Industrial Engineering
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- ItemEnabling Sustainable Futures and Economic Empowerment through PET Recycling in Nablus(2025-02-05) Malak Saadeh; Ghusoon SalahAbstract: Plastic waste poses a significant environmental challenge worldwide, resulting in pollution of land, water, and air that adversely affects human health and wildlife. Challenges include inadequate recycling infrastructure and high volumes of single-use plastics. However, recycling emerges as a crucial solution, addressing environmental impact, resource conservation, and the reduction of new plastic demand. Combining efficient recycling systems with awareness campaigns for responsible consumption and eco-friendly alternatives offers a comprehensive strategy to tackle the global plastic crisis. The project's main objective is to establish a sustainable and economically viable system for recycling Polyethylene Terephthalate (PET) plastic waste in Nablus city. Furthermore, it aims to raise awareness about reducing plastic waste and promoting sustainable practices. To achieve these objectives, an economic feasibility study has been conducted to explore the potential for a PET plastic recycling factory. This feasibility study explores the viability and potential benefits of establishing a PET recycling plant in Nablus, aiming to address the pressing challenges associated with plastic waste management in the region. The study begins with a comprehensive analysis of the current state of plastic waste management in Nablus, emphasizing the escalating environmental impact and the social implications of inadequate waste disposal. The project proposes the establishment of a PET recycling plant as a strategic intervention, offering a systematic approach to reduce the environmental footprint and promote a circular economy. Key components of the feasibility study include an in-depth market analysis, encompassing the demand for recycled PET products in local and international markets. Additionally, a detailed examination of the technical and technological requirements for the recycling process, alongside the identification of potential site for the plant, forms an integral part of the study. The financial feasibility aspect involves a thorough cost-benefit analysis, taking into account initial investment, operational costs, and revenue projections. The financial analysis, spanning a ten-year period, reveals promising results, demonstrating profitability and positive returns on investment. The study incorporates detailed projections for initial setup costs, operational expenditures, and revenue streams. These financial results underscore the project's potential to not only cover its costs but also generate sustainable profits over the projected timeframe. Furthermore, the socio-economic impact assessment highlights job creation, skills development, and community engagement as additional positive outcomes. In summary, the findings of this feasibility study provide valuable insights into the practicality and sustainability of establishing a PET recycling plant in Nablus. This project aims to contribute not only to the reduction of plastic pollution but also to the creation of a more sustainable and environmentally conscious community, aligning with global efforts towards a circular economy and responsible waste management.
- ItemEvaluating Manufacturing Systems with Machine Learning Techniques(2025-02-04) Firas Mabroukeh; Basel Al-SahiliAbstract: In the domination of mass production systems, optimizing efficiency is essential for sustainable operation and competitive advantage. However, the complex interdependencies in sequential operations often lead to high variability in output parameters, create challenges for accurate prediction. This project proposes an approach to address this issue by integrating simulation and machine learning techniques to evaluate manufacturing systems efficiency. The project was divided into two phases, phase one was focused on the development of an accurate machine learning model capable of predicting queuing systems output parameters with precision, this model was trained on data generated through simulation, predictions made were compared with theoretical values of queuing systems equations, phase one came to a conclusion that machine learning models and simulations effectively predict and analyze queuing system behaviors, offering a robust integrated toolset with wide-ranging applications. In phase two, the study of manufacturing systems expanded to include serial production lines, these systems lack evaluation formulas. Utilizing five Tree-Based Machine learning algorithms, models were trained and evaluated using simulated data. The study employed Random Forest (RF), Extra Trees (ET), Gradient boosting decision tree (GBDT), XGBoost, and LightGBM models for prediction. Evaluation metrics such as the Coefficient of Determination (r2) and Mean Absolute Percentage Error (MAPE) were used to compare between the models. The findings from phase two underscore the capability of Tree-Based Machine Learning models in handling the complexities of serial production lines, where traditional analytical approaches falter. Among the models tested, Gradient Boosting XGBoost, and LightGBM demonstrated superior performance in predicting key metrics such as average throughput and buffer levels, achieving high R² values and low MAPE across various configurations. However, Tree-Based Machine Learning models struggled to predict Throughput Standard Deviation accurately. Future studies could explore whether this is due to the training data being too small or lacking variety, or if tree-based models are simply not well-suited for predicting this type of output. This could involve creating larger and more detailed datasets or testing other machine learning methods better suited for this task.
