Dissertations/Theses - Department of Industrial and Production Engineering
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Item Analyzing the challenges to mitigate traffic congestion in densely populated cities: implications for efficient urban planning and sustainability(Department of Industrial & Production Engineering,(IPE), BUET, 2024-03-24) Fahim Bin Alam, Md.; Bari, Dr. A. B. M MainulTraffic congestion (TC) disrupts everyday life, elevating stress levels, extending commute durations, diminishing productivity, and reducing overall quality of life. Due to extended stress and pollutant exposure, TC causes environmental degradation through air pollution, fuel inefficiency, company losses, and increased health risks. Congestion exacerbates already-existing problems in densely populated places by taxing the little infrastructure, reducing productivity, and disrupting supply networks. Urban planning is made more difficult by the residents' lower accessibility and higher levels of distress. Reducing traffic is essential to creating sustainable, livable communities, which calls for creative ways to handle expanding populations while minimizing negative impacts on the environment, economy, and public health. Therefore, this study employs a combined method for multi-criteria decision-making (MCDM), integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique with the interval-valued Pythagorean Fuzzy (IVPF) theory to pinpoint, rank, and analyze the relationships between the challenges impacting the mitigation of TC, with an emphasis on densely populated urban areas like Dhaka. At the outset, 18 (eighteen) challenges were identified through a review of existing literature. Following expert validation, 16 (sixteen) challenges were chosen for analysis utilizing the IVPF DEMATEL method. The findings of the study show that the three major challenges to TC mitigation are “Lack of efficient coordination and management of traffic signals”, “Insufficient choices for public transportation”, and “Lack of integration of advanced data analytics and IoT-based technologies”. The anticipated impact of this study lies in its substantial contribution to future innovation and development in urban planning. By aiding policymakers, urban planners, and stakeholders in formulating long-term strategies through strategic decision-making, the study aims to alleviate severe TC, particularly in densely populated cities. and bring about positive changes in the urban planning sector.Item Modeling humanitarian relief supply chain performance using bayesian network approach(Department of Industrial & Production Engineering (IPE), BUET, 2023-07-25) Nafisa Ahmed, Humaira; Ali, Dr. Syed MithunThe concept of humanitarian relief supply chain management has gained a lot of interest among academics and practitioners since the number of natural or human-made disasters have been increased drastically. These disasters frequently cause extensive destruction, loss of life, and collateral damage. Although these events cannot be prevented, appropriate measures can be taken to mitigate their negative effects on nations. Humanitarian organizations provide aid for disaster relief operations, which is known as the humanitarian relief supply chain. Nonetheless, it is essential to comprehend the efficacy of the humanitarian relief supply chain performance measurement model. A humanitarian organization can monitor and control its relief supply chain more efficiently and effectively by measuring performance. The purpose of this research is to develop a Bayesian belief network model for predicting the performance of the humanitarian relief supply chain in case of catastrophic events, such as natural disasters and man-made crises, in order to efficiently deliver assistance to affected regions. The study begins with the identification of performance metrics that have a direct or indirect effect on the overall performance of a humanitarian organization. Then, with the aid of a Bayesian belief network, a probabilistic graphical model capable of predicting any organization's relief supply chain based on performance metrics was developed. The model has been validated through numerical examples, extreme condition testing, scenario analysis, sensitivity analysis, and diagnostics analysis. The performance measurement model will assist organizations' decision-makers and policymakers in controlling, monitoring, and enhancing their relief supply chain.Item Assessing sustainability in supply chain using dempster-shafer theory(Department of Industrial and Production Engineering, 2019-05-08) Bappy, Mahathir Mohammad; Ali, Dr. Syed MithunSustainability assessment in supply chain is an important task for any organization in the competitive business environment. To ensure better decisions for optimizing the sustainability attributes such assessments are desirable. Therefore, it is essential to have a model of sustainability assessment in supply chain considering the triple bottom line of economic, environmental and social attributes, as failure of these attributes may lead to catastrophic consequences. The sustainability assessment process of an organization is aligned with different sources of information which can be uncertain, incomplete, and subjective in nature. To assess or monitor the sustainability, though there are many techniques available, but the intelligent interpretation of the collected information remains a challenge. Therefore, this research proposes a methodology that uses an integrated approach of Analytical Hierarchy Process (AHP) and