Mekelle University Institutional Repository
Not a member yet
635 research outputs found
Sort by
Improving plant availability through Effective Maintenance System: A Case Study in MESSEBO CEMENT FACTORY
No full textCorrective maintenance technique is have long been one of an obstacle to Messebo cement factory’s efforts to maintain high plant availability. In the fiscal year 2023/24 MESSEBO cement factory is experiencing suboptimal operational efficiency due to the persistently low availability of critical machinery across its production lines. Key equipment essential for raw mill processing, clinker production, cement milling, and packaging is operating below industry- standard availability benchmarks (85-90%), leading to reduced production capacity, increased downtime costs, and potential delays in meeting customer demand.
This research examines the existing maintenance system on plant availability and over all equipment effectiveness (OEE) in the context of messebo cement factory. The study’s main objectives were to assess current maintenance procedures, pinpoint the underlying reasons for outages, and suggest workable plans to improve operational effectiveness through manpower development, predictive technology, and infrastructure improvements.
The research used mixed- methods quantitative and qualitative approach, through a comprehensive case stud approach analyze maintenance data in terms of performance metrics and downtime cases. The research findings highlighted several critical issues. A reactive maintenance culture prevailed, with over 56% of respondents indicating that preventive tasks were often skipped during peak production periods. Aging infrastructure and unstable power supply led to more than 30 major equipment failures annually. Furthermore, outdated manual record keeping practices undermined data accuracy, despite 83% participants acknowledging the link between downtime and the absence of predictive maintenance. Despite these challenges, the study identified several opportunities for improvement. Notably, 60% of the workforce expressed support for modernization efforts, while 50% believed that real-time monitoring systems could significantly enhance decision making and efficiency. The research recommended immediate piloting of IOT sensors on critical equipment (e.g, cement mill rollers), enforcing strict PM via digital checklists. Medium term strategies include CMMS implementation for centralized planning and predictive analytics, alongside specialized maintenance team training. Long term goals target transitioning to predictive maintenance (aiming for 20-40% downtime reduction), fostering cross departmental collaboration through shared KPIs, and securing leadership support by demonstrating RO
Analysis of Potato Value Chain and its impact on farming household’s economic welfare: The case of Tsaeda-Emba Woreda, Eastern Zone, Tigray Regional State
No full textVarious project-based initiatives including those led by the International Potato Center (CIP) have been implemented to upgrade the potato value chain in the region. However, despite these targeted interventions, the actual contribution of potato production to the welfare of smallholder producers remains inadequately understood. Therefore, further efforts were made to empirically examine how potato value chain impacts households’ income and consumption expenditure to improve our understanding of the welfare implications of the crop. The study aimed to identify actors and their roles, analyze benefit distributions of actors, assessing the impacts of potato value chain on households’ economic welfare. For this study 137 potato producers, 137 nonproducers were randomly selected, 5wholesalers, 3collectors, 9 retailers and 5 small scale processors were purposefully selected. Value chain mapping was used to identify actors, their roles and linkages. Endogenous switching regression model was employed to identify determinants of participation decision and to analyse welfare impacts through Average Treatment effect on the Treated (ATT) estimates in potato value chain business. The identified key actors in potato value chain were input suppliers, producers, wholesalers, collectors, retailers, small scale processors and consumers. Main supporting actors were office of agriculture and rural development, micro finance institutions, (union) cooperatives, trade and market development office, Mekelle Agricultural Research Centre, NGOs and banks that found in the woreda. The results of economic analysis revealed that 86% profit goes to small scale potato processors and 5.8% profit margin was captured by potato producers respectively. The rest actors (collectors, wholesalers and retailers) received profit margins of 2.4%, 1.5% and 4.3% respectively. The results of ESR model analysis showed that gender, farming experience, access to credit, irrigation cooperative’s membership, demonstration sits visit, listening to radio programs, and access to irrigation influenced participation decision significantly and positively. Age, family size, training frequency, food shortage experiences affected potato participation decision negatively. Economic welfare of potato producers’ is much higher than non-producers’ because their annual income, annual consumption expenditure, food consumption score and household diet diversity score is increased by 50.7%, 48.7%, 13.7% and 23.3% respectively
Rhamnus prinoides-based Agroforestry for Climate-Smart Agriculture in Drylands of Tigray, Ethiopia
No full textAgriculture is the backbone of socioeconomic development in many developing countries, but climate variability and land degradation are threatening productivity and income. Adopting climate-smart agricultural practices has been increasingly suggested as a solution. Locally practiced tree-based farming systems, such as agroforestry, can offer a promising solution, helping farmers boost productivity, adapt to climate change, and sequester carbon. However, the role and potential of agroforestry practices depend on many socioeconomic and biophysical factors, suggesting for the need of context-specific study. Integrating R. prinoides trees/shrubs with crops is local or indigenous practice in Tigray, Ethiopia providing multiple benefits. Thus, this PhD study aimed at assessing the distribution and characteristics, socioeconomic benefits, and adaptation and mitigation roles of Rhamnus prinoides-based agroforestry practice in four consecutive chapters.
