Industrial Engineering

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Improving Printing Process Efficiency by Identifying and Mitigating Production Delays through System Modelling and Simulation at Berhanena Selam Printing Enterprise
(Addis Ababa University, 2025-06) Getaw Yirga; Gezahegn Tesfaye (PhD)
In the competitive printing industry, operational efficiency is crucial to staying ahead. Efficient operations minimize downtime, reduce waste, and improve resource utilization, which directly impacts profitability and customer satisfaction. Operational efficiency also enables companies to be more agile and responsive to market changes, ultimately giving them a competitive edge in an industry where margins can be tight and customer expectations are high. The Overall Equipment Effectiveness of Berhanena Selam Printing Enterprise for the 2023/24 period, standing at 14.84%, indicates room for significant improvement in operational efficiency. In light of this evidence, it is crucial to propose a research agenda focused on identifying and mitigating production delays through system modeling and simulation approaches to improving operational efficiency. This study adopts a quantitative approach to enhance operational efficiency by analyzing job order processing data through system modeling and simulation. The study investigates the operational efficiency of the wave-offset and offset machines in a printing process by identifying key factors contributing to production delays: operating speed, machine failures, setup time, and make-ready time. Using ARENA software for simulation and analysis, various improvement scenarios were evaluated. Increasing machine capacity to 90% of design speed, reducing machine failure and repair times by half, and cutting setup and make-ready times by half were proposed as strategies to enhance efficiency. These actions resulted in improved Overall Equipment Effectiveness by 4.62% for the wave-offset machine and 28.73% for the offset machine, respectively.
Model development for Industry Extension Services in Small and Medium Enterprises to Promote Innovation and Technology Utilization: A Case study of Gulele Sub City Wereda 04 and 07.
(Addis Ababa University, 2025-06) Cherent Tsegaye; Merertu Wakuma (PhD); Micheal Getachew (MSc.)
Industry Extension Services (IES) refer to support programs designed to enhance the productivity and competitiveness of businesses and also plays a crucial role in supporting small and mediumsized enterprises (SMEs) by providing essential support mechanisms by collaboration with TVET trainers. Industry extension service elements consist of entrepreneurship, kaizen, technological and technical support. This studies concern on technology support ones only due to the wider concept of to address the others industry extension packages. Small and medium enterprises (SMEs) faces different challenges such as poor infrastructure, lack of appropriate marketing options, lack of integrated technology to increase their productivity and lack of financial options are the main challenges SMEs faces currently. The primary objective of this research is to identify and analyze any existing gaps in the technology support system of the case enterprise and develop a model for industry extension services on the promoting innovation and technology utilization within SMEs. It looks at how much these services help SMEs embrace and use technology in better way and techniques to improve their overall performance, productivity, and competitiveness. The research methodology involves conducting a comprehensive literature review, collecting, and analyzing quantitative and qualitative data on the main factors that affect the Industry Extension Services (IES) of the SMEs regarding technology support system. The collected data using both primary and secondary data collection methods was thoroughly analyzed using statistical software SPSS Version 26. The quantitative data was obtained from questionnaires administered to 102 respondents are participated that are 36 Trainer,4 deans ,42 SMEs workers,8 woreda experts and 12 SMEs owners are participated and their responses were analyzed using SPSS. The study's findings propose that Industry Extension Services (IES) for SMEs can solve different critical factors such as poor infrastructure, lack of market relations, and skill of SMEs workers to handle the technology effectively and efficiently and fostering innovation and technology utilization.so This study highly attempts to find possible weaknesses and opportunities for improvement in the current support systems provided to SMEs by critically evaluating the efficiency of industrial extension services due to promoting innovation and technology. The results of this study will aid in the development of more specialized and successful methods to assist SMEs in fostering innovation and the use of technology by policymakers, business professionals, and development organizations.
