to investigate the effect of cutting parameters, namely feed rate, cutting speed, and depth of cut, on the surface hardness generated during the turning process of aluminum alloy 6061. The turning experiments were conducted using a Taguchi L27 orthogonal array arranged for three-level cutting parameters. The Analysis of Variance (ANOVA) was employed to determine the relative importance of each parameter on surface hardness. Additionally, an Artificial Nural Network (ANN) predictive model using the back-propagation learning algorithm was created to predict surface hardness levels at each level of the cutting parameters. The results revealed that increasing the values of all the turning parameters resulted in an increase in hardness, and it was concluded that the feed rate was the most critical factor (53.41%) in achieving high surface hardness, followed by the depth of cut (27.89%), whereas cutting speed had a lower impact (18.7%). This study also suggests a simple equation for estimating the surface hardness from the cutting parameters. The ANN model could accurately estimate the surface hardness with a coefficient of correlation (R) higher than 0.98 between the predicted and experimental values. The predicted values of hardness by ANN were more precise (R2 =0.973839) than those predicted by ANOVA (R2=0.893).
  • Enhancing Risk Management: Leveraging the Likelihood/Severity Matrix for Effective Risk Assessment and Mitigation in the Electrical and Electronic Sector
    Alaa Salahuddin Araibi, Huda H. Dalef, Hiba K. Hussein, Mohamad Shaiful Ashrul Ishak, Muhammad Roslan Rahim
    Al Khwarizmi Engineering Journal, 2024
    This paper presents the basic concept of risk and reviews commonly applied tools and techniques for risk assessment. Generally, risk assessment is a completely experiential decision-making process based on experience and knowledge of risk assistants. This paper emphasises one quantitative/qualitative technique, namely the likelihood/severity matrix approach, which aims to direct the organisation’s attention towards risks that have the highest potential to have a negative effect. This paper’s main contribution lies in introducing a proposed model that utilises the likelihood/severity matrix approach to categorise risks into ‘regions’ and subsequently rank them. This process supports risk managers in making informed decisions to reduce risks effectively. A likelihood/severity matrix was examined through a case study belonging to the electrical and electronic sector to find the critical risks that hinder the assembly line of personal computers. Results showed that the ‘Breaking parts during assembly’, ‘Shocking the components from static electricity discharge’ and ‘Using wrong compatible parts’ risks had the maximum risk score, with values of 10–15 as the most critical risks. These results can influence decision makers in developing actions to mitigate these highlighted risks.
  • Priority study of welding parameters affecting the rate of molten metal precipitation and hardness
    Salah Sabeeh Abed Al Kareem, Hiba K. Hussein, Faiz F. Mustafa
    Aip Conference Proceedings, 2024
  • Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process
    Israa R. Shareef, Hiba K. Hussein, Basma L. Mahdi
    Advances in Science and Technology Research Journal, 2023
    Recently, titanium and its alloys have been widely used in industry. Titanium alloys are difficult to machine due to high tool wear, cutting temperature, and edge formation. Thus, this analysis predicts how machining parameters, particularly drilling parameters, affect titanium work piece integrity. This study used Taguchi and fuzzy control software to calculate the effects of cutting parameters and drill tip angle on surface roughness maximal temperature in titanium alloy workpieces during dry drilling. Three 10 mm cutting tools have 106°, 118°, and 130° tip angles. Cutting tools are made of high-speed steel. The work piece model is a parallelogram with 100 mm width, 150 mm length, and 30 mm thickness. Cutting settings include three spindle speeds 500, 1000, and 1500 rpm with 0.1, 0.2, and 0.3 mm/rev feed rates. All simulations have the same hole depth (4 mm). We also estimated and discussed the rate of temperature change due to cutting settings. This prediction is used to diagnose and improve drilling, increase tool life, and safeguard the work piece. This reduces titanium drilling costs and effort. The machining model’s work piece temperature is influenced by spindle speed and tool tip angle, but feed rate has no effect. Drill - ers can optimize drilling performance and obtain desired results including efficient penetration rates, shortened drilling time, and reduced equipment failure by regulating these parameters. Fuzzy Logic predicts drilling parameters on Titanium work pieces with encouraging results.
