Ethiopia Institute of Technology- Mekelle

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Start date: 2020

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Now showing 1 - 10 of 95
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    ENHANCING BANKING SERVICES THROUGH DATA MINING: A CASE STUDY OF WUKRO CITY , TIGRAY REGION
    (Mekelle University, 2025-11-19) ABRHALEY KORKOS
    Banking services play a crucial role in supporting economic development and financial inclusion by providing essential products such as savings, loans, fund transfers, mobile banking, and customer support. However, in developing regions like Wukro City, Tigray, banks face persistent challenges in delivering efficient, reliable, and customer-oriented services. These challenges include long service times, limited personalization, weak customer relationship management, and gaps in decision-making processes. To address these issues, this study explores how data mining models can be applied to enhance banking services, thereby improving service quality, customer satisfaction, and operational efficiency. The research employed a mixed-methods approach, integrating both quantitative and qualitative techniques. Survey data were collected from banking customers and employees to identify service gaps and customer expectations. Quantitative data were analyzed using WEKA software to develop predictive. The qualitative data, gathered through interviews and focus group discussions, provided contextual insights into customer experiences and perceptions of banking services in Wukro City. The findings revealed that data mining models can significantly enhance banking services by enabling banks to segment customers effectively, predict loan repayment behaviors, identify cross-selling opportunities, and detect service inefficiencies. The study also highlighted that customer satisfaction is closely linked with digital service adoption, personalized banking products, and reduced waiting times. Furthermore, the results suggest that integrating data-driven decision-making into banking operations can strengthen competitiveness and trust in the local financial sector. This research contributes to the growing field of technology-driven financial services by demonstrating the applicability of data mining in a developing regional context. For Wukro City banks, the study provides a practical framework to adopt data mining techniques in order to deliver more customer-focused, efficient, and innovative services. Ultimately, the study concludes that leveraging data mining not only enhances banking performance but also supports broader financial inclusion and sustainable economic development in the Tigray region.
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    Simulation-Based Investigation of Adaptive Suspension Control for Regional Road Conditions in Tigray
    (Mekelle University, 2025-11-19) Abraha Gebru
    This thesis presents the design, modeling, simulation, and performance evaluation of an adaptive suspension control system developed to improve vehicle dynamics under the diverse road conditions of the Tigray region, Ethiopia. Suspension systems are fundamental in enhancing ride comfort, handling, and overall vehicle stability. Conventional passive suspensions, while simple and cost-effective, lack adaptability to the rapidly changing and uneven road conditions prevalent in developing regions. In response, researchers have introduced various intelligent control techniques—such as PID, Fuzzy Logic, and Adaptive Neuro-Fuzzy Inference Systems (ANFIS)—to address these challenges. However, existing studies still face limitations in real-time adaptability, nonlinear response management, and system robustness across unpredictable terrains. To overcome these challenges, this study proposes a hybrid PID–ANFIS adaptive suspension control approach, combining the fast response of the PID controller with the learning and adaptability of ANFIS. A quarter-car model of a light-duty vehicle was developed in MATLAB/Simulink to simulate various representative road conditions, including paved, unpaved, bump, and hilly terrains. The controller’s performance was evaluated using key dynamic metrics: ride comfort (weighted RMS acceleration), suspension travel, and road holding ability. Simulation results demonstrated that the hybrid PID–ANFIS controller outperformed both the classical PID and passive suspension systems. Specifically, body acceleration was reduced by over 80%, suspension travel was maintained within safe mechanical limits, and tire force variation was minimized, improving road holding stability. The overshoot decreased from 72.33% (PID) to 19.73% (PID–ANFIS), while rise time improved from 34.71 ms to 12.59 ms, and the RMS error reduced from 0.05784 (passive) to 0.00026 (PID–ANFIS). Compared to prior studies reporting 70–78% improvement using hybrid controllers, the proposed system achieved higher performance gains due to optimized parameter tuning and adaptive learning capabilities. The results confirm that the proposed hybrid PID–ANFIS controller is an effective, terrain-adaptive solution capable of improving ride comfort, stability, and safety for vehicles operating in challenging regional road conditions. This work contributes a region-specific adaptive suspension model that can be applied to improve vehicle performance in developing areas with similar infrastructure characteristics.
