Browsing by Author "Mehret Getachew (Mr.) Co-Advisor"

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    Factors of Production Throughput Improvement of Flexible Job Shop with Hybrid MTO-MTS Production Strategy Through Production Scheduling Using Dispatching Rules and Simulation; Case of Deluxe Furniture Manufacturing, Minaye P.L.C
    (Addis Ababa University, 2022-11) Eskedar Negese; Ermias Tesfaye (PhD); Mehret Getachew (Mr.) Co-Advisor
    For the past few decades, the production schedule has been the focal area for researchers under different production types and respective strategies being implemented on. Among the previous researches, the partial flexible job shop scheduling problem with the concept of the production strategy implemented on hasn’t brought to the academic research as well as practical based research development areas. Based on the reviewed articles and studies, it has been identified that there exists certain gaps on the production scheduling of a partial flexible job shop production floor type and the strategy implemented. The need for this concept is to clearly define methods using the production scheduling to indicate on how to manage the natural constraint conflict taking place on this very kind production floor type. In meantime, support the implemented strategy to improve the throughput and other performance parameters such as capacity to accept new orders, WIP accumulation percentage and number of tardy job orders. Thus, this paper will be proposing production scheduling using dispatching rules integrated in simulation tool. The throughput improvement is achieved as a result of to the factors of improved work-in-process (“WIP”) accumulation % and tardy number of job orders. The study is conducted based on clear understanding of the existing production scheduling and developing consistent production scheduling policy, strategy and methods using the above mentioned tool in representing the operating system and respective scheduling model. The overall aim of the study is to propose suitable production scheduling using dispatching rules to concisely developed for the production nature under the study; and simulation tool to exhaustively representing the production floor. As a result improve the number of tardy jobs as well as other neglected performance metrics: capacity to accept new orders, WIP accumulation percentage and throughput of the production floor.
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    Lean-Six Sigma Approach for Enhanced Efficiency and Quality in Textile Manufacturing; a Case of Else Addis Industrial Development P.L.C., Ethiopia
    (Addis Ababa University, 2025-03) Asefa Kebede; Ameha Mulugeta (PhD); Mehret Getachew (Mr.) Co-Advisor
    The study focuses on addressing textile product quality and process inefficiency challenges, as well as how to enhance product quality and efficiency through the Lean Six Sigma principles, tools, and techniques in Ethiopia’s textile industry, specifically targeting the production of 40Ne yarn count. This particular yarn count was selected due to its recurring quality and efficiency issues, making it a critical area for improvement. The research employs both qualitative and quantitative methods to assess product quality and process efficiency, ensuring a comprehensive validation of the existing problems. During case company observation major defect were recorded with amount of defect rejected. The major defect identified were count variation, yarn hairiness, thin-thick place, winding fault, shape of the cone, bad piecing, and nep formation. From the major defect Pareto chart analysis revealed three major defect types contributing to 64% of quality issues. These are count variation (24%), yarn hairiness (22%), and thin/thick places (18%). Root cause analysis using fishbone diagrams identified key contributors including machine inconsistencies, operator skill gaps, material flow inefficiencies, and measurement errors. Also, from observed data, process efficiency evaluation showed big waste, with only 47.7% value-added time versus 52.3% non-value-added activities, primarily from motion waste (40.4%). The current sigma level of 3.25 indicated big process variability. The DMAIC framework was applied to address these challenges, integrating Lean tools like 5S and Value Stream Mapping (VSM) to reduce waste and Six Sigma methods to minimize defects DPMO and sigma levels was determined based production per months and defect rejection in production per month. Through the compressive analysis of the winding process using tools, process mapping, 5S, and DMAIC approach with tools, and based on the findings of the analysis, this study was developed and proposes an improvement strategy for the yarn manufacturing industry.