Industrial Engineering

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    Cluster Development for Metal Work Industries: Case Study on Addis Ababa Micro and Small-Scale Metal Work Industries
    (Addis Ababa University, 2011-11) Tariku Tamiru; Daniel Kitaw (PhD); Gulelat Gatew (Mr.)
    The contribution of micro, small and medium Scale industries towards employment generation, alleviation of poverty and inequalities and development of backward areas is recognized worldwide. Although, these industries have great role in economic development of our country, they doesn‟t benefit as their potential due to their problems related to their size. Most of the problems are lack of: market, skilled manpower, working capitals, information and low level of competitiveness. In addition there is lack of cooperation among themselves, which limits sharing of resources between them. Micro and small industries clustering is a group of these industries, producing similar products, located in a geographical proximity, sharing resources (like knowledge, technology etc) among themselves in order to overcome their internal and/or external challenges, and that compete each other but also cooperate with one another. The study is concerned on cluster development of micro and small metal work industries in Addis Ababa city. It covers 32 micro and small scale metal work industries selected from all sub cities with the objectives of developing micro and small metal work industry cluster to create a conducive environment for the development of inter-firm cooperation, improve the competitiveness of the industries, to solve marketing problems of the industries, and to facilitate metal work technology transfer to the country. For the accomplishment of the objectives of the study the selected industries were assessed through questionnaires, interviews and observation. The results obtained from the survey shows that Addis Ababa micro and small metal work industries faced with the following problems. These were:- lack of: market, product displaying area (marketing area), working capital, technical training, trust among the metal working industries; and flexibility of price and quality of raw materials. In order to solve the observed problems with the support of published and unpublished literatures the study proposed the development of micro and small metal work industry cluster and identifies suitable cluster location in the city. Taking into consideration of other countries experiences, for realization of the benefits of developed metal work industry cluster it should be suggested that to properly cooperate all collaborators of the cluster.
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    Reverse Logistics Network Development for E-Waste Management in Ethiopia
    (Addis Ababa University, 2023-10) Zeritu Agegnehu; Ameha Mulugeta (PhD)
    This research is aiming to solve problem of managing ever increasing e-wastes particularly mobile phone wastes in Ethiopia generated in assembling companies from their production process and end users caused due to its technology advancement, shortest life span compared to other EEE and tendency to use latest model by identifying the amount of mobile phone waste in the country and factors affect implementation of reverse logistics and related issues. Due to its opposite pole economic effect, the negative in its nature of hazardous materials content that damage the environment and human and positive effect due to the presence of valuable material in it, proper management through designing circular economy driven reverse logistics networks. The objective of designing optimum reverse logistics network and selecting appropriate business model for the enabling of the RLN in circular economy point of view, in reverse logistics a take-back practice being no longer makes the industries sustainable. For the achievement of companies for its competitiveness and countries sustainable development, implementation of circular economy effectively that is with closed concern on the two building blocks known as network design and business model is critically. Using qualitative and quantitative data collecting through observation and interview and using questionnaire format too together with secondary document revision valuable data is collected. Literatures written in general on reverse logistics designing and factors affecting its implementation, circular economy and circular business model are reviewed selecting as much latest as possible majorly using electronic data bases. Using the design and analysis tool together with data organizing, the result indicates that the network with 5 CC located in 5 cities with a total capacity of collecting 8,681,600 end-of-life MP is optimum but needs intervention and cooperation of government and all other stakeholders for its effectiveness on protecting human and environment in addition to solving the assembling industries problem of recycling and disposal.
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    Adoption of Additive Manufacturing for Auto Parts Production: Case of Bishoftu Automotive and Manufacturing Industry
    (Addis Ababa University, 2023-10) Sultan Asefa; Ameha Mulugeta (PhD)
    This study investigates the adoption of additive manufacturing in the Bishoftu Automotive Industry in Ethiopia. The study applies an integrated framework of Diffusion of Innovation (DOI) and Technology-Organization-Environment (TOE). This study also used combined data from primary and secondary sources using quantitative and qualitative methodologies to allow for the exploration of the factors and constraints influencing the decision to adopt additive manufacturing. Additionally, the research undertakes a thorough literature analysis of Adoption theories such as DOI, TOE, and factors affecting additive manufacturing adoption. Five point Likert scale was the method used to collect the useful information for this study. The questionnaire was distributed to managers, engineers, and technicians in the Bishoftu Automotive and Manufacturing Industry. Subsequently, the collected data was subjected to analysis through the application of descriptive statistics and partial least squares structural equation modeling (PLS-SEM) utilizing SPSS version 27 and SmartPLS version software. The study outcomes revealed that several critical determinants significantly impact the adoption of additive manufacturing (AM) in the automotive sector. These determinants encompass relative advantage, compatibility, complexity, trialability, observability, technology-related factors, and organizational as well as environmental factors The results of this study enhance our understanding of the adoption of additive manufacturing and provide valuable practical guidance for decision-makers within the Bishoftu Automotive Industry. Drawing from these findings, recommendations have been formulated to facilitate the effective integration of AM in the automotive sector. Additionally, this study identifies potential areas for future research in this field.