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    Modeling, Simulation, and Experimental Validation of an Electrical-based Injera Baking Mitad System
    (Mekelle University, 2025-08-14) Ataklti Gedamu
    About 30 to 50 percent of Ethiopian households utilize energy for injera baking, and conventional charcoal-fired Mitads produce a lot of emissions (about 1.2 kg CO₂ per session). Although they provide an alternative, electric mitads have a thermal efficiency that is typically between 60 and 70 percent. By using numerical modeling of composite materials to optimize electric Mitad performance, this study fills a research void that hasn't been filled by previous experimental work. We verified 17 minutes to reach 148°C and baked 21 injeras at 3 minutes each (66.81% efficiency) using ANSYS transient thermal software to validate a baseline model (2.8 kW clay pan) against experimental data (<3% deviance). Three composites were assessed: [1] Heating time was shortened by 59% (7 minutes to 150°C) using 95% clay and 5% aluminum chips. and baking time to 2.5 minutes per injera, achieving 70.21% efficiency (0.47 kWh/session saved); [2] ceramic reached 150°C in 12.5 minutes but required reheating due to ~10°C temperature drops per cycle; [3] 60:40 clay-aluminum composite achieved 150°C in 9 minutes with stable heat retention (68.2% efficiency). The 95% clay-aluminum composite demonstrated 25% total energy reduction per cycle, potentially saving households ~120 kWh annually. This work enables future optimization of composites, insulation, and socioeconomic analysis of production costs versus energy/fuel savings.
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    MODELING AND SIMULATION OF A COMPACT ELECTRIC VEHICLE CONVERSION FOR ETHIOPIAN URBAN TRANSPORT USING MATLAB/SIMULINK
    (Mekelle University, 2025-11-19) HEAVEN AMANUEL
    Ethiopia’s transition to sustainable mobility is challenged by high fuel costs, import dependence, and limited access to affordable electric vehicles (EVs). This study develops a technically feasible and economically adaptable framework for converting internal combustion engine (ICE) vehicles to EVs, ensuring compliance with national retrofit standards and optimizing drivetrain integration, energy efficiency, and performance validation. A widely used 1993 Toyota Corolla was selected for conversion and equipped with a three-phase liquid-cooled BLDC motor rated at 20 kW nominal and 50 kW peak power, limited to 145 Nm torque per standard. The 121.6 V, 280 Ah LiFePO₄ battery pack (34.06 kWh) powered the system, while the original five-speed gearbox was retained to enhance torque delivery and maintain compatibility. Safety and auxiliary systems included vacuum-assisted braking, electric hydraulic steering, and a 600 A battery management system. The methodology encompassed powertrain sizing, component selection, and MATLAB/Simulink-based simulations using the FTP-75 urban cycle. Results showed a 261 km range per charge and 130.6 Wh/km energy consumption, indicating strong urban applicability. Compared with commercially available EVs such as the BYD Seagull, the converted vehicle exhibited comparable performance and efficiency. The originality of this work lies in its use of a locally available ICE platform, adherence to Ethiopian retrofit standards, and comprehensive simulation-based validation. These findings highlight the potential of vehicle retrofitting as a cost-effective strategy for electrifying Ethiopia’s existing fleet, reducing fuel dependency, and supporting national sustainability goals.
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    DEVELOPMENT AND SELECTION OF GLASS/SISAL AND SHEEP WOOL FIBER REINFORCED HYBRID POLYMER COMPOSITES FOR VEHICLE BUMPERS
    (Mekelle University, 2025-11-24) Mulu Gidey
    Background: A bumper is an essential part of a vehicle, engineered to absorb impacts and shield the front and rear during low-speed collisions. This research focuses on creating glass/sisal and sheep wool fiber-reinforced composites for bumpers, meeting the demand for lightweight, sustainable materials while fostering local economic growth through job creation. It seeks to substitute traditional heavy materials, decrease costs, and advance sustainability initiatives within the automotive sector. Objective: The primary objective of this research is to develop and select hybrid composite materials that combine glass, sisal, and wool fibers reinforced with epoxy resin for use in vehicle bumpers. Specific goals include enhancing the mechanical properties of natural fibers and optimizing the composite design for performance and cost-effectiveness. Method: The methodology involves treating sisal and wool fibers with sodium hydroxide to enhance their mechanical properties, followed by the fabrication of composites using hand lay-up techniques. A comprehensive series of mechanical tests based on ASTM standards assesses properties such as tensile strength, impact resistance, and water absorption. Result: The composites demonstrate a tensile strength of 114.07 MPa, impact resistance of 112.5 kJ/m², and the composite bumper can absorb a maximum energy of 49.34kJ/m2 with speed 2.22m/s, and also a weight of 3.8 kg, significantly lighter than traditional steel bumpers (5.16 kg). Software analysis using Genetic Algorithms optimized the design, achieving a maximum stress of 31 Mpa and a deflection of 89 mm under impact conditions, indicating superior performance compared to conventional materials. This study supports the transition to environmentally friendly materials in the automotive industry. Conclusion: This research substantiates that glass/sisal and wool fiber-reinforced composites are viable alternatives for automotive bumper applications, offering improved performance and reduced environmental impact, to reduced fuel consumption and local economic growth. The findings support the ongoing transition toward sustainable materials in the automotive industry and highlight the economic benefits associated with local fiber utilization.