Using Maxent model, the future distribution of R. prinoides agroforestry under climate change scenarios was predicted, showing that suitable areas may shrink. R. prinoides is successful in the highlands and midlands with moderate temperature, good soil, and partial sunlight. Field surveys of 191 households practicing R. prinoides agroforestry reveal that the system thrives in rain-fed areas and is particularly resilient due to its inverse phenology, which reduces competition with crops, and optimizes water use. R. prinoides-based agroforestry is not only more profitable than traditional wheat farming, yielding three times higher returns, but also creates additional employment and strengthens land use rights, with women playing a central role in harvesting and income management. The practice enhances farmers’ resilience by diversifying production and stabilizing income throughout the year. Beyond social and economic benefits, R. prinoides agroforestry contributes significantly to climate change mitigation, with carbon stocks up to three times higher than in annual crop mono-cropping systems.
This research underscores the importance of context-specific agroforestry systems that align with both biophysical and socioeconomic factors. Scaling up R. prinoides agroforestry and similar practices can play a critical role in meeting global climate-smart agriculture goals, offering a sustainable path for smallholder farmers to thrive in the face of climate change. Incorporating tree-based farming into agricultural practices not only boosts productivity but also helps mitigate climate impacts, making it a key strategy for building resilient and sustainable agricultural systems worldwide
Effect of intra-row spacing and NPS fertilizer rates on growth and bulb yield of onion (Allium cepa L.) in Saharti District, South Eastern zone of Tigray, Ethiopia
No full textOnion (Allium cepa L.) is one of the most important vegetable crops cultivated under irrigated conditions in the southeastern zone and some parts of the other region; the Tigray. The cultivation of onions requires proper supply of plant nutrients and plant densities. Despite of several constraints linked with onion production and productivity Inappropriate application rates of NPS fertilizer and inappropriate plant densities are one of the major constraints for onion production and growth in the study area. Therefore, this study was initiated with the aim of to determine Effect of intra row spacing and NPS fertilizer rates on growth and bulb yield of onion in Saharti District, South Eastern zone of Tigray, Ethiopia. The experiment was arranged in factorial combination of four level of intra row spacing (5, 7.5,10 and 12.5 cm) and four NPS fertilizer rates (0,150,200 and 250 kg ha -1) in a Randomized Complete Block Design with three replications. Growth and bulb yield components of onion data were collected and analyzed using GenStat software 18th edition. The analysis of variance showed that intra row spacing and NPS fertilizer had significant effect on days to physiological maturity, leaf length, leaf number per plant, bulb length and bulb diameter. The interaction effect of intra-row spacing and NPS fertilizer had significant effect on plant height, average bulb weight gram per plant, marketable bulb yield, unmarketable bulb yield, and total bulb yield. The highest marketable bulb yield 38.5 t ha-1 was obtained on the combined application of 200 kg ha -1 NPS fertilizer rate with 5 cm intra-row spacing. The highest net benefit (ETBirr 1,843,300) with the highest of Marginal rate of return (2942 %) was obtained on the combined application of 200 kg ha-1 NPS fertilizer rate with 5 cm intra-row spacing. Accordingly, onion producers in Saharti District and similar agro-ecologies can adopt the combination of 5 cm intra-row spacing and 200 kg ha-1 NPS fertilizer to achieve high marketable bulb yields, maximize net benefits, and obtain high marginal rates of return. However, as this study was conducted in a single location and season using the Bombay Red onion variety, further research is necessary to validate these findings across various seasons, locations, and with different improved onion varieties