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    Designing a Multivariate Process Control Procedures for Production System Case of Ethio Cement PLC
    (Addis Ababa University, 2023-05) Daniel Ashagrie; Daniel Kitaw (Prof.); Eshetie Berhan (PhD)
    This dissertation explores the application of Statistical Process Control (SPC) techniques in the manufacturing sector. Industries demand multivariate process monitoring technique capable of identifying cause of variation, and conducting fast and accurate fault detection analysis. However, the existing techniques fall short of satisfying this demand. Hence, the research question is devised as follows: how to design a multivariate process control procedure that can effectively monitor and control the production system, identify the root causes of variation, and provide solutions for improvement. The literature review conducted in this study revealed that while SPC techniques have been extensively studied and applied in various industries, the multivariate analysis of identifying cause of variation is relatively limited. Their practical implementation and adaptation to the industry have not been thoroughly explored. The main objective of this research is to design a procedure that can bridge the theoretical gap that exist in the manufacturing sector. By addressing this gap, it is anticipated that the productivity, quality, and overall performance of the production system can be improved. To address these limitations, a novel approach called the GANNT chart is introduced in this research. The GANNT chart incorporates three key theories: Graph theory (G), Artificial Neural Networks (ANN), and Hotelling T2 (T). By combining these theories, the proposed approach aims to enhance the process control technique used in the production system. The GANNT chart mimics human decision-making processes and serves as a decision support system for both process engineers and operators.The GANNT chart methodology offers several advantages. Firstly, it analyzes the correlation effects between variables using Hotelling T2, allowing for a more comprehensive understanding of process variation. Secondly, it leverages graph theories to retain and utilize knowledge from previous successful operations, facilitating continuous improvement. Lastly, the system is trained using Artificial Neural Networks, enabling it to provide solutions to future challenges based on learned patterns from past operations. The proposed model is validated in the cement industry to assess its effectiveness and practicality. The results demonstrate that the GANNT chart effectively addresses the identified gaps in the application of SPC techniques to the cement production process. The model's ability to accurately detect process deviations and provide insights into the causes of variation contributes to improved productivity, quality, and overall performance. As a future research direction, this study highlights two suggestions. The first one is examining and extending the assumptions to design this model in such a way that it considers different scenarios not covered by this research. The second direction is extend the implementation of GANNT chart to various industries, including service giving industries, and study and explore its applicability. In conclusion, bridging the gap between theory and practice, this research aims to contribute to the advancement of multivariate process control to the industry, ultimately leading to enhanced operational efficiency and product quality.
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    Improving Workplace safety and Employee Working Behavior to Enhance the Productivity of Elevator Installation Process: A case study of SINTEC ETHIOPIA PLC.
    (Addis Ababa University, 2023-10) Ephrem Gezahegn; Kassu Jilcha (PhD)
    This paper explores the relationship between workplace safety, employee behavior and elevator installation enhancement. The objective is to understand the factors that contribute to enhanced elevator installation process by focusing on safety practices and promoting employee behavior. The study conducted a comprehensive literature review to identify the strength, weakness, and gaps in existing research. The review literature tells that workplace safety measures and employee working behavioral issues, such as the implementation of safety practices, including personal protective equipment(PPE) and adherence to regulatory guidelines, significantly impact the overall productivity of elevator installations during the process. However, gaps in the existing literature are identified. Limited research has been conducted on the specific challenges and limitations faced in implementing workplace safety practices during elevator installations. This study aims to fill these challenges by conducting primary research involving interviews, site observation and surveys with professionals in the elevator installation industry together with the secondary data. The data collected will provide insights into the practical experiences, perceptions, and recommendations of industry experts regarding the enhancement of elevator installation process through improvement of workplace safety and employee behavior. To analyze the data collected from surveyed questionnaire, the study implemented SPSS Software (Statistical package for Social Science) and Fish Bone diagram tool and Process Failure Mode Effect Analysis (PFMEA) techniques used to analyze root causes of the collected data from the professional’s. So that, The findings of this research will contribute to the development of strategies and interventions aimed at improving workplace safety practices, raising positive employee behavior, and ultimately enhancing elevator installation process.