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    THE IMPACTS OF CHILD LABOR ON EDUCATIONAL ACHIEVEMENT: WITH A FOCUS ON TRADITIONAL MINING IN YECHILA
    (Mekelle University, 2025-08-28) KEWANI TADESSE GEBREHIWOT
    This study investigates the impact of child labor in the mining sector on the educational achievement in Yechila Woreda, Tigray. The research explores the nature of this labor, its underlying socio-economic drivers, and its specific effects on children’s education. Adopting a qualitative, phenomenological research design, the study drew data from a purposively selected sample in three mining-prevalent kebeles: Jijike, Gira, and Emba Rfael. Data was collected through in-depth interviews (IDIs) with 25 child laborers, three focus group discussions (FGDs) with 18 child laborers, and key informant interviews (KIIs) with 17 government officials, teachers, and community leaders. The findings reveal that child labor in Yechila's mines is a brutal and hazardous reality, predominantly affecting boys aged 14 and younger. The work is characterized by extreme physical hardship, constant danger, psychological trauma, and economic exploitation. The study concludes that this crisis is a direct consequence of the war, which acted as a catalyst, transforming chronic poverty into an acute survival crisis by systematically destroying traditional livelihoods, devastating family structures, and causing the total collapse of the educational system. The educational impact is catastrophic: a staggering 97.7% of the child miners in the study had either never attended school or had dropped out completely. Mining systematically dismantles education by making school attendance physically impossible, causing severe cognitive impairment that renders learning ineffective for those who try to attend, and psychologically eroding the children's aspirations for an educated future. The study recommends an urgent and integrated response focused on post-conflict recovery. Key recommendations include: immediate humanitarian interventions such as food aid and cash transfers to alleviate household poverty; programs to restore and diversify livelihoods; a trauma-informed rehabilitation of the educational system through the creation of flexible learning centers and the reconstruction of schools; and the establishment of community-based child protection committees to rebuild social safety nets. This research highlights the creation of a lost generation and underscores the need for immediate, comprehensive action to restore children's fundamental right to education and hope.
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    Distributed Power Flow Controller Based Power Quality Improvement for Grid Connected Wind Farm- Case Study Ashegoda Wind Farm
    (Mekelle University, 2025-09-23) Ashenafi Selema
    Grid penetration level of renewable energy is growing and merging dramatically. However, poor power quality creates a major integration and operation problems. Ashegoda wind farm represents Ethiopian first large scale wind power installation, having a total rated capacity of 120 MW. The substation is equipped with two 230kv buses that interconnect Lachi and Alamata substations. In the analyzed system, both transmission lines experienced high reactive power flow approximately 43MVAr and more than 3% current total harmonic distortion (THD), which leads to additional power loss, voltage drop, equipment overheating, and network congestions. On the other hand, the on-load tap changer (OLTC) transformer used to support voltage sag, swell, under-voltage, and over-voltage has slow response time up to 10 seconds per tap, and creates transformer overheating and mechanical fatigue. To solve such integration challenges, the incorporation of a distributed power flow controller (DPFC) with in the system is necessary for improved power quality and reliability. This study analyzed and modeled the integration, impact, cost benefit analysis, and Genetic Algorithm (GA) based optimal sizing and placement of DPFC for Ashegoda wind farm. The objective was to model, simulate, and asses its impact on voltage stability, reactive power compensation, and steady state and dynamic performance. The result indicated that, without DPFC the 230kv system operated at under-voltage of 0.89 pu with 5% current THD at bus 690v. After integration of 8MVA series and 25MVA shunt DPFC controller, the voltage profile is improved to 0.96 pu and current THD is minimized to 1.8%. Integrating DPFC exhibited excellent performance in maintaining voltage stability and limiting short-circuit current levels under different fault scenarios. The cost benefit analysis was carried out over a 20-year period. The total net present value (NPV) is estimated around $15,310,316.0 US dollars, while the total investment cost amounts $7,883,000.00 US dollars. By implementing the system, Ethiopian electric utility is expected to gain $7.5 million US dollars profit without considering scrap value. Generally, the researcher proved that DPFC is technically and economically feasible. MATLAB/Simulink 2018a and Excel-2013 was employed to model, simulate, and analyze the proposed DPFC system.