Improving Yarn Quality Through Process Optimization using the Taguchi Approach and GRA (Case study: MAA Garment and Textile Company)
No full textIn today’s competitive textile market, yarn quality plays a critical role in ensuring product performance, reducing waste, and maintaining customer satisfaction. This study focuses on improving yarn quality in the carding machine section of MAA Garment and Textile Company by optimizing key process parameters using the Taguchi Method and Grey Relational Analysis (GRA). The research identifies and investigates the influence of four key carding parameters: cylinder speed, flat speed, cylinder-to-doffer gauge, and cylinder-to-flat gauge on yarn imperfections such as neps, thick places, and thin places. A Taguchi L9 orthogonal array was used to design controlled experiments, and GRA was applied to handle multiple quality responses simultaneously. The analysis revealed that flat speed has the most significant effect on yarn imperfection. The optimal parameter settings (CS = 780 rpm, FS = 260 mm/min, CTD = 0.15 mm, CTF = Level A) led to substantial reductions in yarn defects. The confirmation test validated these findings, showing a significant improvement in yarn quality, as the Grey Relational Grade (GRG) increased from 0.41 to 0.61. The study demonstrates that a systematic, data-driven approach can effectively enhance yarn quality while minimizing experimentation cost and time. The findings provide valuable insights for textile manufacturers aiming to implement robust quality improvement strategies in their spinning processes
Magnitude and Determinants of Maternal Complications during Pregnancy and Post-Partum in Ethiopia: A Survey Study using PMA Data
No full textBackground: A maternal complication is a physical or mental issue that affects the mother's health, the fetus's health, or both. Even women who were healthy before getting pregnant can experience complications. These complications may make the pregnancy a high-risk pregnancy. All pregnancies are at risk. According WHO (world health organization) most of the complications develop during pregnancy and most are preventable or treatable. Other complications may exist before pregnancy but are worsened during pregnancy. In Ethiopia the these complications were the major direct obstetric complications
Objective: To determine the magnitude and determinant factors during pregnancy and postpartum complications data from PMA Ethiopia
Methods: Performance Monitoring for action (PMA) surveys are a prospective cohort survey based on a multistage stratified cluster sampling design with urban-rural stratification. The sample size of this study is 1678 and the study population was women’s who have pregnant or women 0-4 weeks of postpartum. The magnitude of complications during pregnancy and postpartum period will be computed by using STATA 17 software. Multivariable logistic regression analysis was used to control confounding variables at the p-value < 0.05 and the strength of the statistical association with maternal complication during pregnancy and post partum was measured by using adjusted odds ratios and ` 95% confidence intervals.
Result: magnitude of maternal complication during pregnancy and postpartum is 37.31% and38.74% respectively. Women who have develop a complication both during pregnancy and post partum were 18.3%. Women who have completed the higher education [AOR =0.191, 95% CI: (0.093, 0.392)]. A woman who has a grand multi Para [(AOR = 0.662, 95 % CI: (0.442, 0.993)]. Women’s who have obtain ANC follow up[AOR =0.758, 95% CI: (0.573, 1.004)]. Women with twin pregnancies [(AOR = 1.97, 95 % CI: (0.974, 3.963)] these factors associated with maternal complication during pregnancy. Living with a man [AOR = 2.453, 95% CI: (1.214, 4.957)]. Women who attended greater than 4 ANC follow up [AOR = 0.727, 95% CI: (0.526, 1.006)]. Women with twin pregnancy [AOR = 3.596, 95% CI: (1.225, 10.556)]. Postpartum visit [AOR = 0.682, 95% CI: (0.482, 0.965)] these factors associated with postpartum complication.