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    Lithium-Ion Battery Value Chain Analysis: Assessing Ethiopia's Competitiveness and Strategic Framework
    (Addis Ababa University, 2023-06) Seyidu Wohabrebi; Ermias Tesfaye (PhD)
    The Lithium-Ion Battery (LIB) industry has gained significant importance as a key enabler for electric vehicles. The Federal Democratic Republic of Ethiopia has ambitious plans to decarbonize its transportation sector through the introduction of a sizable number of electric buses and small cars. However, these cars will eventually require new batteries after a while. This study uses a value chain analysis of the LIB industry, with a focus on assessing Ethiopia's competitiveness in the LIB value chain. It examines the entire value chain of LIBs, starting with the upstream stage involving the extraction and processing of raw materials, moving on to the midstream stage involving the manufacture of battery cells and component assembly, and finishing with the downstream stage involving battery integration and end-use applications. The study assesses Ethiopia's current position and potential for competitive advantage in each stage of the value chain using a combination of SWOT and Porter's five-force frameworks. It examines important elements such as the availability of raw materials, technological capabilities, and infrastructure development. The results highlight that Ethiopia has an estimated total of 3 million tons of Lithium brines linked to the potash horizons in Danakil, Afar region, with a 50% recovery rate. The nation also possesses abundant reserves of other important raw materials like nickel and graphite. Lithium, a key component of LIBs, holds significant value and is abundantly available in Ethiopia. Compared to graphite and nickel, lithium extraction requires less complex infrastructure and lower capital investments. Experts suggest that Ethiopia should prioritize lithium extraction to maximize its potential in the LIB value chain. However, substantial investments in infrastructure, technology, and knowledge are still required for the extraction and processing of these materials. Based on the analysis, the study provides a strategic framework to enhance Ethiopia's competitiveness in the LIB value chain. It can also serve as a valuable resource for policymakers, industry stakeholders, and investors interested in understanding Ethiopia's competitiveness in the LIB sector.
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    Enhancement of Overall Equipment Effectiveness (OEE) through the use of Industry 4.0: In the case of Hilina Energy-Enriched Foods Manufacturing Industry
    (Addis Ababa University, 2023-06) Solomon Muhabaw; Ermias Tesfaye (Ass. Prof.)
    Overall equipment effectiveness (OEE) is a metric used to measure machinery effectiveness while Industry 4.0 (I4.0) is a revolution of digital transformation which used to change convectional manufacturing industry to smart manufacturing industry, through its evolution always open for improvement of productivity, equipment effectiveness and efficiency of machinery, as well as create comfort zone for human and other habitats. This study aims to identify equipment effectiveness metrics and possible solutions for enhancing OEE in the manufacturing industry, specifically in the case of the Hilina energy-enriched foods manufacturing industry. By utilizing a mixed-methods explanatory research approach that involves qualitative and quantitative data collection and analysis with the aid of advanced analytics techniques and recognize patterns trained with data, big data is used. The data analysis identifies the biggest losses occurring at auxiliary grand machines, especially the filler and packaging machines, resulting in a current actual OEE of only 33.46 percent. However, the remaining auxiliary machines have an OEE of 79.64 percent, giving an overall OEE of 68.34 percent. Consequently, the study advocates using I 4.0 technologies such as the Internet of Things (IoT), smart devices with sensors, machine learning, and vision to mitigate downtime, speed, and quality losses of auxiliary grand machines and provide solutions to these issues. Moreover, through the analysis of big data, the study provides maintenance strategies and machine setups that can help reduce unexpected failures, the largest losses in organizations. Thus, the use of I 4.0 technologies can enhance OEE in the manufacturing industry by providing possible solutions for each problem. It is noted that the OEE improved from 68.34% to 73.36%. This study concludes that by using the industry 4.0 in the organizations can effectively enhance the effectiveness of their equipment and achieve maximum effectiveness.