Hierarchical Evidential Reasoning (HER) based on Dempster-Shafer (D-S) theory to develop a supply chain sustainability assessment model. After identifying the sustainability assessment criteria, AHP is used to structure and rate the criteria based on expert’s opinion. In this research, subjective judgmental belief data have been used to test the model. The information is combined using D-S theory and results are depicted as supply chain sustainability index. In the proposed model, the results of D-S theory are compared using Yager’s recursive rule of combination. The model generates satisfactory results based on the utilized data.Item Application of reliability centered maintenance (RCM) in lead oxide production system a case study(Department of Industrial and Production Engineering (IPE), 2015-12) Ahasan-Ul-Karim, Md.; Ahmad, Dr. NafisIn this work a framework on application of Reliability Centered Maintenance (RCM) for Lead Oxide production process in the battery industry is developed. Reliability-Centered Maintenance (RCM) integrates Preventive Maintenance (PM), Predictive Testing and Inspection (PT&I), Repair (also called reactive maintenance), and Proactive Maintenance to increase the probability that a machine or component will function in the required manner over its design life-cycle with a minimum amount of maintenance and downtime. RCM method is used here through Failure Mode and Effect Analysis (FMEA) and decision making for maintenance criteria is established in view of Criticality and Logic Tree Analysis (LTA). Finally Task allocation of equipment is described based on the following strategies: condition based, interval based, failure finding and run to failure or redesign. Evaluation of this RCM frame work is performed based on standard evaluation criteria by society of automotive engineers inc. Challenges of the application which can influence the performance of the plan also described. The study is done for Lead Oxide production process- a critical system of battery industries. RCM method can shift the maintenance culture and thinking while maximizing equipment availability and enhancing plant reliability in this type of industries and other industries also.Item Capacity constrained materials planning and scheduling in a plastic manufacturing company(Department of Industrial and Production Engineering, BUET, 2003-04) Alamgir Hossain, Mohammad; Hasin, Dr. M. Ahsan AkhtarThe competition is strong between firms in Bangladesh, manuracluring plastIc items, especially in [he areas of bottling of water and other juices. A large number of companies grew over the few years, thereby creating intense competition in the market. The problem, ror a company are manifolds: i) there is generally a huge amount of s[ock, iLltiley don't know how t" load and reiea,e orders when there are multiple SL!nultJneous orders from many customers. etc. Additionally, their capacity is limited, and thus. are alway' overloaded. Therefore. If [hey wam 0 prosper fLHtiler, the company needs to prepLirea good m~teriuls planning _'y,lem, which would minimize average flow time, the mmt commOn measure of scheduling, Though MRPII is a system for material, planning as well, it cannot handle and schedule orders as per capaclly, and prepare an optimal plan. TilliS, it is required that an optimal planning algonlhm would be used for schedLlling orders, and then preparing a buekw~rd scheduling plan lo find out materials purchasing timings_ Thi, ,wdy uSeS Heunslic Algorithm for de,ired perform~nee me~su•.e (~ltel"i1mive.,",-e, number of tardy jobs. minimizing flow lime, minimizing average lateness. etc,) for parallcl Ldcnticalm~ehines_Item Production system synthesis and application of operations research techniques toward operations management decision making(Department of Industrial and Production Engineering, BUET, 1990-12) Abdul Hannan; Rahman, Dr. Md. MizanurProfitable performance of an industrial unit depends on a rationale production system. The level of performance depends solely on the production policy along with any other relevant factors. Establishment of a clearcut relation between the level of performance and cost of production as a whole would require such considerations as, i. Use~of mathematical tools and Scientific methodology of Operations Research .(OR) and statistics. ii. Scientific approach of record keeping, sorting, and retrieval of basic data etc. The present research work is intended primarily to explore the use of OR techniques and demonstrate their application to an industrial unit through its different stages of production decisions. The work starts with an analysis of the production system of the Mimi Chocolate Factory, with the aim to find out idle time of both man and machine, the bottlenecks in the production system. Secondly, the work is concerned with the estimation of demand of the products through the use of the historical iv sales data of past 24 months of consecutive periods. The Winters' method of exponential smoothing was applied for the purpose. Thirdly, the work is concerned with the determination of the optimal product-mix of the Mimi products. An LP model was developed on the basis of plant capacity,availability of man-hrs. and machine-hrs., ingredients and forecasted demand. Finally, an optimum procurement policy for some of the major raw materials and ingredients of Mimi chocolate factory was formulated on the basis of various cost elements related to inventory. The Dynamic Programming technique was applied to arrive at a solution to each of the ingredients of the problem.