Advancement of Science and Technology in Sustainable Manufacturing and Process Engineering

The fluctuating wind speed affects the power output of WECS (Wind Energy Conversion Systems), which might lead to problems with power quality when it is integrated into the grid network. Numerous difficulties have emerged as a result of the tremendous proliferation of interconnected power systems. These include oscillations, power swings, blackouts, and outages caused by natural disasters, and system flaws at transmission lines, load centers, and generation sites. This can lead to power system instability, which makes it difficult to plan for and schedule maintenance. FACTS (flexible alternating current transmission system) contribute to the enhancement of transient stability as well as the damping of oscillations, in addition to the control of active and reactive power. It must, however, be placed in a specific power network, be appropriately sized, and use the best FACTS device. The purpose of this study is to examine the impact of integrating FACTS into the 153 MW Adama II wind farm with the national grid of Ethiopia. The proposed wind farm is modeled using primary data while the grid side is represented by an IEEE 14-bus test system. Using the MATLAB/PSAT software tool, the ideal type of FACTS and their corresponding locations are determined by simulating the power flow in the combined WECS-IEEE 14 bus network. The IPFC (interline power flow controller) and UPFC (unified power flow controller) are added, together with the system response without FACTS, to compare performance. These devices’ effects on improving transient stability, reducing loss, damping power system oscillation, and supporting the voltage profile from the WECS to the distribution system have all been studied including under fault scenarios. The addition of IPFC and UPFC to the overall test systems significantly improves transient stability, dampens the multi-machine oscillations, and shortens the oscillation transient period. For this case study, FACTS devices decrease power losses in underperforming networks by 0.2485 p.u. with IPFC, and 0.1337 p.u. with UPFC.

Deep learning using convolutional neural networks has shown great promise in analyzing neuroimaging data. Identification of Alzheimer’s disease patients from healthy individuals using structural magnetic resonance data is one of the clinical problems that has been widely explored by employing convolutional neural networks and producing very high classification accuracies. However, in most studies, the results were not supported by explainability tools.

In this study, an interpretable convolutional neural network model derived from pre-trained VGG-16 is proposed to classify Alzheimer’s disease patients versus healthy subjects using MRI data obtained from an Open Access Series of Imaging Studies (OASIS) dataset. The model was trained and validated based on a five-fold cross-validation loop and produced a classification accuracy of 71.62% on the validation set. Moreover, we incorporated four CNN visualization techniques that highlight important brain regions used by the model to identify AD patients: saliency map, gradient class activation mapping, occlusion mapping, and heatmap generated by Shapley additive explanation (SHAP) method. The potential of these explainability tools in identifying biased models that produce inflated erroneous results is also investigated, and the resulting heatmaps were able to indicate a bias in the model’s training procedure.

Eye diseases are a major cause of blindness, primarily affecting elderly individuals, especially in developing nations. Among various eye diseases, glaucoma, age-related macular degeneration, and cataracts are the most prevalent in sub-Saharan African nations. Many of these eye conditions are preventable or treatable if detected early. Unfortunately, in low-resource settings, due to a lack of screening mechanisms and poorly organized healthcare structures, people do not often seek early checkups before the disease progresses. Furthermore, most eye diseases do not exhibit clear symptoms in the early stages and may be irreversible. Developing countries’ health facilities lack modern and high-quality screening technologies and specialized experts. In addition, conventional eye screening methods are reliant on physicians’ expertise and knowledge, which can lead to misdiagnosis. This study proposes a digital eye disease diagnosis support system that integrates image acquisition, enhancement, retinal vessel extraction, machine learning-based segmentation, and cup-to-disk ratio determination with intraocular pressure measurement for automated eye disease screening. Our experimental results indicate that this proposed system has the potential to be utilized as a decision support system for eye disease diagnosis, particularly in resource-limited settings.