Predicting and Analyzing the Impact of Occupational Safety& Health on Labor Productivity: A Case of Ethiopia Plastic Industry
(Addis Ababa University, 2024-10) Feleke Workie; Kassu Jilcha (Assoc. Prof.); Ayele Legesse (Mr.) Co-Advisor
Back ground: the Ethiopian plastic industry occupational health and safety risks are negatively impact labours motivations and output. While the information of Ethiopian plastic industry occupational health and safety, such as a review of situational analysis and needs assessment and the impact of energy use on labour productivity in the industry, specially address how to predict or look into the relationship between worker productivity and OHS in Ethiopia plastic industry out of 396 employees of 70 target labours are take all. Objective: In order to create mitigation plans for preventive and corrective measures, the objective is to forecast and analyze the impact of OHS on labour productivity in EPI. Methods: the following techniques to be used to predict and assess how OHS would affect worker productivity in Ethiopia plastic industry. review of relevant literature: analyse the corpus of work on occupational health and safety in multinational industrial enterprises, with a focus on the plastic industry. This to give insight on the possibility, challenges, and state of the industry’s OHS protocols. Gatherings of data: gathering pertinent information on worker productivity, OHS metrics, and other Ethiopian plastic industry component. This data to be gathered through unstructured interview, primary and secondary data sources, and surveys, and then analysed the integration of all that are regression analysis and correlation analysis. Purpose: The aim of this study was to determine how worker productivity in Ethiopia plastic industries was affected by occupational safety and health. Results and discussion: According to the study's findings, the majority of workers are aware of how workplace safety and health affect labours productivity. Furthermore, the survey discovered that even though workers are aware of the risks to their health and safety at work, they often forget to wear personal protective equipment because they think it's too hot. The study comes to the conclusion that worker productivity is strongly impacted by occupational health and safety. In order to reduce workplace accidents and injuries, this study advises management to protect employees and supply them with personal protective equipment. In order to reduce workplace accidents and increase productivity, the study also suggests that management provide routine training and education on occupational health and safety issue.
Mitigating Fashion Obsolescence Risk through Transit Time Reduction: An Agent Based Modeling Study of Apparel Supply Chain
(Addis Ababa University, 2025-06) Mulugeta Fekade; Ameha Mulugeta (PhD)
The global fashion industry is experiencing rapid trend acceleration, with styles shifting every three to four months due to social media influence and fast fashion dynamics. This short lifecycle increase the risk of fashion obsolescence, especially for manufacturers in developing countries like Ethiopia, where delayed deliveries lead to missed market windows and financial loss.in the bole lemi special economic zone (BLSEZ), a major garment manufacturing hub, long transit times caused by inefficient logistics infrastructure, slow customs procedures, and underperforming logistics agents reduce the competitiveness of local manufacturers and threaten the zone’s ability to retain global investment. This study aims to mitigate the risk of fashion obsolescence by improving logistics responsiveness and reducing supply chain transit time within BLSEZ. A mixed methods approach was employed, including surveys, interviews, document review, and direct observation to assess the current logistics performance and stakeholder capacity. Based on this empirical data, an agent modeling technique was used to simulate and evaluate three improvement scenarios: introducing new logistics agents, improving the performance of existing agents by 10%, and combining both strategies. Each scenario was analyzed to determine its effectiveness in enhancing delivery speed and supply chain reliability. The results showed meaningful improvements across all scenarios, with scenario 1 achieving a 40.52% transit time reduction, scenario 2 yielding a 34.45% improvement, and scenario 3 producing the most significant result with a 58.74% reduction. A phased implementation is proposed: short term (within 1 year) incentives to attract competitive logistics firms, followed by medium and long term improvements in customs clearance infrastructure, technology use, and production speed reduce 58.74% obsolescence risk. These findings highlight the critical of integrated logistics strategies in aligning Ethiopia’s garment industry with the time sensitive demands of the global fashion market. The study provides evidence based insights for policymakers, and manufacturers seeking to enhance competitiveness through responsive supply chain systems.
Investigating the Influence of supply chain management practices on the sustainability of plastic industries: A Case Study of ENPLAST P.L.C.
(Addis Ababa University, 2024-10) Abera Aragie; Gezahegn Tesfay (PhD)
This study seeks to investigate the Influence of supply chain management practice sustainability of Plastic Industries through Recycling In the case of ENPLAST P.L.C. This research studied SCM in the area of supply chain integration, information sharing, customer relationship management, and internal lean practices. Explanatory survey design was used while a questionnaire was used to gather primary data. The study covered census of 66 employees of ENPLAST P.L.C. The study used questionnaire as primary data collection tool. The data collected was analyzed with the aid of descriptive statistical techniques such as frequencies, percentages and mean score. More so, correlation and multiple linear regressions were used to establish the relationship between study variables using Statistical Package of Social Sciences Version 22. The findings of the study revealed that the combined effect of various SCM practices influenced organizational performance positively. The correlation result shows that there is positive and significant relationship between all SCM practices (supply chain integration, information sharing, customer relationship management, and internal lean practices) and organizational performance. The result of regression also revealed that all predictor variables (supply chain integration, information sharing, customer relationship management, and internal lean practices) have statistically significant contribution on organizational performance. The adjusted R² of 0.502 indicates 67.2% of the variance in organizational performance can be predicted by SCM practices of the company. Thus, it can be concluded that improved SCM practices are significantly influencing organizational performance. Therefore, the management of ENPLAST P.L.C. Share Company should influence its supply chain integration, information sharing, customer relationship management, and internal lean practices as a way of improving the company performance.