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    Artificial Neuro-Fuzzy Inference System (ANFIS) Based Speed Control of Separately Excited DC Motor for Load Torque Variations
    (Mekelle University, 2025-09-09) Kibrom Zerau
    Separately excited direct Motor (SEDCM) is an electromechanical actuator used to power different loads across several industrial and domestic applications. One fundamental characteristic for controlling when driving is the motor's speed. The external load linked to the drive negatively impacts speed if the controller is weak and the load varies. Objective of this thesis work is to design an Artificial Neuro-Fuzzy Inference System (ANFIS)-based speed control mechanism for a separately excited DC motor under varying load torque conditions. The ANFIS controller integrates neural networks and fuzzy logic to improve motor speed regulation, ensuring robust performance despite disturbances in load torque. Additionally, this this work explores the effectiveness of armature voltage control (source voltage adjustment) for dynamically regulating motor speed, comparing its performance with conventional control strategies. ANFIS, fuzzy logic controllers, PID controllers, and open loop (without controller) have all been used to measure the speed of an independently stimulated SEDC motor. At first, the motor speed can be regulated and modified by changing the armature voltage (the input supply voltage).When the torque of the load grows and the transient and steady state faults rise, the motor's speed falls in the absence of a controller. The motor performs poorly as a result, and its speed will not maintain its rated level. A PID controller improves the motor's speed over an open loop, but the overall performance is still poor and there are still some transient and steady state issues. Although fuzzy logic controllers perform better than PID controllers in terms of system performance, the speed still fluctuates as the torque of the load changes. However, ANFIS better than fuzzy, PID, and open loop control systems, operates at its rated speed, has low steady state and transient errors, and keeps the motor's speed constant as the load increases. In conclusion, NFIS is superior to fuzzy and PID controllers due to its zero overshoot and reduced 38.31% settling time compared to fuzzy and 50.93 % compared to PID, reduced 37.12% rise time compared to fuzzy and 44.87 % compared to PID, and reduced 85% steady-state error compared to fuzzy and 98.5 % compared to PID. Additionally, by resolving the motor's nonlinear properties, the system's overall performance will improve.
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    Voltage Control of DC-DC Boost Converter Using Lyapunov Rule Based Model Reference Adaptive Controller
    (Mekelle University, 2024-10-24) Mebrahtu Ngusse
    The switched mode DC-DC converters are the simplest power electronic circuits that facilitate the conversion of electrical voltage from one level to another through a switching process efficiently. DC-DC boost converters are utilized for step-up voltage in various applications. The output voltage of boost converter has, oscillation, overshoot, undershoot, and steady-state error. PID controllers have been usually applied to the converters because of their simplicity to obtain the desired voltage. But, PID controller could work well in one operating condition and cannot continuously adapt the changes in the process dynamic. To overcome this problem an advanced controller is required. The proposed Lyapunov Rule Based MRAC is adaptive and non-linear controller designed to overcome the uncertainties and nonlinearities for DC-DC boost Converter under Continuous Conduction Mode (CCM) operating condition. Using MATLAB/Simulink the performance of the proposed Lyapunov rule based MRAC is compared with that of the PID controller based on the dynamic response of the system. Using PID controller, overshoot and settling time have been improved by reducing from 67.5229% to 7.7717% and 0.6985 Sec to 0.277 Sec respectively. In the case of the proposed controller (Lyapunov rule based MRAC), overshoot, settling time, and undershoot have been improved by reducing from 67.5229% to 4.5993%, from 0.6985 Sec to 0.1458 Sec, and from 0.0036% to 0.0% respectively. To test the performance of the DC-DC boost converter, it is assumed that, the input voltage has been decreased and increased from its operating point by 25% and 41.67% respectively. Also the load resistance is assumed to be decreased and increased from its operating load resistance by 25% and 20% respectively. An external disturbance is applied to the system to check how the controller handles to uncertainties and PID controller has shown deviation from the desired value but, the controller MRAC maintained the desired value.
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    Comparative Analysis of Passive, PID And Fuzzy_PID Controller For Quarter Car Model
    (Mekelle University, 2025-09-15) Atsede Gebreyohans
    This paper presents a comparative analysis of passive, PID, and fuzzy PID control strategies for a quarter-car suspension system utilizing a fuzzy PID controller to enhance ride comfort and stability by effectively managing displacement and velocity. The quarter-car model serves as a simplified representation of vehicle dynamics, where the primary objective is to minimize the vertical displacement of the vehicle body and control the relative velocity between the body an the wheel. Additional PID controllers often struggle with non-linearity and uncertainties present in suspension systems; therefore, it is proposed a fuzzy logic approach to tune the PID parameters dynamically based on real-time system states. The fuzzy-PID controller integrates the benefit of fuzzy logic’s ability to handle uncertainty and the robustness of classical PID control. Simulation results demonstrate that the proposed fuzzy-PID versus passive controller significantly reduces body displacement by 88％of overshoot and 56％of settling time with bumpy input road1. Fuzzy-PID versus passive controller significantly reduces velocity response by 24％of overshoot and 55％of settling time with bumpy input road1.