The development of irrigation and agricultural water management technology holds significant potential to improve water productivity. Improper on-farm irrigation management practices lead to poor water distribution, non-uniform crop growth, excessive leaching in some areas leading to waterlogging, and insufficient leaching in others leading to salinity buildup. The research was conducted to evaluate water saving, yield, and water productivity of wheat by using the Wetting Front Detector (WFD) and Chameleon sensor at Chihona, Adibera, and Teleta blocks during the 2018/2019 irrigation season. The study shows that the Wetting Front Detector and Chameleon sensor irrigation water management system can save 6% and 25% water, respectively. The average water productivity (WP) of the scheme was 0.64 kg/m³, 0.85 kg/m³, and 0.87 kg/m³ for the Control group (i.e., traditional irrigation scheduling, based on experience), WFD, and soil moisture sensor (Chameleon) respectively. Likewise, the average yield of the scheme was 2788 kg/ha, 3220 kg/ha, and 3490 kg/ha for the Control group, WFD, and Chameleon, respectively. If all fields in the scheme were guided by WFD, additional land to be irrigated could be 2080 ha. Similarly, if all fields in the scheme were guided by the Chameleon sensor, 691 ha of additional land can be irrigated.

Rapid harvesting provides extra days to prepare the land and to plan the next crop earlier, especially for irrigation-based farming. The sorghum fields of Raya-Kobo and Azebo were chosen as study sites to better understand the effects of manual sorghum harvesting practices. The main examined drawbacks were low sorghum yield productivity owing to the lack of affordable modern machinery, inadequate control of repeated sorghum crop losses due to unexpected rains, labor crisis, and long harvesting process during the peak harvesting period. Hence, the aim of this study was to build a compatible sorghum reaper machine by using different methods. The initial approach involved measuring the diameter, length, and weight of seed-stage sorghum stalks by collecting samples from fields and recording the stalk’s tensile and shear strength values using a universal testing machine. The analytical designs of the reaper shafts were compared with a Finite Element Method using ANSYS; the results were accomplished with less than 5.5% errors. Particularly in the reciprocating system of the cutter bar, cranks and cutter bars were simulated using created MATLAB codes to reduce such catastrophic failures. As a result, the crank is in proper rotation, and the cutter bar is in exact translation. The forward speed in full load, Vm, 1.3 m/s, cutting speed, Vf, 1.82 m/s, and conveying speed, Vs, 3.076 m/s, were analyzed as significant points. Finally, if this reaper machine is built quickly, within 1 h, it will be able to harvest a 4.67 km² sorghum field.

This research was conducted with the aim to compare the difference in the electro-optical system’s output signal when the laser and photo detector in the system are concurrently exposed to the magnetic field relative to those transducers individually subjected to the field. To demonstrate the difference in the effect, an experimental setup was prepared in the laboratory using a Vertical Cavity Surface Emitting Laser (VCSEL) and a PIN photo detector. Then experiments were carried out by applying a stationary magnetic field with an amplitude of (0–1000 mT) in parallel (B┴n) and perpendicular (B//n) to the active region of the input laser and output photo detector at around room temperature (20 °C), and the output is measured and logged at different magnetic field strength while the laser and photo detector are individually as well as simultaneously subjected to the field. The results measured when the laser and photo detector are concurrently exposed to the magnetic field compared with the result measured when both transducers are independently exposed. Our experimental results showed that for B//n alignment to the VCSEL, the output voltage increased by 6.8%, but for B┴n, no change in output voltage was observed. Regarding the PIN photo detector, for both B//n and B┴n alignment of the magnetic field, an output voltage increased by 6.7% and 13%, respectively. Overall, when both VCSEL and PIN photo detector are simultaneously exposed to the field, the output voltage increased by 71%.