Application of Green Lean Six Sigma (GLSS) through DMAIC Approach: A Case of Walia Steel Industry (WSI)
(Addis Ababa University, 2025-06) Seble Negash (PhD); Yitagesu Yilma (PhD); Birhanu Tolosa (Mr.) Co-Advisor
In today’s manufacturing world, producing high-quality products while reducing waste and environmental harm is increasingly critical. This study explores the application of Green Lean Six Sigma (GLSS) an integrated framework combining Lean principles, Six Sigma methodologies, and sustainability practices within the Walia Steel Industry (WSI), a major steel profile manufacturer in Ethiopia. The research applies the DMAIC (Define, Measure, Analyze, Improve, Control) approach to assess and address rising product defects, which increased from 2.34% in 2022/23 to 3.06% in 2023/24, alongside growing material waste and emissions. A mixed-method case study was employed, drawing on production records, interviews, and observational data. Analytical tools such as Pareto charts, Material Flow Analysis (MFA), simplified Life Cycle Assessment (LCA), fishbone diagrams, and the 5 Whys method were used to identify and analyze key defects in CHS, RHS, SHS, and LTZ products. Root causes were traced to poor machine calibration, substandard raw materials, and inadequate storage conditions. The process capability assessment revealed a DPMO of approximately 10,213, corresponding to a Sigma level of 2.6 for without 1.5σ shift and 3.8 for with 1.5σ shift. MFA projected 149.83 tons/year of material waste, while LCA estimated this waste contributes approximately 45 tons of CO₂e emissions annually. Additionally, Lean wastes particularly Defects, Waiting, Motion, and Overprocessing were conceptually mapped using the TIMWOOD framework, based on qualitative observations. As a result, the study proposes a tailored GLSS-based conceptual framework designed to reduce defects by an estimated 46.7%, potentially lowering CO₂e emissions by 21 tons/year. The framework integrates Lean waste reduction, Six Sigma quality control, and Green sustainability tools across all DMAIC phases. This research fills a critical gap in the literature by demonstrating how GLSS can be applied in developing country contexts like Ethiopia to drive operational efficiency and environmental performance. The findings offer a scalable model for sustainable manufacturing applicable to similar industrial settings.ment.
Enhancing Competitiveness Through Value Chain Analysis in Case of Abyssinia Integrated Steel plc.
(Addis Ababa University, 2025-06) Nardos Mekoya; Ameha Mulugeta
The thesis investigates the significant challenges of rework waste and productivity inefficiencies at Abyssinia Integrated Steel Manufacturing, a prominent Ethiopian producer of rebar. Over the period from 2013 to 2015, the company experienced an average rework waste of 6,500 kg annually, underscoring the critical need for systematic improvements within its production processes. The primary objectives of this research are twofold: first, to conduct a comprehensive Value Chain Analysis (VCA) to identify key inefficiencies across the production stages; and second, to develop strategic interventions aimed at enhancing competitiveness and operational performance. The study employs a mixed-methods approach, integrating qualitative insights from interviews with production and quality control staff, alongside quantitative data analyzed using PROCAST simulation software. This software facilitates detailed modeling of thermal stress and solidification behaviors during the continuous casting process. The findings reveal that the improper control of casting parameters, particularly temperature and speed, is a major contributor to defect rates. Specifically, the research identifies an optimal casting temperature range of 1650°C to 1700°C and a casting speed of 1.5 m/min as critical conditions for minimizing turbulence and ensuring effective solidification. These parameters significantly reduce the incidence of defects, such as longitudinal and transverse cracks, which have plagued the production process. In conclusion, this study underscores the importance of integrating VCA with predictive simulation tools to create a robust framework for quality control and operational decision-making. By systematically identifying and addressing inefficiencies, Abyssinia Integrated Steel can enhance resource utilization, improve worker safety, and bolster its competitiveness in both domestic and international markets. The implications of this research extend beyond the case study, providing a valuable framework for other manufacturers in developing countries aiming to align production efficiency with quality standards through data-driven and strategic interventions. This approach not only contributes to operational excellence but also supports sustainable manufacturing practices in the steel industry.
Enhancing a Vehicle Competency Assurance Service in Case of Addis Ababa City Administration Driver & Vehicle License & Control Authority (DVLCA).
