Relevant bibliographies by topics / Disassembly line balancing

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Academic literature on the topic 'Disassembly line balancing'

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Published: 25 May 2024

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Journal articles on the topic "Disassembly line balancing"

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Hu, Youxi, Chao Liu, Ming Zhang, Yu Jia, and Yuchun Xu. "A Novel Simulated Annealing-Based Hyper-Heuristic Algorithm for Stochastic Parallel Disassembly Line Balancing in Smart Remanufacturing." Sensors 23, no. 3 (February 2, 2023): 1652. http://dx.doi.org/10.3390/s23031652.

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Remanufacturing prolongs the life cycle and increases the residual value of various end-of-life (EoL) products. As an inevitable process in remanufacturing, disassembly plays an essential role in retrieving the high-value and useable components of EoL products. To disassemble massive quantities and multi-types of EoL products, disassembly lines are introduced to improve the cost-effectiveness and efficiency of the disassembly processes. In this context, disassembly line balancing problem (DLBP) becomes a critical challenge that determines the overall performance of disassembly lines. Currently, the DLBP is mostly studied in straight disassembly lines using single-objective optimization methods, which cannot represent the actual disassembly environment. Therefore, in this paper, we extend the mathematical model of the basic DLBP to stochastic parallel complete disassembly line balancing problem (DLBP-SP). A novel simulated annealing-based hyper-heuristic algorithm (HH) is proposed for multi-objective optimization of the DLBP-SP, considering the number of workstations, working load index, and profits. The feasibility, superiority, stability, and robustness of the proposed HH algorithm are validated through computational experiments, including a set of comparison experiments and a case study of gearboxes disassembly. To the best of our knowledge, this research is the first to introduce gearboxes as a case study in DLBP which enriches the research on disassembly of industrial equipment.
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Altekin, F. Tevhide, Levent Kandiller, and Nur Evin Ozdemirel. "Profit-oriented disassembly-line balancing." International Journal of Production Research 46, no. 10 (May 15, 2008): 2675–93. http://dx.doi.org/10.1080/00207540601137207.

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Xu, Gongdan, Zhiwei Zhang, Zhiwu Li, Xiwang Guo, Liang Qi, and Xianzhao Liu. "Multi-Objective Discrete Brainstorming Optimizer to Solve the Stochastic Multiple-Product Robotic Disassembly Line Balancing Problem Subject to Disassembly Failures." Mathematics 11, no. 6 (March 22, 2023): 1557. http://dx.doi.org/10.3390/math11061557.

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Robots are now widely used in product disassembly lines, which significantly improves end-of-life (EOL) product disassembly efficiency. Most of the current research on disassembly line balancing problems focuses on decomposing one product. More than one product can be disassembled concurrently, which can further improve the efficiency. Moreover, uncertainty such as the depreciation of EOL products, may result in disassembly failure. In this research, a stochastic multi-product robotic disassembly line balancing model is established using an AND/OR graph. It takes the precedence relationship, cycle constraint, and disassembly failure into consideration to maximize the profit and minimize the energy consumption for disassembling multiple products. A Pareto-improved multi-objective brainstorming optimization algorithm combined with stochastic simulation is proposed to solve the problem. Furthermore, by conducting experiments on some real cases and comparing with four state-of-the-art multi-objective optimization algorithms, i.e., the multi-objective discrete gray wolf optimizer, artificial bee colony algorithm, nondominated sorting genetic algorithm II, and multi-objective evolutionary algorithm based on decomposition, this paper validates its excellent performance in solving the concerned problem.
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Zhang, Qi, Yang Xing, Man Yao, Jiacun Wang, Xiwang Guo, Shujin Qin, Liang Qi, and Fuguang Huang. "An Improved Discrete Bat Algorithm for Multi-Objective Partial Parallel Disassembly Line Balancing Problem." Mathematics 12, no. 5 (February 28, 2024): 703. http://dx.doi.org/10.3390/math12050703.