- ItemUtilizing Machine Learning Techniques in Inventory Planning and Control of Automotive Spare Parts(2024-11-25) Baha’a Dweikat; Galina Zagha; Leen Atout; Yasser IsteitiehAbstract The automotive industry facing significant challenges in inventory planning and control activities, particularly in managing the availability of spare parts. In this project, machine learning techniques were utilized to develop and analyze several models to enhance the inventory planning and control of automotive spare parts, and their performance was compared with traditional methods to show their applicability. The focus was placed on employing Artificial Neural Networks (ANN) and Autoregressive Integrated Moving Average (ARIMA) models, and their effectiveness was compared against the traditional Moving Average method. The primary objective was to enhance the accuracy of inventory forecasts and improve overall inventory management efficiency. Historical data were collected and analyzed, models were trained and tested, and their performance was evaluated. Specific constraints were encountered, such as the lack of comprehensive historical data and limited software availability. The unavailability of suitable software restricted the development and analysis of support vector machine models, leading to a concentration on ANN and ARIMA models. It was demonstrated that machine learning models, particularly ANN, provided more accurate forecasts compared to the traditional Moving Average method. Superior performance in capturing complex patterns in the data was shown by the ANN model, whereas the ARIMA model offered robust time series forecasting capabilities. The traditional Moving Average method, while simpler, lacked the sophistication needed to handle the details of automotive spare parts inventory. Overall, the potential of machine learning techniques in revolutionizing inventory planning and control in the automotive industry was underscored by this project. By leveraging advanced models, significant improvements in forecast accuracy and inventory management can be achieved, ultimately contributing to more efficient operations and reduced costs.
- ItemCookie Quality Optimization for piece of cake(2024-10-06) Ahmad kayed; Yara sayeh1 Our project titled "Cookie Quality Optimization for Piece of Cake" focuses on improving the quality and longevity of cookies produced by a small family-owned factory called "Piece of Cake" in Palestine. The project aims to enhance the freshness of cookies over time, addressing the issue of cookies becoming dry and unappealing after storage. The approach involves modifying the recipe, optimizing the production process, and enhancing quality control measures. Key Objectives: 1. Improve the productivity and quality of the cookies for an extended period. 2. Use industrial engineering tools to streamline operations and increase efficiency. Methodology: • Data collection and analysis were conducted, including customer feedback through questionnaires. • Various trials were performed to identify the best modifications to the cookie recipe. • The recipe was altered by adjusting ingredients such as flour, sugar, and baking soda to achieve longer-lasting quality. Results: • Two optimized recipes were developed that enhanced cookie quality, particularly in maintaining softness and taste for up to two days. • The modified recipes were shared with the factory, leading to positive feedback from the head chef and testers. Recommendations: • Implement one of the optimized recipes for improved product quality. • Upgrade packaging methods to maintain freshness for a longer time. • Educate staff on proper storage techniques and increase production volume, leveraging the longer shelf life of the new recipe. The project concluded that improving the freshness and quality of the cookies, along with better packaging and staff training, could help "Piece of Cake" enhance its competitive edge in the market.
- ItemFeasibility Study for Establishing Polypropylene Random Copolymer (PPR) Pipes and Fittings Plant(2024-09-09) Deema Khalili; Ibraheem Dwikat; Hamdy Abu Eisha1 Abstract This project's main idea revolved around conducting a feasibility study to establish a plant for producing PPR pipes to ensure the project will be successful or not in the West Bank. The first step was to make a simple introduction that presented the problem, the most crucial project objectives, scope of work, significance of the project, and the report's organization. The second step was a review of the literature, which is considered one of the essential parts that help in deep understanding, gives an overview about the level reached by science in this topic, and provides an opportunity to reach new conclusions, theories, and ideas. Then, the methodology is a simple summary showing the products that have been identified, aspects of the production process required, steps that were followed to conduct the market study, in addition to an explanation of a simple summary about the questionnaire that was done, and steps that will be followed to complete both the technical study and the financial study. The market study was started by completing a questionnaire that includes three basic categories. The questions for each category differed from the other categories. The questions aimed to study the volume of demand and supply, determine the product's market share, know the market's nature is monopolistic or competitive, and determine the most used and demanded PPR products, the production line that will be established depending on the diameters that most requested. Based on the preliminary analysis, we found that the market is competitive, the demand for these products is excellent, the PPR products that will be adopted are PPR and PPR-CT, and the project will be limited to one production line. In the second semester, this project was completed, beginning with a detailed analysis of the market study, by identifying demand, target areas, competition, and others. After that, a technical study was made in which the machines and molds will be defined. And a 2D modeling for the production line and a 3D modeling of the extrusion die head, using the Autodesk Inventor software. Next, the financial study was defined to find out the investment capital and analyze many important indicators such as the rate of return, payback period, break-even point, and others. Finally, some recommendations and conclusions will be made in which a will be made whether the project is feasible or not.