  • Impact of TIG Welding Parameters on the Mechanical Properties of 6061-T6 Aluminum Alloy Joints
    Salah Sabeeh Abed Al Kareem, Basma Luay Mahdi, Hiba K. Hussein
    Advances in Science and Technology Research Journal, 2023
    The most common gas-shielded arc welding method is tungsten inert gas welding, which uses shielding gas to isolate the welded area. Such technique is mostly used in the industrial domain, including steel framework fabrication and installation, plumbing systems, and other building jobs. The welding method and the implementation of a suitable welding joint based on some factors that contribute to the fusion process were studied in the present research. The research investigated the specifications and efficiency of the area to be welded in terms of the thermal effect on the welding joint shape and some significant mechanical property-related factors which that were deter - mined during the welding process. In this paper, aluminum alloy sheets, AA 6061-T6, with a thickness of 3 mm, were used with a 60mm width and 80mm length. These sheets were prepared to be welded using welding currents of 90A, 95A, and 100A, welding speeds of 60mm/min, 80 mm/min, and100 mm/min, and gas flow rates of 8 l/ min, 9 l/min, and 10 l/min. The experiments were designed at three distinct levels. These levels were selected to create the L9 orthogonal array. Regression analysis, signal-to-noise ratio evaluation, and analysis of variance were carried out. The created model has enhanced accuracy by predicting the reinforced hardness found in the weld specimens, according to the regression study, which showed R2= 90.09%. In addition, it was discovered that the ideal welding parameters for a welded specimen were 100 A for welding current, 80 mm/min for welding speed, and 9 l/min for gas flow. The present research examined the shape of the thermal distribution of welded parts us - ing the engineering computer program ANSYS. The experimental results clarified the proposed approach, as they showed that the welding current is the most influential factor in the hardness of the weld using the fusion process of 90.95%, followed by the welding speed of 7.48%, while the gas flow rate of 1.52% has the least effect. The authors recommend using qualified welders to ensure optimal performance. It is anticipated that these findings will serve as a foundation for analysis to optimize welding processes and reduce welding defects.
  • Comparative Prediction and Modelling of Surface Roughness in Milling of AL-7075 Using Regression Analysis and Neural Network
    Hiba K. Hussein, Israa R. Shareef, Iman A. Zayer
    Mathematical Modelling of Engineering Problems, 2022
    The surface roughness (Ra) of machine parts effects significantly the fatigue strength, corrosion resistance and aesthetic appeal of them. Therefore, Ra is an important parameter in manufacturing process. In this research, Ra of Aluminum Al-7075 in milling process is predicted and minimized. Ra minimization has to be in standard mathematical model formula. In order to predict minimum Ra value, developing a model is taken to deal with real Ra experimental data of the milling process. Two model approaches which are Regression and Artificial Neural Network (ANN) are proposed for minimum Ra value prediction. The studied process parameters were: speed of cut, feed rate and depth of cut. Regression and ANN were used to investigate the effect of these parameters on Ra through 27 cases of study, where full Analysis of Ra besides to determining regression equation and optimum process parameters are achieved. This study results show that each of Regression & ANN models had reduced minimum Ra in very similar value by 0.987. This similarity reflects the promise approach of this study in predicting Ra in AL-7075 milling, unlike previous studies that either the regression or the Artificial intelligence method was the dominant in results.
  • EXPERIMENTAL INVESTIGATION AND MODELLING OF RESIDUAL STRESSES IN FACE MILLING OF AL-6061-T3 USING NEURAL NETWORK
    Basma L. Mahdi, Huda H. Dalef, Hiba K. Hussein
    Eastern European Journal of Enterprise Technologies, 2022
    Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, but few of them provided the distribution of RS in a direct and singular way. This work focuses on studying and optimizing the effect of cutting speed, feed rate, and depth of cut for 6061-T3 aluminum alloy on the RS of the surface. The optimum values of geometry parameters have been found by using the L27 orthogonal array. Analysis and simulation of RS by using an artificial neural network (ANN) were carried out to predict the RS behavior due to changing machining process parameters. Using ANN to predict the behavior of RS due to changing machining process parameters is presented as a promising method. The milling process produces more RS at high cutting speed, roughly intermediate feed rate, and deeper cut, according to the results. The best residual stress obtained from ANN is ‒135.204 N/mm2 at a cutting depth of 5 mm, feed rate of 0.25 mm/rev and cutting speed of 1,000 rpm. ANN can be considered a powerful tool for estimating residual stress