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    Warehouse Management Improvement Model via Lean Warehousing for the Case of National Oil Ethiopia PLC (NOC)
    (Addis Ababa University, 2023-06) Abraham Negash; Gulelat Gatew (PhD)
    This research has provided a specific model framework of ways to solve and address the warehousing problems using lean management techniques. The problems identified at the case company were synthesized to reflect on which performance indicator they affect by utilizing the studies of various researchers. Furthermore, 24 lean tools associated with lean warehousing presented and validated by different researchers were identified and they were characterized into seven based on their management techniques. The wastes in warehousing of the case company were assessed seven principle of wastes which directly apply to a distribution warehouse. Interview with employees, first hand observation and collection of responses from questionnaire a sample size of 16 people was instrumental to analyze the wastes at each stages of the warehousing activities. The root cause of these wastes was analyzed by using combination of the 5W 1H history analysis method and 5 Whys root cause analysis technique and then Pareto analysis was utilized to recognize significant causes of warehousing problems. Consequently, twenty two cases were identified and these problems were further clustered to seven based on the notion they represent. Afterward, it was necessary to identify which warehousing issues correspond to the problems stated in the problem statement. To analyze that, a questionnaire was distributed amongst 73 sample population in which the analysis was undertaken by using Relative Importance Method. With that regard, Storage System, Standardization, Existing Human Resources, Warehouse Design and Training were found to be attesting to the problem statement. The next step taken after the identification of causes of major warehousing wastes was to identify which lean management tools can have an impact in solving these root causes. The sample size for questionnaire distribution and analysis for this step is similar to that of the previous step. With that regard, Continuous Improvement Management, Human Resource Management Lean Tools and Product and Process Management Lean Tools were found to have an impact in solving the warehousing issues at the case company. The findings of this research indicate that the warehousing problems at the case company can be solved by utilizing the above mentioned lean management techniques and the tools that they are comprised of.
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    Identifying Root Causes of Delay and Modeling Metal Industry Projects from Owners’ Perspective: A Case of Selected Metal Industry Projects
    (Addis Ababa University, 2023-10) Andinet Haile; Kassu Jilcha (Assoc. Prof.)
    Being behind schedule is a familiar case in the manufacturing sector that challenges the overall progress of projects resulting in poor performance and an inability to keep up with the dynamics of the business environment. Project delivery in the metals industry depends not only on its schedule but also on the performance of many stakeholders and the external environment that positively or negatively affects them. In this study, critical causes of delay were identified and feedback loop diagram is used to indicate effect of major causes of delay variable Interaction. Therefore, the study uses a causal loop diagram to show how the major causes of metal industry project delay factor interacts with in and with other system variable. Primary data was collected through questionnaires, group discussion and observations by the researcher. The questionnaires consist of 32 causes of delays which were distributed to project owners, the project managers, and Governmental staff researchers at the Manufacturing Technology and Engineering Industry Research and Development Center. Whereas; the secondary data were obtained from the literature reviewed and reported documents. The study aims at identifying the critical cause of project delay, then further models to understand the effect of factors interaction related to the causes of delay by the System dynamics model. accordingly, the critical factors that were identified in this research are; Effect of Inflation, Inadequate foreign currency, Bureaucracy, Unavailability of an infrastructure facility (interruption of electric power), Inadequate raw material, Difficulty in financing the Project, Existence of corruption, Unacceptable level of change orders by clients, Late material delivery, Unavailability of supply chain management, Inaccuracy submitted bid document and Late procurement of items. These causes are used to model the causal loop diagram. The study contributed to the metals industry projects by determining the critical factors of delay and the effects of system variable interaction on project delay system. and finally, devise mitigation strategies that potentially reduce project delays.