Traditional fermentation is carried out initially by natural microorganisms present in the substrate. This usually leads to a long fermentation time and occasional failure of the fermentation, and creates inconsistencies in the product quality. Teff injera is one of the widely used Ethiopian fermented foods that suffer from such a problem. Therefore, the aim of this study was the identification of the dominant species of lactic acid bacteria (LAB) and yeast for the optimization of the traditional fermentation process of teff injera dough fermentation. The dominant LAB and yeast species were identified by using morphological, physiological, and biochemical characterization. The growth kinetics of both LAB and yeast in fermented teff dough was increased significantly (p < 0.05) from 8.91 to 9.97 log cfu/g and 5.98 to 7.62 log cfu/g. In this study, five LAB and three yeast dominant strains were identified. The LAB strains were identified as Lactobacillus fermentum (26.7%), Lactobacillus brevis (20%), Lactobacillus plantarum (13.3%), Bacillus subtilis (20%), and Enterococcus casseliflavus (20%), and the yeast species included Saccharomyces cerevisiae (40%), Candida krusei (40%), and Pichia kudriavzevii (20%). Lactobacillus plantarum, Lactobacillus fermentum, Lactobacillus brevis, Bacillus subtilis, Enterococcus casseliflavus, Saccharomyces cerevisiae, Candida krusei, and Pichia kudriavzevii were found to be the most dominant LAB and yeast species and could be detected in fermented teff dough samples from the beginning (24 h) to the later (96 h) fermentation times. In the current study, the fermentation time of teff dough with single starter culture was improved by 75% compared with the conventional fermentation time, which is reduced from 96 to 24 h of fermentation time. Hence, further study will require the molecular characterization of the identified LAB and yeast isolates by using 16s rRNA to confirm the isolates as LAB and yeast.

Even though the production of maize in Ethiopia is highest, its post-harvest loss is very high that estimated as high as 19.8%. Post-harvest loss of maize occurred at each post-harvest activity along the value chain. In Ethiopia, high loss of maize is incurring during threshing, drying, and storage. Open sun drying/sun drying is the only drying system before and after harvesting of maize that results from 5.8% to 17.4% loss. Thus, it is very important to dry maize using an appropriate dryer to minimize this loss during storage and drying itself. The main objective of this study was to investigate the performance of a collapsible dryer for the drying of freshly harvested maize grain. Collapsible dryer is an affordable and portable dryer that can dry various agricultural products safely and conveniently. The performance of the collapsible dryer was tested using a sample load of 500 kg (10.45 kg/m²) freshly harvested maize grain with a variety of BH-540. During the drying period, drying air, relative humidity and temperature (both loading and unloading condition), and maize grain moisture content were measured continuously and total energy consumption and drying rate were computed. In addition, the temperature and relative humidity of the experimental environment were measured. The performance of the collapsible dryer was compared with open sun drying system for maize grain. The result revealed that the drying time required for maize grain dry to 14% moisture content (w.b.) in collapsible and open sun drying system were 26 and 74 hours, respectively. The hourly moisture removal rate was found 0.17 kg moisture/hr. and 0.062 kg moisture/hr. in collapsible and open sun drying, respectively. The drying efficiency and total energy consumed by the collapsible dryer were found to be 76.25% and 169.65 MJ, respectively. The performance of a collapsible dryer was better than open sun drying for maize grain drying, and this technology could be considered as a good option for the drying of grain to reduce the loss.

Quality assurance (QA) is an important subject in the construction industry. The industry has been challenged with serious QA issues. The stakeholders of the industry (that is, clients, consultants, contractors, and the regulatory body) collectively play a vital role in addressing the challenges of QA in the industry. The research investigates or finds current and existing QA methods, techniques, and practices that determine the major factors that affect QA management practices, explores mechanisms to improve QA management practices, and prepares a conceptual framework for public construction projects in Bahir Dar City. The survey questionnaires conducted interviews, and case studies for three projects. The questionnaires were administered to the respondents (clients, consultants, contractors, and regulatory bodies in Bahir Dar) who were directly involved in the 26 public construction projects. The study points out that following instructions standards and codes, direct supervision, laboratory experiment, and inspection were major techniques for QA management practices. Project type and complexity, design, contract, materials, labor, and equipment were major factors that affect QA management practices, and management commitment, reducing miscommunication, and review/analysis were improving mechanisms for QA management practices for public construction projects in Bahir Dar City.

The emergence of water ATM technology and its socioeconomic advantages are discussed in this chapter. Water ATMs are automatic dispensers that provide purified, drinkable liquid water at the customer’s request with minimal or no human interaction. It’s critical to enhance the quantity of potable water with the least amount of effort, expense, time, and technology. Three different types of water ATM systems are now present worldwide. These are coin and/or note-based ATMs, smart card-operated, and smart card and IoT-based systems. Smart card-based operating systems are those which can use smart cards and/or cash methods, but they are self-monitored systems. A smart card and IOT-based system Modules are integerated into the water dispenser machine to achieve an efficient payment method approach and real-time monitoring, respectively. Most ATMs are developed from components like microcontrollers, NFC and RFID smart cards, coin modules, LCD displays, solenoids, pumps, and water tankers. The socioeconomic benefits with respect to accessibility of quality water and possible technological advancements together with the cost of services are detailed to show the importance of the ATMs as the best alternative to the existing pure water supply methods.