  • Implementation of Artificial Neural Network to Achieve Speed Control and Power Saving of a Belt Conveyor System
    Israa R. Shareef, Hiba K. Hussein
    Eastern European Journal of Enterprise Technologies, 2021
    According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through the conveyor belt motion. An optimal speed controlling mechanism of the conveyor belt is presented by detecting smartly the parts' number and weights using the vision sensor, where the latter will give sufficient visualization about the system. Then image processing will deliver the important data to ANN, which will optimally decide the best conveyor belt speed. This decided speed will achieve the aim of power saving in belt motion. The proposed controlling system will optimally switch the speed of the conveyor belt system to ON, OFF and idle status in order to minimize the consumption of energy in the conveyor belt. As the conveyor belt is fully loaded it moves at its maximum speed. But if the conveyor is partially loaded, the speed will be adjusted accordingly by the ANN. If no loading existed, the conveyor will be stopped. By this way, a very significant energy amount in addition to cost will be saved. The developed conveyor belt system will modernize industrial manufacturing lines, besides reducing energy consumption and cost and increasing the conveyor belts lifetime
  • Development of Automated Liquid Filling System Based on the Interactive Design Approach
    Oday Abdullah, Wisam Abbood, Hiba Hussein
    Fme Transactions, 2020
    The automatic liquid filling system is used in different applications such as production of detergents, liquid soaps, fruit juices, milk products, bottled water, etc. The automatic bottle filling system is highly expensive. Where, the common filling systems required to complex changes in hardware and software in order to modify volume of liquid. There are many important variables in the filling process such as volume of liquid, the filling time, etc. This paper presents a new approach to develop an automatic liquid filling system. The new proposed system consists of a conveyor subsystem, filling stations, and camera to detect the level of the liquid at any instant during the filling process. The camera can detect accurately the level of liquid based on the imaging process technique (Edge Detection Approach). In order to achieve the aim of this work, Arduino board is used as the controller unit in the automatic operation of developed filling system. The developed automatic liquid filling system is designed to be not expensive compared to the other available filling systems on the markets. The system is also easy to operate and user-friendly,where only simple steps are required to operate the filling system or modify the working condition.It was found, based on results, that the Prewitt edge detection is the optimal method that should be applied to obtain high accuracy of results and quick response of developed system.
  • Industrial tracking camera and product vision detection system
    Wisam T. Abbood, Hiba K. Hussein, Oday I. Abdullah
    Journal of Mechanical Engineering Research and Developments, 2019
  • Prediction of spot welding parameters using fuzzy logic controlling
    Hiba Khalid Hussein, Israa Rafie Shareef, Iman Ahmed Zayer
    Eastern European Journal of Enterprise Technologies, 2019

RECENT SCHOLAR PUBLICATIONS

  • Investigation the thermal effects on tensile strength in welding of carbon steel sheets
    SSAA Kareem, HK Hussein, OF Abdulateef
    AIP Conference Proceedings 3379 (1), 020011 , 2026
    2026
  • The Influence of Cutting Parameters on the Surface Hardness in Turning of 6061 Aluminum Alloy
    BL Mahdi, AH Ali, HK Hussein, OF Abdulateef
    Engineering, Technology & Applied Science Research 14 (5), 17118-17124 , 2024
    2024
    Citations: 3
  • Enhancing risk management: Leveraging the likelihood/severity matrix for effective risk assessment and mitigation in the electrical and electronic sector
    AS Araibi, HH Dalef, HK Hussein, MSA Ishak, MR Rahim
    Al-Khwarizmi Engineering Journal 20 (3), 59-70 , 2024
    2024
    Citations: 7
  • Priority study of welding parameters affecting the rate of molten metal precipitation and hardness
    SSA Al Kareem, HK Hussein, FF Mustafa
    AIP Conference Proceedings 3105 (1), 020016 , 2024
    2024
    Citations: 1
  • Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process
    IR Shareef, HK Hussein, BL Mahdi
    Advances in Science and Technology. Research Journal 17 (6) , 2023
    2023
    Citations: 9