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    Transformer Failure Root Cause Analysis and Developing Mitigation Strategies: A Case of Addis Ababa City
    (Addis Ababa University, 2023-06) Esubalew Birhan; Kassu Jilcha (PhD)
    The distribution transformer is a critical component of the distribution system that must be very reliable in order to provide consumers with uninterrupted power supply. The failure of a distribution transformer has an impact on the supply system's reliability and power quality. This study aimed at failure root cause analysis and mitigation strategy development for distribution transformer in Addis Ababa. The study addresses 3,825 number of distribution transformers from the year 2020/21 to 2022/23 and the failure rate obtained is 13.4%. The collected data were recorded failure documents, interview and group discussion from Kotebi maintenance centers, Addis Ababa City Administration Electric Utility (AACAEU) and four electric utility districts in Addis Ababa. In the first part, the results of failure analysis are statistically summarized. In second part, the failure modes, effect analysis (FMEA) is used to analyze distribution transformer failure modes, causes, local and end effects of failure. To identify the most critical parts of the transformer, a risk priority number (RPN) is calculated based on the severity labelling, probability of occurrence, and probability of detection. Thus, from FMEA analysis, the most vulnerable parts of distribution transformers that have highest RPN value of 576 is insulation failure due to human related errors as a primary cause and with electrical mode of failure. Other component failure due to operational error and with thermal mode of failure is 512 RPN followed by winding failure, bushing failure and tap changer failure. FMEA leads to the identification of future preventative measures to be implemented to decrease the risk of the transformer by eliminating the causes of failure, thus minimizing the severity and probability of occurrence. The direct and indirect relationship between failure causes and effects of FMEA components are analyzed using causal loop diagram(CLD) and could clearly recognize unseen failure factors and their consequences. The root cause of transformer failure that covers 75% is human related factors, which is the primary source of operational failure causes like overloading, short circuit, internal problem and others. Solving failure of distribution transformers in Addis Ababa, the developed failure mitigation strategy is an asset management system of especially focused on predictive type supervisory control and data acquisition (SCADA) system. This study could fill the identified gaps, which means it has its own contribution to the body of knowledge of failure analysis. Finally, the outcome of this study has been thesis document, strategic solutions to minimize transformer failure and input source for further research.
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    Service Quality Improvement of Healthcare Through Complex Systems Perspective: A Case of Yekatit-12 Hospital
    (Addis Ababa University, 2023-10) Gezahegn Gebeyehu; Ameha Mulugeta (PhD)
    Service quality of healthcare is usually expressed as the extent of service providers’ attempt to meet or even exceed patients’ expectations during the service on the one hand and the level of patients’ satisfaction with their perceived quality of service on the other hand. On top of that, healthcare service sectors are an integral component of all types of communities, regardless of where they are located, since they are geared toward satisfaction for patients while offering the proper services in the proper manners and at the proper times. Nevertheless, it’s an obvious phenomenon that the existing healthcare system has been regarded as a linear hierarchic interaction although recent developments point out healthcare systems as complex entities that exhibit multifaceted patterns of non-linear interactions in their very nature. Thus, this research aims to enhance the quality of current healthcare services through a complex systems perspective. To do so, data was collected from the case hospital (Yekatit-12 Hospital) through direct observation, interview questions, and SERVQUAL dimensions-based questionnaires. Having corroborated with data interpretations from the Statistical Package for the Social Sciences (SPSS), the level of patient satisfaction was analyzed based on the five-point Likert scale and then complex causality noticed in the system was depicted using the system dynamics (SD) modeling. The result showed the three most problematic SERVQUAL dimensions in the hospital’s healthcare service. i.e., longer waiting time (reliability-related), complaints managing problems (empathy-related), and lack of a trend of intentionally asking about patients’ needs accompanied by swift action (courtesy-related) issues in decreasing order of their severity. Having applied SD modeling, all three problems listed above have been addressed and consequently, healthcare professionals and other academics in similar niches are encouraged for the furtherance of what is done here.
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    Investigating Workplace Risks & Ergonomic Interventions for Agricultural Harvest Workers: A Case of Agri-flower Strawberry Harvesting Workers of Holeta
    (Addis Ababa University, 2023-10) Hana Girma; Kasu Jilcha (Assoc.Prof.)
    strawberry harvesting workers in Holeta, as there is limited research conducted on this specific domain. In conclusion, this research contributes to the existing body of knowledge by providing a detailed investigation of workplace risks and proposing practical ergonomic interventions for Agri-Flower strawberry harvesting workers. The study's findings and proposed interventions improve worker safety, reduce musculoskeletal disorders, and enhance productivity in the agricultural sector.
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    Service Quality Design Through Customer-Oriented Failure Reduction (Case Company: Saint Paulos Hospital)
    (Addis Ababa University, 2023-06) Kiya Beyecha; Ameha Mulugeta (Asst. Prof.)