(Addis Ababa University, 2024-06) Berhe Tesfakiros; Gezahegne Tesfaye (PhD); Sharmarke A. (Mr.) Co-Adviser
The Addis Ababa City Administration Driver & Vehicle License & Control Authority (AA-DVLCA) has a lot of problems and inefficiencies when it comes to providing services for vehicle competency assurance. The efficacy and efficiency of vehicle inspections are significantly impacted by problems including antiquated equipment, a shortage of skilled workers, and ineffective processes. Longer inspection periods and lower service quality are caused by these issues, which increase the risk to public safety and erode customer happiness. The study uses both qualitative and quantitative research approaches to address these problems. Site visits, semi-structured interviews, and document analysis are some of the techniques used to gather data with the goal of comprehending existing issues and seeing areas for change. In addition, a discrete event simulation model is created to assess the functionality of the current system and suggest improvements. In order to simulate numerous scenarios and evaluate their effects on system performance and service quality, the model includes a variety of factors and variables. The results of the study show that by modernizing inspection methods and maximizing resource utilization, considerable improvements in inspection times and service standards can be attained. Purchasing state-of-the-art inspection tools, improving staff development initiatives, and putting in place thorough quality control protocols are among the main suggestions. The report also emphasizes how crucial it is to build ongoing feedback systems and include stakeholders in order to guarantee long-lasting advancements in vehicle competency assurance services. It is anticipated that these actions will greatly improve the effectiveness, dependability, and general caliber of services rendered by the AA-DVLCA.
Developing a Decision Support System for Spare Parts Inventory Management to Reduce Repair Cost at Sunshine Construction.
(Addis Ababa University, 2024) Biruk Gebremedhine; Ameha Mulugeta (PhD); Ayele Legesse (Mr.) Co-Advisor
The research aims to develop a decision support system (DSS) for spare parts inventory management in order to reduce maintenance costs at Sunshine Construction Company. The study employs a well-designed approach, incorporating data analysis techniques and leveraging DSS systems to gain insights for optimizing inventory management and reducing repair costs. The literature review examines inventory management in the construction industry, focusing on areas like optimizing stock levels, lead-time, decision support systems, maintenance, and repair cost control. It explores strategies such as (s, S) and (q, r) policies, modern inventory management technologies, and the importance of collaboration among stakeholders. A critical issue identified in the review is the need to address the challenge of inaccurate demand forecasting, which can significantly impact inventory optimization efforts. The data collection and analysis used both quantitative data from a case company concerned department recording data like inventory levels, repair costs, maintenance costs) and qualitative data (through interviews). Tools like Excel, FMEA, and the EOQ model are used to analyze and optimize factors like stock levels, lead times, reorder quantities, and safety stock. The expected findings and recommendations aim to improve inventory performance, reduce costs, and promote business success in spare parts management at Sunshine Construction Company. The study aims to contribute innovative solutions related to demand forecasting, inventory policies, maintenance cost control, and technology integration
Developing a Predictive Maintenance Model for Addressing Underfill in Heineken Brewery’s Share Company
(Addis Ababa University, 2024-10) Ruth Wondosen; Ameha Mulugeta (PhD); Natnael Mekonnen (Mr.) Co-Advisor
Predictive maintenance (PdM) is crucial for enhancing operational efficiency and reducing downtime in industrial processes. This study introduces a novel approach to developing a predictive maintenance model for addressing underfilling issues in the bottling processes of Heineken Company, which significantly impact revenue and product quality. Unlike previous works that rely solely on historical data, this research incorporates synthetic data generated using Conditional Generative Adversarial Networks (cGAN) to overcome data limitations and enhance model robustness. The methodology involved comprehensive data preprocessing, including imputation and feature engineering, to prepare the dataset for training a Random Forest classifier. The model development was refined through hyperparameter tuning via Grid Search and validated using cross-validation. The results demonstrated a strong predictive capability, with a training accuracy of 90.67%, test accuracy of 90.21%, and cross-validation accuracy of 90.89%, indicating reliable generalization. The use of cGAN contributed to increased data variability, mitigating overfitting and ensuring realistic model training scenarios. This study advances the field of predictive maintenance by demonstrating how synthetic data can augment limited datasets to improve model accuracy and resilience. Integrating this model into the production line enables proactive maintenance scheduling, reducing disruptions and enhancing product consistency. Future work will focus on expanding the model's scope to incorporate real-time sensor integration for adaptive learning and exploring ensemble models, such as hybrid Random Forest and LSTM architectures, to handle temporal patterns and further optimize predictive performance.