Different types of inks are imported to Ethiopia; however, the country has strong potential plants that can be used to produce inks. Due to this, it is necessary to produce writing ink from locally available plants like Ficus vasta and Euphorbia abyssinica. The main objective of this research was aimed at the formulation and characterization of ink from the milky fluid of F. vasta and E. abyssinica with methanol as solvent, soot as pigment, black berry as colorant, and vinegar as additive (preservative). The raw materials were collected and prepared for further process. Then, the effects of solvent concentration (50%, 75%, and 100% methanol) and mixing ratio (R₁, R₂, and R₃) of F. vasta to E. abyssinica on ink properties were investigated. The experimental results were collected and characterized in terms of pH, viscosity, and drying time, and their values were found 5.56 ± 0.04, 1.35 ± 0.048 mNs/m², and 2.37 ± 0.035 s respectively, at R₃ (102.8:51.4) and 75% v/v methanol concentration. These results clearly showed that F. vasta and E. abyssinica have the potential to produce writing ink.

Reduction of non-revenue water remains one of the major challenges facing the water utility in Bahir Dar, although there are currently no effective reduction plans in place. The general objective of this study was thus to pinpoint the root causes of non-revenue water and offer potential solutions. To achieve this objective, flow measurements, ultrasonic leak detection, and questionnaires and interviews were conducted. Statistical analysis was applied to analyze the non-revenue water questionnaires and interviews. Quantitative and qualitative research techniques within a probability systematic and a non-probability purposive sampling methodology were used. The findings indicated that a substantial percentage up to 45% of the water entering the Bahir Dar water supply system is non-revenue water. According to the results of the questionnaires and interviews, the current management of the water network, which lacks maintenance and repairs, active leakage control, high unpaid water bills, low employee motivation, low team spirit, and insufficient financial resources of the utility, are the main causes of the high non-revenue water in the Bahir Dar water supply system.

Recent studies reveal that supply chain integration (SCI) has a fully mediating role between supply chain management practices (SCMPs) and supply chain performance (SCP). It enhances SCP and facilitates other elements of SCMPs, although it is a great challenge for many manufacturing firms to achieve a higher level of integration. The severity of the challenges varies based on: product characteristics, industry characteristics, location of suppliers, and the role of firms in the global supply chain (GSC). However, there is a lack of study on the characteristics and challenges of SCI while firms make a shift of role in the GSC. The aim of this study is to assess the characteristics of SCI taking the leather and leather products manufacturing industry in Ethiopia as empirical evidence, wherein a dynamic shift has occurred from the state of raw material supplier to supplier of value-added products to the GSC. Survey, observation, and questionnaire were applied to collect data. The data were analyzed with the framework of Supply Chain Operations Reference (SCOR) Model and compared against the McLaren’s five levels of SCI characteristics. The study has identified six typologies of supply chains, which are practiced by large and medium-scale firms. Out of the six typologies, supply chain-5, formed by vertical expansion of firms, is dominantly practiced by many of the firms. This supply chain doesn’t satisfy any of the higher levels of McLaren’s SCI characteristics (Level-III, Level-IV, and Level-V) since there is a lack of horizontal integration among firms by outsourcing non-core activities. The output of this study can help to shed light on the nature of supply chains in developing countries while moving from raw material supplier to producer of value-added products. In the end, further study is needed to study the complete supply chain including raw material and input suppliers in order to understand its effect on firm’s overall performance.