    Service quality has been considered as one of the vital areas for improving performance of any business process. Service quality is one of the most effective means of building a competitive position. Especially in health care service sector, service quality have significant role because, in this sector the main customers are patients who need a medical service so in this sector quality of service is linked with wellbeing of patients. This research was conducted by measuring the service quality, determining appropriate service design based on customer requirement and identifying customer oriented service failures and preparing corrective and preventive solution for the identified failures. The major problems identified in service quality of saint paulos hospital are patients take a long service time to be served in OPD department, OPD doctors have high working load which affects their effectiveness and in all ward of the hospital it is observed that there is frequent readmission rate of patients. So the objective of this study is to improve service quality in St Paul‘s hospital by providing mechanism of developing appropriate service design based on customer‘s requirement and reducing or eliminating significant failures. In order to measure the service quality SERVQUAL model is used for analyzing respondents expectation and perception and service gap is identified.using QFD analysis having regular technical training,having transparency in information flow,desining policies and procedures,having up-to-dated medical equipments,and conducting regular interpersonal training are identified as the most critical technical requirnments.using FMEA analysis ―not accurate medial records, not having adequet equpments, no on time serice delivery,understanding problem and patients not feeling safety during diagnosis‖ are identified as the most critical failures respectfully.according to the identified critical technical requirements the suggested service design is proposed.And also the recommended solution for the identified critical failures is provided.
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    Defect Reduction Using a Lean Six Sigma DMAIC Approach: A Case of 3F Manufacturing PLC
    (Addis Ababa University, 2023-06) Legesse Muchew; Gezahegn Tesfaye (PhD)
    Companies are forced by competitive pressures to look for ways to reduce defects while enhancing product quality. One of the best methods for corporate transformation is lean Six Sigma. This study seeks to give an empirical case study on the use of lean Six Sigma DMAIC approaches to reduce defects in a wood furniture company. The case company faces issues with the quality of its goods, which are reflected in its quality department and complaints from customers regarding the existence of defect rates of 59% in door product. Therefore, this study's objective is to reduce defects. To evaluate opportunities, present evidence for improvement, and identify possible benefits, the DMAIC technique is used in the study to look into the root causes of problems and suggest mitigation strategies. The result showed a significant decrease in the defect rate for door products. Previously, the defect rate stood at a concerning 59%; after effective interventions, it has dropped substantially to an impressive 22.96%. Through careful examination and rectification of underlying causes, it successfully identified and addressed the issues leading to defects. As a result, the number of defective doors produced has significantly decreased. Not only tackled defects but also made notable strides in improving process efficiency. The cycle time has witnessed a commendable reduction of 51 minutes, decreasing from 2114 minutes to 2063 minutes. To measure the consistency and reliability of our processes, it is important to utilize the sigma level. The sigma level has shown significant progress, improving from 2.6 to 3.2, considering a 1.5 sigma shift. This means that our process now operates within a narrower range of acceptable variations, ensuring greater consistency and reliability in the products. Even without factoring in the 1.5 sigma shift, the sigma level has improved from 1.18 to 1.7. This improvement is in terms of reducing variations and increasing process stability. With these outcomes, it is evident that Lean Six Sigma can indeed be applied for defect reduction in a furniture company, successfully reducing the defect rate, enhancing the overall quality of our products, and strengthening the reliability and consistency of our processes. During the research phase of the DMAIC process, a serious oversight was discovered; a lack of validation relative to the identified root causes. This omission may limit the achievement of intended goals and lead to ongoing processing difficulties.
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    Enhancing Performance of Spare Part Manufacturing Industry through Job-Shop Scheduling System: A Case of Addis Machine and Spare Parts Manufacturing Industry (AMSMI)
    (Addis Ababa University, 2023-03) Misgana Setu; Kassu Jilcha (Assoc. Prof.)
    Industries nowadays must be able to quickly adapt with the customer and improve production performance to survive in the competitive edge. This study aims at enhancing performance of spare part manufacturing industry through job shop scheduling by taking Addis Machine and Spare Parts Manufacturing Industry (AMSMI) as a cases study. The study combines scheduling and model simulation as methodological techniques to optimize numerous performance indicators in the production system. The study also identifying critical success factors affecting performance of manufacturing industry and major key production performance indicators, through different literature review. Moreover, brief evaluations of solution techniques for Flexible Job Shop Scheduling Problem (FJSSP) are addressed. Due to poor production schedule attainment, the company (AMSMI) is facing long lead time of products (make span), idleness of machine and high work in process (WIP). To address those problems, detail shop floor assessment and analysis of current scheduling system (First Come First Serve) and other alternative schedule scenarios (Longest Processing Time and Generic shifting Bottleneck) are conducted using Lekin and Arena simulation software. As the analysis shows, in the current scheduling system makespan, product output, machine utilization and works in process (WIP) are 1100 minutes, 126, 31.44% and 470.01 respectively, whereas in the optimum scheduling model (Generic Shifting Bottleneck Algorithm), makespan, product output, machine utilization and work in process (WIP) are 1043 minutes, 131, 36.06% and 432.08 respectively. So it is concluded as, using the proposed scheduling model (Generic Shifting Bottleneck Algorithm) can increases makespan, machine utilization and product output by 5.1%, 4.6% and 3.8% respectively, and decreased work in process (WIP) by 8%. Therefore, this research implies that combining scheduling and model simulation to use as the performance enhancement approach can optimize several performance indicators simultaneously, in spare part manufacturing industries.