  • Impact of TIG welding parameters on the mechanical properties of 6061-T6 aluminum alloy joints
    SSAA Kareem, BL Mahdi, HK Hussein
    Advances in Science and Technology. Research Journal 17 (5) , 2023
    2023
    Citations: 6
  • Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
    B L Mahdi, HH Dalef, HK Hussein
    Eastern-European Journal of Enterprise Technologies 6 (1), 120 , 2022
    2022
    Citations: 3
  • Comparative Prediction and Modelling of Surface Roughness in Milling of AL-7075 Using Regression Analysis and Neural Network
    IAZ Hiba K. Hussein, Israa R. Shareef
    Mathematical Modelling of Engineering Problems 9 (1), 186-193 , 2022
    2022
    Citations: 4
  • Implementation of Artificial Neural Network to Achieve Speed Control and Power Saving of a Belt Conveyor System
    IR Shareef, HK Hussein
    Eastern-European Journal of Enterprise Technologies 2 (2), 44-53 , 2021
    2021
    Citations: 33
  • Experimental investigation and parametric optimization of FSW for the 2024-O aluminum alloy joints
    AM Takhakh, HK Hussein
    IOP Conference Series: Materials Science and Engineering 1094 (1), 012134 , 2021
    2021
    Citations: 8
  • Development of automated liquid filling system based on the interactive design approach
    OI Abdullah
    2020
    Citations: 33
  • Industrial tracking camera and product vision detection system
    WT Abbood, HK Hussein, OI Abdullah
    Journal of mechanical engineering research and developments 42 (4), 277-280 , 2019
    2019
    Citations: 10
  • Industrial Automated Robotic Vision System
    WT Abbood, HK Hussein
    LAP LAMBERT Academic Publishing , 2019
    2019
  • Prediction of spot welding parameters using fuzzy logic controlling
    HK Hussein, IR Shareef, IA Zayer
    Восточно-Европейский журнал передовых технологий, 49-56 , 2019
    2019
    Citations: 9

MOST CITED SCHOLAR PUBLICATIONS

  • Implementation of Artificial Neural Network to Achieve Speed Control and Power Saving of a Belt Conveyor System
    IR Shareef, HK Hussein
    Eastern-European Journal of Enterprise Technologies 2 (2), 44-53 , 2021
    2021
    Citations: 33
  • Development of automated liquid filling system based on the interactive design approach
    OI Abdullah
    2020
    Citations: 33
  • Industrial tracking camera and product vision detection system
    WT Abbood, HK Hussein, OI Abdullah
    Journal of mechanical engineering research and developments 42 (4), 277-280 , 2019
    2019
    Citations: 10
  • Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process
    IR Shareef, HK Hussein, BL Mahdi
    Advances in Science and Technology. Research Journal 17 (6) , 2023
    2023
    Citations: 9
  • Prediction of spot welding parameters using fuzzy logic controlling
    HK Hussein, IR Shareef, IA Zayer
    Восточно-Европейский журнал передовых технологий, 49-56 , 2019
    2019
    Citations: 9
  • Experimental investigation and parametric optimization of FSW for the 2024-O aluminum alloy joints
    AM Takhakh, HK Hussein
    IOP Conference Series: Materials Science and Engineering 1094 (1), 012134 , 2021
    2021
    Citations: 8
  • Enhancing risk management: Leveraging the likelihood/severity matrix for effective risk assessment and mitigation in the electrical and electronic sector
    AS Araibi, HH Dalef, HK Hussein, MSA Ishak, MR Rahim
    Al-Khwarizmi Engineering Journal 20 (3), 59-70 , 2024
    2024
    Citations: 7
  • Impact of TIG welding parameters on the mechanical properties of 6061-T6 aluminum alloy joints
    SSAA Kareem, BL Mahdi, HK Hussein
    Advances in Science and Technology. Research Journal 17 (5) , 2023
    2023
    Citations: 6
  • Comparative Prediction and Modelling of Surface Roughness in Milling of AL-7075 Using Regression Analysis and Neural Network
    IAZ Hiba K. Hussein, Israa R. Shareef
    Mathematical Modelling of Engineering Problems 9 (1), 186-193 , 2022
    2022
    Citations: 4
  • The Influence of Cutting Parameters on the Surface Hardness in Turning of 6061 Aluminum Alloy
    BL Mahdi, AH Ali, HK Hussein, OF Abdulateef
    Engineering, Technology & Applied Science Research 14 (5), 17118-17124 , 2024
    2024
    Citations: 3
  • Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
    B L Mahdi, HH Dalef, HK Hussein
    Eastern-European Journal of Enterprise Technologies 6 (1), 120 , 2022
    2022
    Citations: 3
  • Priority study of welding parameters affecting the rate of molten metal precipitation and hardness
    SSA Al Kareem, HK Hussein, FF Mustafa
    AIP Conference Proceedings 3105 (1), 020016 , 2024
    2024
    Citations: 1
  • Investigation the thermal effects on tensile strength in welding of carbon steel sheets
    SSAA Kareem, HK Hussein, OF Abdulateef
    AIP Conference Proceedings 3379 (1), 020011 , 2026
    2026
  • Industrial Automated Robotic Vision System
    WT Abbood, HK Hussein
    LAP LAMBERT Academic Publishing , 2019
    2019