Although maize is a staple crop in Ethiopia, an inefficient postharvest management system causes significant postharvest loss of it. The purpose of this study was to study the effect of threshing and storage conditions on mold contamination of maize grain during storage. Freshly harvested maize grain with BH-540 variety was used for the study. Maize at two different moisture content, 17 ± 0.5, and 23 ± 0.5%, was threshed by hand and mechanical threshing methods and then dried to safe storage moisture (13 ± 0.5% w.b.) by a solar bubble drier. The dried maize grains were kept in hermetic bags (Purdue Improved crop storage bag and GrainPro) and non-hermetic bags (ZeroFly, woven polypropylene bag with plastic liner, and woven polypropylene bag) at room temperature for 6-months. Maize grain moisture content was measured and occurrence of mold on the grain was investigated at 3-months interval during storage. Minitab software package (version 19.2) was used for data analysis. At the onset of the experiment, the moisture content of maize grain was 12.93% (w.b.), and it was increased to 14.31% (w.b.) in woven polyethylene bags but kept constant in hermetic bags at the end of the 6-month storage. Overall, maize grain that threshed mechanically and kept in non-hermetic bags had higher moisture content than hermetically stored ones. Consequently, the incidence and frequency of fungal growth was increased with storage duration in non-hermetic bags. After 6 months of storage, the greatest levels of Aspergillus, Penicillium, and Fusarium spp. were found in maize threshed mechanically at 23% moisture content and kept in woven polyethylene bags. Generally, hermetic bags are more suited for preserving stored maize grains from fungal invasion throughout storage periods weather it is threshed mechanically or on hand.

The main aim of this research is to formulate and evaluate firefly and artificial bee colony metaheuristic algorithms to track the global maximum power point for photovoltaic (PV) system in partial shading condition. The review of related researchs group available approaches as classical and evolutionary algorithms-based techniques for the proposed application. However, the classical optimization technique-based approaches have common shortcomings of being unable to track the global maximum power point whenever partial shading and mismatching in PV panels happen, missing the correct tracking direction during fast radiation change and output oscillation during steady-state condition since they are perturbation based approaches even though they are simple and have less complexity. A number of research activities using artificial intelligence-based approaches inspired by human intelligence, swarm intelligence, and different animals’ natural intelligence have been proposed and implemented using a direct duty ratio control approach for the power electronic converter. In this research firefly and artificial bee colony-based algorithms are formulated for direct voltage control approach, implemented, and their performance is evaluated. The results revealed that the proposed approach can track the global peak accurately and reduce steady-state oscillations compared to the incremental conductance (InCod) classical approach implemented for comparison purpose.

This chapter presents the study carried out to discover uncertain parameters in a model of a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS) and to investigate their effects on WECS plant while harvesting energy from wind at varying speeds. This is carried out by analytically formulating the steady-state models of a DFIG-based WECS and computing the parameters of these models at different wind speeds that drive wind turbines at rotor speed from sub-synchronous to super-synchronous. The main uncertain parameters in this system are the mutual reactances between stator and rotor windings, and the reactance of rotor winding. These variations happen due to the varying wind speed. The effect of parametric uncertainties on the steady-state performances of DFIG-based WECS is examined. The results depicted that the steady-state performances of DFIG-based WECS are influenced by uncertain phenomena. Typically a 0.5% change in mutual reactances caused up to 10 kW change in the generator output power. Mainly, it causes instability in the performances of the DFIG-based WECS and slightly reduces overall efficiency at a higher value of the wind speed.

A study was carried out to evaluate and demonstrate simple handheld maize Sheller for small holder maize producer at Debremawi water shade, Yilmana Dena Woreda, North Western Ethiopia. The technology was manufactured at Bahirdar Agricultural Mechanization and Food science research center and compared with two traditional methods of maize shelling; shelling by rubbing with a tomb (finger shelling) and shelling by rubbing two cobs together. Shelling efficiency, percentage damage, and shelling capacity were used as performance indicators for comparing the shelling methods. The maximum output of the Sheller was 35 kg.hr.⁻1. The cost benefit analysis shows that by costing 50.00 ETB for Sheller and 1800.00 ETB for one laborer, the user can save 2097.49ETB and 21.47 working days per month compared to finger shelling technique within a month output. Training for technology manufacturers (producers) should be planned timely in order to extend to the broad scale.

Besides, taking in to consideration that in small scale farmers maize shelling is the main duties of women, this technology will enable to combat women’s work load and hence it is one of the “Women’s friendly” technologies to be promoted in the maize producer areas.