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    Overall Equipment Effectiveness Improvement through Implementation of Total Productive Maintenance: A Case Study on Dugda Construction Plc.
    (Addis Ababa University, 2023-06) Muluneh Shibiru; Ermias Tesfaye (PhD)
    In the TPM literature, numerous frameworks for Total Productive Maintenance (TPM) pillars have been given proposed by various writers. However, the majority of them are based on research done in countries like Japan, Italy, the United States, China, and India. Thus, the aim of this study was to assess the contribution of a few TPM pillars to manufacturing performance in the construction industry. Data on production, downtime, reasons for downtime, and maintenance are gathered from the case company and analyzed to determine how the company's equipment is currently performing. Using a survey approach, 31 corporate employees were given questionnaires, with a 98% response rate being the end result. The relationship between the manufacturing performance dimension and TPM Pillars has been calculated using descriptive statistical methods. In the survey, autonomous and planned maintenance received the most attention, whereas development management received the least attention. The TPM Pillars, autonomous maintenance, focused maintenance, planned maintenance, and training and education are all covered up in the report, despite their considerable contributions to manufacturing performance, including lower costs, greater equipment availability, strong delivery, and improved quality. The results of the study indicate that the company's availability, performance, quality, and OEE were all increased by 67.74% 71.38% 99.08% 47.91%, respectively, as a result of the application of TPM. For the case company, a new implementation framework has been suggested. When completely implemented, all of the chosen pillars have activities that improve shop floor safety. Maintaining safety initiatives across all pillars will be crucial to creating a secure working environment.
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    Industrial Occupational Safety and Health Model Development in Manufacturing Industries:-a case of Akaki Basic Metal Industry
    (Addis Ababa University, 2023-06) Rahel Mulugeta; Kassu Jilcha(PhD)
    Manufacturing is a significant sector of the economy in many nations and is frequently regarded as an engine of economic expansion, particularly in developing nations. Despite its importance, the metal sector is seen as unsafe due to frequent and high accident rates as well as worker health issues. Therefore, the primary goal of this research is to create a safety model with the goal of development in occupational safety and health in order to reduce workplace injuries, diseases, and deaths in the Akaki Basic Metal Industry. Employees of Akaki Basic Metal Industry from all departments were deemed to be the study population's respondents. Using an open-ended questionnaire, 220 randomly chosen corporate employees provided the primary data .The hypothesized model was developed and tested on a sample 215 respondents who worked for production businesses. The Statistical Package for the Social Sciences (SPSS) version 23.0 was used to enter and analyze the acquired data, and the Analysis Moment of Structure (AMOS) version 21 software was used to build the model. Descriptive statistics were utilized to analyze the data in order to evaluate the OSHP-related factors at Akaki Basic Metal Industry. Through the use of structural equation modeling (SEM) and confirmatory factor analysis (CFA), research models were examined and confirmed. The case company develop a safety model with the aim of to reduce workplace hazard .To achieve all of the goals, a design using mixed methodologies was developed. A good-fit structural model (PCLOSE=0.001, Goodness of Fit Index=0.971, Root Mean Square Error of Approximation=0.121, Comparative Fit Index=0.986 and TLI =0.906) indicated that Safety culture, safety police and safety climate constructs direct influence on firm productivity. The new Occupational Safety and Health Model Result can be used to provide better understanding of the links between firm productivity indicators and contributing components, and make stronger recommendations for effective intervention in construction projects. Employees are more likely to abide by safety rules if administrative professionals are seen as being concerned about OHS. A worker safety and health program has also been created and put into place. However, without the cooperation of both employees and employers a thorough occupational safety and health program were unachievable
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    Fatigue Life Investigation for Aisi-H13 Used for The Application of Pickaxe Die Using Numerical and Analytical Method
    (Addis Ababa University, 2023-04) Belay Ayalew