Conclusion: Maternal complication during pregnancy and postpartum in Ethiopia was found to be major maternal health issue. Being living with a man, uneducated mother and their life partners, twin pregnancy, absence of post natal visit and low ANC visit were important predictors of maternal complications during pregnancy and postpartum period. By implementing targeted interventions to address the identified maternal complications, focusing on high - risk areas and populations to improve maternal health outcomes
Dairy Value Chain Analysis and its Challenges: The case of Raya-Alamata Woreda, Southern Zone, Tigray Regional State
No full textIn Raya-Alamata, Tigray Ethiopia, dairy is recognized as a multifunctional livelihood activity. However, the sector is not well integrated with market systems and other value chain functions, leaving the associated challenges and opportunities unclear. This study aims to examine the dairy value chain and its challenges in Raya-Alamata. Data were collected from 155 respondents, including producers, retailers, and consumers, using a household survey. The collected data were analyzed using descriptive statistics and a probit model. The results indicate that the dairy value chain faces several constraints, such as inadequate feed, which reduces milk production, and animal diseases that lower yields and negatively impact herd health. Limited access to credit and financial resources restricts farmers from investing in the sector, while inadequate veterinary services hinder effective disease management. Additionally, the absence of organized marketing channels and processing centers limits farmers' selling options and bargaining power, and low milk prices discourage expansion. The cost-benefit analysis of milk production reveals that producers incur an average cost of 32 birr per liter, selling it at 98.7 birr, resulting in a profit of 66.7 birr per liter. Retailers sell milk at 120 birr, earning 15.3 birr per liter after incurring monthly marketing costs of 429,272.2 birr. Producers add significant value at 67.5%, while retailers contribute 12.5%. This analysis underscores the profitability of milk production and the importance of understanding cost dynamics within the dairy value chain. Moreover, the probit model identifies several key factors influencing milk market supply. The age of the household head positively affects milk supply, as older producers tend to have more experience and better networks. Conversely, larger land sizes may decrease milk supply, likely because farmers diversify into other crops and livestock instead of focusing solely on milk production. Additionally, as consumer demand increases, producers are likely to boost their milk supply in response. Finally, improved access to market information enables producers to make informed decisions, leading to increased milk supply as they respond effectively to market trends
NATIONALISTIC TIGRIGNA MUSIC VIDEO CLIPS IN ‘DIMTSI WEYANE’ TV IN 2010-2011 E.C
No full textThe research aimed at studying Tigraian nationalistic music in terms of developing nationalism in Tigrai. It is a descriptive study type, which employed qualitative research approach to analyze the musical nature, ways of enhancement of nationalism and the roles of the music in development of nationalism. Data was gathered through document analysis from five music video clips that were selected using purposive sampling. Each music video clip was analyzed for nationalism features such as identity, temporal and spatial claims focusing on its lyrics (use or delivery of language), sound structure, melody, rhythms, instruments, performances (dances styles and costumes) and reception among the audience. The music were sound to be nationalistic in nature in terms of their language delivery, musical composition, performances, costumes and hairstyles in enhancing to describe nationalism . The music had also a substantial role in promoting and enhancing nationalism through their strong language delivery in their lyrics; using indigenous musical instruments and distinctive Tigraian melody and rhythmic structure; including acted and natural performances, that are unique to Tigraian people in their video clip, In doing so, the songs enhances the identity, temporal and spatial claims that the nationalism discourse is based on and are considered to be successful in inspiring the people to get together and protect its right for self-administration and self-governance. It is recommended that music writers and composers have to consider the basic elements of nationalism and incorporate them in every aspect of their songs. They also have to consider minimizing the influence of western musical instruments and encouraging the use of indigenous cultural instruments. The office of Tigrai culture and tourism, Tigrai educational institutions, language and culture research centres and national media have to study some role of the nature and contribution of music in building nationalism because it helps to establish a research and documentation center and to the preservation and documentation of nationalism music. Further study that includes more nationalistic music and data that are more comprehensive also recommended