Improving Operational Performance by prioritizing Lean Maintenance Tools: A Case Study of Reppie Waste-to-Energy Power Generation Plant
(Addis Ababa University, 2024-10) Kefyalew Lemu; Gezahagn Tesfaye (PhD)
The main purpose of this research is to improve operational performance in waste-to-energy (WTE) plant facility by prioritizing lean maintenance tools. Waste-to-energy power plants are complicated systems that need several maintenance strategies to be available and efficient in all of their functionalities. The Operational performance; availability, efficiency, quality maintenance and maintenance costs of the WTE plants are significantly impacted by maintenance performance. The shortcomings of WTE facilities' lifetime maintenance could lead to higher production costs, a decrease in ability to compete, increased downtime, and a higher mean-time-failure rate. This study aims to improve operational performance by applying the selected Lean Maintenance Tools (LMT) framework in the case company. Data relevant to the research was collected among employees in different positions within the organization to evaluate the potential for operational performance improvement using designed questionnaire, informal interview, direct observations, and company records. The reliability and validity of the survey findings were confirmed through a triangulation approach, incorporating various data collection methods. In order to analyze the collected data from primary and secondary sources, the researcher has used descriptive analysis method such as Analytic Hierarchy Process (AHP), SPSS software and Pareto diagram. The selection of lean maintenance tools can help identify and address potential waste areas in equipment failures by prioritizing lean tools in maintenance strategies. AHP tool prioritization of LMT and operational dimension has been calculated. The most prioritized lean maintenance tool on the survey is TPM while the least emphasized tool is Kanban system. The findings of this study supports the promotion of sustainable operation, waste management practices, reduced maintenance cost and increased renewable energy production efficiency. The researcher then selected the top five LMT above listed that can address significant impact in affecting operational performance and finally proposed a new implementation framework including operational procedure and action plan that are going to be practiced.
Enhancing Railway Infrastructure Protection through System Dynamics Modeling and Analysis: A Case of the Ethio-Djibouti Railway
(Addis Ababa University, 2024-06) Getahun Kebede; Birhanu Beshah (PhD); Mulatu Tilahun (Mr.) Co-Advisor
The railway infrastructure in Ethiopia faces significant threats from natural disasters, human-made destruction, and technical failures. Reports indicate a concerning trend of frequent theft and vandalism incidents targeting critical railway components, which disrupt service, compromise safety, and incur substantial financial losses. This study aims to develop a comprehensive system dynamics model to identify the risks and challenges associated with protecting the Ethio-Djibouti Railway (EDR) infrastructure and propose effective mitigation strategies. The research employs a mixed-methods approach, combining qualitative and quantitative data gathered through expert interviews, questioners and literature review. A system dynamics model is constructed to capture the key variables and their interrelationships affecting railway infrastructure protection. The model is used to simulate different scenarios and test the effectiveness of interventions. The findings reveal that the selected Exogenous variables “community empowerment and awareness creation, accidents on domestic animals, and population density” have a great impact on the entire infrastructure security. Those variables are found to be effective in minimizing accidents, train delay time and blockages, and overall infrastructure damage. The study also highlights the impact of population density, where highly populated areas tend to experience increased theft and vandalism, leading to more train delays. In Addition to that this research also recommended and showed in the system dynamics model, Implementing various surveillance mechanisms, such as technology-enabled monitoring, can significantly reduce the incidents of theft and vandalism. By integrating Crime Prevention Through Environmental Design (CPTED) principles with system dynamics modeling, this research provides a holistic framework for improving the overall safety and security of the EDR infrastructure. The study's recommendations serve as a valuable resource for future studies, policymakers and railway operators to develop and implement targeted interventions to safeguard railway infrastructure.
Investigating the Impact & Predicting Occupational Safety & Health in Metal Manufacturing Firms: A Case Study of Addis Machine & Spare Parts Manufacturing Industry
(Addis Ababa University, 2024-10) Woubeshet Kebede; Kassu Jilcha (Assoc. Prof.); Shemelis Nesibu (Mr.)