    The main objective of this research was to obtain optimum forging load and temperature to investigate the fatigue life for the pickaxe piercing die made of AISI-H13 which was working under hot forging process in Kotebe Metal Tools Factory. The die supported to manufacture a pickaxe with circular whole diameter of 52mm. Under estimation of the optimum forging load, the temperature of the pickaxe piercing die, the temperature of die and work-piece, the stoke length of the forging press, press ram speed and coefficient of friction were considered as input parameters. This research approach combined analytical and numerical analysis to find a solution to set target (for estimating the forging load). The geometrical model of the dies and work-piece have been modelled using geometrical modelling software (SOLID WORK) and simulated using numerical simulation software(DEFORM-3D),wchich was adopted to simulate the forging processes using the input parameters. Then, the fatigue life of the lower die was analyzed using ANSYS software. To optimize the forging process parameters (dies and work-piece temperatures as well as coefficient of friction), the Taguchi optimization technique based on analysis of variance (ANOVA) and Analysis of mean value (ANOM) was applied. The forging process parameters were considered as experimental factors and the optimization of the forging load was considered as experimental objective. In order to obtain optimum forging load, the forging process parameters are examined using a three-level full factorial design of experiments and analyzed using MINITAB software. As an output ,the obtimum forging load,working temperature and coefficient of friction were identified with values of 2.16MN,1050C, and 0.3 respectively. Among the three forging process parameters,workpiece temperature is the most significant parameter followed by coeffiecent of friction and die temperature to get the lower required forging load.Their percentage contribution to the forging load was 61.33,37.12, and 0.87% respectively. The results of the simulation and the mathematical model were compared for validation and the identified results agreed with each other. By implementing the minimum optimized forging load(2.16 MN), the fatigue life of the lower pickaxe piercing die can be extended to 106 cycles until the die fracture.
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    Circular Business Model for Vehicle Lead-Acid Batteries in Ethiopia
    (Addis Ababa University, 2023-10) Samuel Alemu
    The automotive battery industry is shifting towards sustainability, driven by the need for circular business models, particularly lead acid batteries (LABs). This transition presents unique challenges and opportunities for circular economy implementation. In developing countries like Ethiopia, the LAB industry faces sustainability issues and undercapacity utilization. This research aims to identify potential circular strategies, pinpoint the most influential factors affecting adopting of circular business model (CBM), and develop a CBM tailored for LABs to address sustainability challenges and promote circular practice in the automotive battery industry. The research employs a multi-faceted methodology including expert opinions, thematic analysis, hybrid Grey and Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis, and the Business Model Canvas framework. The study identifies and propose three promising circular economy strategies: repair for reuse, repurpose, and recycle which collectively provide substantial environmental and economic benefits by extending battery life, reducing resource consumption, and generating revenue. Further, the study identifies four key factors influencing the adoption of CBM for LABs by analyzing the dynamic interplay of 23 factors: lack of business model with take-back systems, high cost of handling and processing, lack of effective communication and coordination, and lack of supportive government policies. Finally, the study offers a practical roadmap for implementing circular practices by modeling identified circular strategies within the Circular Business Model Canvas framework. This research prioritizes environmental responsibility, resource efficiency, and economic viability, contributing to LAB sustainability and fostering an environmentally responsible automotive sector.
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    Developments of Quality Management System (QMS) for Steel Industries (Quality Improvement: A Case Study of Walia Steel Industry)
    (Addis Ababa University, 2023-12) Zewde Tegenu
    Quality management system framework is a synchronized set of quality management system principles and quality tools and techniques which implemented by an organization to meet the standards demanded by customers and stakeholders. The research aims is developing a quality management system (QMS) framework for Walia Steel Industry by addressing the barriers and lack of integration of quality tools and techniques with the company process approach and management. Methodologically, the study employed a literature review and a case study-based questionnaire involving 38 respondents, including quality managers, top managements, department managers, and supervisors. The findings of the study identified eight critical success factors and seven barriers in the practice of quality management system at Walia Steel Industry. The study emphasizes that sustaining the practice of QMS requires integrating quality tools and techniques with the company's process approach and management. By doing so, it is believed that the quality of products and services provided by Walia Steel Industry can be improved. The research also suggests that the developed QMS framework can be applicable to other manufacturing industries that practice quality management systems. The uniqueness of this study lies in its focus on the integration of quality tools and techniques with the company's process approach and management, specifically within the context of Walia Steel Industry. In conclusion, the study proposes that integrating quality tools and techniques with the company's process approach and management is a potent QMS framework for sustaining the practice of quality management system. By adopting this framework, Walia Steel Industry and similar manufacturing industries can enhance their product and service quality.