EMOTION DETECTION AND CLASSIFICATION ON TIGRIGNA SOCIAL MEDIA TEXTS USING TRANSFORMER MODELS
No full textThe rapid growth of social media has reshaped emotional expression, producing large-scale digital data for social, cultural, and political analysis, thereby highlighting the importance of reliable automated emotion detection tools. Despite advances in Natural Language Processing (NLP), Tigrigna remains underrepresented, with existing multilingual models often underperforming due to limited annotated data, lack of tailored resources, and linguistic complexity. To address this gap, this study introduces transformer-based models tailored for emotion detection and classification in Tigrigna social media texts, focusing on four emotion categories: happiness, sadness, neutral, and disgust. A total of 4,000 Tigrigna sentences were collected from Facebook and YouTube and manually annotated with a high Inter-Annotator Agreement. To expand and balance the corpus, 6,000 additional sentences were generated using data augmentation techniques, including backtranslation and synonym replacement, resulting in a final dataset of 10,000 sentences. Following preprocessing, including normalization, tokenization, and cleaning, the data was split into training (8,000), validation (1,000), and testing (1,000) subsets. Three transformer-based models namely XLM-RoBERTa, tiBERT, and the Tigrigna-specific tiRoBERTa were fine-tuned and evaluated using Macro-F1, precision, and recall metrics to address class imbalance. The results demonstrated progressive improvements across models: XLM-R achieved an F1-score of 81%, tiBERT 84.4%, and tiRoBERTa 88%, with tiRoBERTa outperforming the others across all emotion categories, particularly in distinguishing subtle distinctions between sadness and happiness. Misclassifications between neutral and disgust persisted, reflecting data-related issues, model-specific challenges, and the low-resource nature of Tigrigna. Data augmentation improved F1-scores by 2–10% across models, underscoring its crucial role in enhancing performance in low-resource NLP tasks. The study concludes that transformer models, when culturally and linguistically adapted, are highly effective for Tigrigna emotion detection. Future research should expand Tigrigna-specific pretraining corpora, explore advanced augmentation, investigate hybrid architectures, and integrate multimodal data (e.g., combining text with images or videos). Applying these findings via APIs and dashboards can support researchers, policymakers, and organizations in leveraging Tigrigna social media for informed decision-making
FACTORS AFFECTING HUMANITARIAN LOGISTICS PERFORMANCE IN THE CASE OF THE RED CROSS SOCIETY, TIGRAI REGIONAL STATE, ETHIOPIA
No full textThe performance of humanitarian logistics is shaped by a dynamic interplay of internal and external factors that collectively determine the efficiency, responsiveness, and reliability of aid delivery systems. This study examined the case of the Tigray Red Cross Society (TRCS) to identify and analyze the determinants of logistics performance in crisis conditions. Data were collected from 145 participants, including managers, sub-coordinators, and operational staff, using instruments adapted from validated logistics performance assessment tools and prior empirical studies. A mixed-methods, cross-sectional survey design was employed, integrating qualitative insights with quantitative evidence. Multiple regression analysis confirmed that all the selected independent variables—donor funding, government support, infrastructure quality, and the availability of skilled personnel—had a statistically significant and positive influence on TRCS’s logistics performance. The findings demonstrate that effective humanitarian logistics is not the product of isolated activities but rather the outcome of a coordinated integration of internal processes and external enablers. Specifically, TRCS’s ability to align core practices such as procurement, inventory management, warehousing, and transportation with strong partnerships, government collaboration, and infrastructure utilization has substantially enhanced its operational efficiency and timely response capacity. The originality of this study lies in its context specific empirical evidence from a conflict-affected region, offering insights rarely captured in humanitarian logistics research. By emphasizing the role of institutional capacity-building, sustainable donor engagement, and strategic collaboration, the study positions TRCS as a potential model for resilient humanitarian logistics in resource-constrained environments. Recommendations include targeted investments in staff training, infrastructure upgrades, sustainable funding mechanisms, and stronger stakeholder linkages. Ultimately, the study contributes to both theory and practice by presenting a holistic framework for improving logistics performance that is adaptable to other humanitarian organizations operating in complex emergency settings