Occupational safety and health practice in the manufacturing industry appears to be relatively low, as evidenced by observations and writings from various scholars regarding the problems in case company working environments. This study aims to examine, the impact of Occupational safety and health (OSH) which ultimately affect the overall performance of metal manufacturing industry. A random sampling method was used to select 147 participants with combination of primary and secondary data sources. The collected data were analyzed & interpreted using IBM SPSS Version 27 software. The study's analysis results indicate that, the impact of OSH challenges includes: 62.1% reporting workplace health and safety issues, 66.3% experiencing high safety exposure rates, 56.5% expressing job dissatisfaction, and 72.6% noting inconsistent use of PPE and lack of safety equipment. Only 27.4% reported adequate provision of PPE in the workplace. Conversely, from 2020 to 2022, there were 405 sick leaves (168 male, 237 female) and 434 absences (112 male, 322 female), attributed to long work hours, frequent machine breakdowns, inadequate use of PPE, worker reluctance, and insufficient health and safety controls. In the same way, based on the observed data of health & safety (HS), the predicted values injury rate range from 1.54 (lower risk) to 3.81 (higher risk), reflecting varying levels of health and safety risk associated with dependent variable. Additionally, the mean predicted injury rate of 2.59 indicates a moderate level of health and safety conditions, with values below 2.59 requiring urgent action. Moreover, study found the dependent variable can be expressed by independent variable with R2 =80.7%, Adjusted R2=79.4%, F-statistics (8, 88) = 61.3, P= 0.001 and giving the number of independent variables providing an explanatory estimate to the model. Furthermore, issues like lower safety & health rules & regulations, lower use of essential equipment, high injury rate on leg, shoulder, head, ear & human resource system problems. The study identified only one statistically significant independent variable among six, yet the cumulative results still yield reliable predictions for health and safety. However, a limitation of the study is that, it did not address the impact of all variables. The overall result of the study might give beginning point for researchers, academicians & policy makers to further elaborate and develop mitigation strategies in enhancing workplace health & safety practice in manufacturing industry. The study emphasizes improvement strategy aiming to create safer & more productive environment, strong safety practice, reduce accidents & enhance safety culture.
Work place Ergonomics Assessment and its Impact on Social Sustainability in Garment Manufacturing: a Case Study of Senmul Garment Manufacturing.
(Addis Ababa University, 2024-10) Tagesse Amtachew; Kassu Jilcha (Assoc Prof.); Shemelis Nesibu (Mr.) Co-Advisor
Workplace ergonomics in garment industry relates to the arrangement of workplaces, tools, and equipment that are arranged to fit and align with the skills of the workers, and its objective is to create workplace and work activities that are fit for the employee. Ensuring employee health and well-being is important to social sustainability in garment manufacturing industry. In addition to this, the research is mainly focused on an assessment of the existing workplace ergonomics in Senmul garment manufacturing. The main aim of this study is to evaluate and identify workplace ergonomics based on existing ergonomic practices and their impacts on social sustainability in Senmul garment manufacturing. The methodology includes a comprehensive literature review, collecting and analyzing qualitative and quantitative data’s. The data has been gathered by using both primary and secondary data from site visit assessments, selected grouped interviews discussions, company data reviews, organized questionnaires, interviews, document reviews. In addition to this, the study uses the REBA rapid entire body assessment soft wares and MS Excel and Visio software to analyze the research and to find the hazards of musculoskeletal disorders occurring at workplaces. Result from the study employees at senmul garment manufacturing face high risk of job related ergonomic hazards injuries and social sustainability in work ethics, work environment, community relationship, health and safety, human rights In order to address these problems implementing suggested strategy mechanisms for the improvement of workplace ergonomics such as a compressive ergonomics program in routine evaluation, continuous monitoring to support social sustainability, investing in ergonomics trainings for the managers and employee and focus on ergonomics risk identification and the social sustainability objectives of the industry that employee rights, encouraging ethical labor practices, crate standard working hours and enhancing the employee quality of life these makes a more ethical industry. Moreover implementing ergonomic interventions like job rotation schedules, adjustable workstations, and task and tool design can reduce musculoskeletal disorder.
Vehicles Characteristics and Their Implication on Fleet Management Performance: A Case of East Africa Bottling S.C (EABSC)
(Addius Ababa University, 2025-02) Tesfamichael Assefa; Kassu Jilacha (PhD)
Effective fleet management is essential for organizations to enhance operational efficiency, achieve cost savings, and promote sustainability in transportation and logistics. Notably, logistics costs can account for 10% to 30% of a manufacturing firm's overall expenses, with transportation comprising about 50% of total distribution costs. This study focuses on the impact of various vehicle characteristics on fleet management performance at East Africa Bottling S.C. (EABSC), examining factors such as fleet aging, vehicle mass, fleet size, standardization, commonality, and wheelbase. Utilizing a mixed-methods approach, the research combines primary data from questionnaires with secondary data from academic and industry sources, employing quantitative analyses like regression and correlation to explore the relationships between vehicle characteristics and fleet performance. The study also develops a Capacitated Vehicle Routing Problem (CVRP) optimization framework that incorporates these vehicle characteristics to enhance fleet optimization accuracy. Findings indicate that fleet aging, fleet size, fleet standardization, and fleet commonality significantly affect overall fleet performance. On the other hand, vehicle mass affects the fleet performance moderately. Vehicle height and vehicle wheel base has low significant on the performance. The optimization results suggest that integrating vehicle characteristics into the CVRP model can improve the fleet composition to meet a delivery demand of 80 million cases while adhering to a cost target of 150 million from 164 million. Recommendations include implementing effective maintenance practices, optimizing fleet usage, and aligning fleet strategies with organizational goals. This research contributes to existing knowledge by clarifying how vehicle characteristics influence fleet management performance and emphasizing their importance in transportation and logistics system design.
Customer-Oriented Product Development: A Case Study at Yirgalem Addis Textile Factory Plc.
(Addis Ababa University, 2017-03) Yonas Habtu; Kassahun Yimer (PhD)
The success of a product or service largely depends on how they meet the customers' needs and expectations. This thesis work employs Quality Function Deployment methodology to translate customer needs and requirements into the quality characteristics to improve quality for an existing product and to develop a new consumer product. Quality Function Deployment is a management tool that provides a visual connective process to help teams focus on the needs of the customers throughout the total development cycle of a product or process. It provides the means for translating customer needs into appropriate technical requirements for each stage of a product/process‐development life‐cycle. It helps to develop more customer‐oriented, higherquality products. The study was conducted in a case company called Yirgalem Addis Textile. The study used focus group discussion and questionnaire to identify customer needs of Yirgalem Addis Textile product of men’s t-shirt and based on the result of the survey, fifteen customer needs and product technical requirement were identified. In order to identify the most prominent customer needs and product technical requirement, the data were analyzed using Quality Function Deployment approach and Pareto chart. It was revealed in the study that Yirgalem Addis Textile failed in terms of meeting the needs of customers of men’s t-shirts and so as to alleviate those problems, the study recommends to use Quality Function Deployment as a means to meet customers’ need and facilitate means of communications between each department of the company.
Assessing and Enhancing Service Quality in the Transport Sector: Case of Addis Ababa City Bus Service Company (AACBSC)
(Addis Ababa University, 2024-06) Kalkidan Bekele; Gulelat Gatew
Service quality in the transport industry sector is crucial in one’s country socio, economic and political aspects evaluated to ascertain the level of service provided to customers. This study focuses on determining the impact of service quality dimensions on customer satisfaction and loyalty within this sector. The research was conducted in Addis Ababa, under the four terminals: Addis Ketema (Mercato), Leghar, Piassa (Menelik), and Megenagna. The study involved 138 participants who were surveyed using SERVPERF and Kano model questionnaires to assess service performance and prioritize customer needs. Descriptive analysis was carried out using Statistical Package for Social Sciences (SPSS) software to evaluate service performance. The findings revealed a low performance across all service quality dimensions, with reliability being identified as the most severe compared to others. This indicates that customers perceive a significant gap in the consistency and dependability of the service provided. The Kano model analysis further categorized service attributes, where five attributes fell under the "Must be" category. These attributes were critical to customers and were deemed essential for their basic satisfaction. These findings were then utilized as inputs for the House of Quality (HOQ) framework to translate customer requirements into actionable service improvements. The HOQ methodology, through its relation and correlation matrices, was employed to establish proposed solutions aimed at enhancing the identified service quality dimensions. The proposed solutions focused on improving shortcomings dimensions prioritizing reliability and other critical service attributes to meet customer expectations and improve overall service quality. This paper contributes to the ongoing efforts to understand and enhance service quality in the transport industry, providing a comprehensive analysis and practical recommendations for service improvement
Modeling the Integrated Impact of Total Quality and Knowledge Management on Production Efficiency: A Case of ASKU PLC Aquaddis Spring Water
(Addis Ababa University, 2024-10) Mekdes Ayalew; Gezahegn Tesfaye (PhD); Mulatu Tilahun (Mr.) Co- Advisor
This study required to modeling the Integrated Impact of Total Quality Management and Knowledge Management on Production Efficiency on ASKU PLC'S Aquaddis spring water production efficiency. Aligning TQM with Knowledge management involves creating a holistic approach that emphasizes shared goals, employee engagement, continuous improvement, and effective knowledge sharing. By integrating these practices, organizations can enhance their production efficiency. The study adopts descriptive research method. While analyzing the problem, both qualitative and quantitative research method are utilized. The main tools of data collection are questionnaires and interviews. The quantitative data collect through questionnaire analyzes by creating and practicing of inferential statistics using SPSS version 20 software. The performance measurement variables and their effects on production efficiency dimensions are analyzed by involving appropriate parametric statistical methods to determine the level of association and degree of relationship based on the distribution of the collected sample data. The results of the study show a positive and strong correlation between integrated knowledge management and total quality management and overall production efficiency. The research contributes to the body of knowledge by analyzing the effects of knowledge management integration along with quality management ideas, which are helpful for increasing production efficiency. Therefore, the researcher highlights the problems involved in a very weak customer focus, employee involvement and integrated system, continuous improvement and other related activities that have to do with a production efficiency. In order to examine the links between dependent and independent variables correlation analysis was performed. The correlation matrix showed that all independent variables had positive coefficients of correlation and significantly correlated with the dependent variable. Further regression analysis was also conducted and results revealed that all the independent variables contribute to statistically significant level at (p-value = 0.001). When effectively combined, these two management practices create a powerful synergy that enhances production efficiency. Limits of the current research sample size the sample is too small, it might not be representative of the broader population, leading to issues with the generalizability of the results. Future studies should aim to include larger and more diverse populations to enhance the generalizability of the findings.
Supply Chain Performance Measurement and Framework Development Case Company: Ethiopian Airlines- Tool Engineering Section
(Addis Ababa University, 2018-06) Melaku Debas; Gulelat Gatew (PhD); Haileluel Mamo (Mr.) Co-Advisor
The purpose of this paper is to present “Supply Chain Performance Measurement (SCPM) and Framework Development in case of Ethiopian Airlines -Tool Engineering section using Supply Chain Operation Reference (SCOR) model”. The business environments of the aviation industry maintenance organizations are heavily related to the performance of the supply chain networks and the supply chain performance measurement metrics. Aircraft maintenance stations are competing and measured each other through: on time accomplishment of maintenance tasks, readiness of aircraft for dispatch, customer satisfaction, and secureness of safety and working environment. Ethiopian Airlines-Maintenance Repair Overhaul (MRO) is one of aircraft maintenance service provider company, but some sections affected with lack of supply chain performance measurement system. From the past half year report and from the secondary collected data - Tool Engineering section is one of the most responsible section for aircraft delay, tasks carryover, customer dissatisfaction, weak inventory management system, material and information distortion are highly occurred from other supporting sections. Hence; this research focuses on to illustrate impact of supply chain performance measurement metrics and framework development to enhancing profitability of the company and prevent the problems encounters in Ethiopian Airlines- Tool Engineering section. To do this qualitative and quantitative data’s had been obtainable from internal and external customers, suppliers and from inter-departments. Based on the research, Supply Chain Operation Reference (SCOR) performance measurement model with pair-wise comparison of Analytical Hierarchy Priority (AHP) methodology has been developed to enhance the section performance and its supply chain measurement system. The developed framework of SCOR with AHP has been proposed, to contribute on tool engineering supply chain performance measurements and metrics enhancement on the company productivity. The proposed framework is used on tool engineering section supply chain performance measurements. However, the developed measurement and framework also could be consumed in other aviation sub-sections and industries by customizing the SCOR+AHP modules.
The Determinants and Business Impact of Additive Manufacturing Technology Adoption: A Case of Ethiopian Metal Manufacturing Industries
(Addis Ababa University, 2024-06) Amanuel Haile; Eshetie Berhan (PhD); Behailu Kemaw (Mr.) Co-Adviso
Additive Manufacturing (AM) technology, also called 3D-printing, is a disruptive technology providing opportunities and huge potential benefits through innovative way of manufacturing products. This study is concerned with identifying the determinants for adoption of Additive Manufacturing technology within Ethiopian metal manufacturing industries. In light of this objective, the study adopts both quantitative and qualitative approaches with purposive sampling. The quantitative approach used 7-likert scale questionnaire for empirical analysis of the data to determine the factors that influence the adoption of AM technology. For the qualitative approach, an interview is conducted to determine the business impact and the challenges of adopting AM technology. A sample of team leaders, engineers, metal researchers, technicians, IT professionals and quality controllers is taken to capture their opinions, views and reflections about the determinants for adopting AM technology in metal manufacturing industries. A self-administered questionnaire is used to rate the influence of technological, organizational, and environmental determinants on the decision to adopt the technology. Both SPSS and SmartPLS software tools are used for descriptive statistics analysis and structural equation modeling (SEM) of the collected data respectively. Results indicate that out of the determinants, the perceived value, perceived cost, top management support, organizational readiness, external pressure and perceived outside support affecting significantly a decision for adopting AM technology. The study further explores the benefits, potential business impact and the challenges of adopting AM technology in metal manufacturing industries. This study's contribution is to provide academics, business people and policymakers with insightful information about the determinants that influence AM technology adoption and its benefits enabling them to implement the necessary initiatives or policies that are essential for the technology to be adopted successfully. Lastly the study recommends further research in this field.

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