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Product disassembly is an effective means of waste recycling and reutilization that has received much attention recently. In terms of disassembly efficiency, the number of disassembly skills possessed by workers plays a crucial role in improving disassembly efficiency. Therefore, in order to effectively and reasonably disassemble discarded products, this paper proposes a partial parallel disassembly line balancing problem (PP-DLBP) that takes into account the number of worker skills. In this paper, the disassembly tasks and the disassembly relationships between components are described using AND–OR graphs. In this paper, a multi-objective optimization model is established aiming to maximize the net profit of disassembly and minimize the number of skills for the workers. Based on the bat algorithm (BA), we propose an improved discrete bat algorithm (IDBA), which involves designing adaptive composite optimization operators to replace the original continuous formula expressions and applying them to solve the PP-DLBP. To demonstrate the advantages of IDBA, we compares it with NSGA-II, NSGA-III, SPEA-II, ESPEA, and MOEA/D. Experimental results show that IDBA outperforms the other five algorithms in real disassembly cases and exhibits high efficiency.
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Filip, Florin Gheorghe. ""The Disassembly Line: Balancing and Modeling" - Book Review." International Journal of Computers Communications & Control 6, no. 3 (September 1, 2011): 581. http://dx.doi.org/10.15837/ijccc.2011.3.2137.

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<p>This book is about the disassembly of end-of-life products with particular emphasis on methods and techniques for solving the Disassembly Line Balancing Problem.</p><p>Disassembly is viewed as "the systematic separation and extracting valuable entities for possible future re-usage". In fact, disassembly is a distinct phase of the product lifecycle. It follows the "before life" phases (such as design and economical evaluation), "useful period" phases (such as manufacturing, distribution, usage and maintenance) and "end of life" phases (such as collecting, sorting). Disassembly might represent the essential first phase of the future activities, such as re-use and re-manufacturing and recycle. Due to the ever higher public awareness, the more and more strict regulations concerning environment quality preservation and increasing economic effectiveness and attractiveness for industry, the activities of recovering valuable parts and subassemblies have become a desirable alternative to the old fashioned disposal processes of end-of-life products.</p><p>The authors state, in the preface of the book, that the "disassembly line seems to be the most efficient way to disassemble a product". Consequently, the primary concern of the book is "the complete disassembly of [end-of-life] products on a paced disassembly line for component/material recovery purposes". The authors aim at investigating "the qualitative and quantitative aspects of multi-criteria solution sequences using the various combinatorial optimization techniques" (page 16) to solve the Disassembly Line Balancing Problem (DLPB). The DLBP consists in finding a disassembly feasible solution sequence which preserves precedence constraints and aims at attaining several objectives, such as minimizing the number of work stations and total idle time, ensuring similar idle time at each work station, while attempting to remove hazardous parts and materials and extracting highly demanded product components at the earliest moments possible and minimizing the number of direction changes required for disassembly (removing parts with similar part removal directions together), (page 102).</p><p>The book is composed of 29 chapters grouped into three parts entitled "Disassembly Background", "Disassembly-Line Balancing" and "Further Disassembly-Line Considerations" which address general aspects concerning disassembly processes, variations of methods and techniques to solve the DLBP, and other problems related to the disassembly line, respectively. <br /> <br /> Part I comprises six chapters which are meant to set the stage for the subsequent chapters. Various information concerning disassembly processes, assembly lines, disassembly lines, other related researches, graphical representations and computational complexity of combinatorial problems are provided.<br /> <br /> Part II is made up of 20 chapters and addresses the statement and analysis of the DLBP and several specific variations of methods and techniques which were adapted for solving the problem, tested on four application cases exprimental instances and compared. The objectives of this part of the book are: stating the mathematical model of DLBP, establishing the difficulty of the problem by using the complexity theory and determining the data sets and evaluation criteria to be used in analyzing the problem and solving techniques which are selected (page 99). <br /> <br /> It is demonstrated (in chapter 9) that the DLBP is a complex NP complete problem in the strong sense and necessitates specialized solution techniques. Accordingly, authors plea for combinatorial optimization approaches and select several algorithms to solve the problem. The techniques to be utilized to solve the DLBP are introduced in chapter 10 and their usage and performances in solving the problem are presented in chapters 12 through 19. There are seven techniques which are adapted, tested and compared. The exhaustive search is used to provide the optimal solution. Two metaheuristic approaches (genetic algorithms and ant colony optimization) are next studied. Two purely deterministic searches (the greedy algorithm and the "hunter-killer" search) and two 2-phase hybrid methods are adapted and tested.</p><p>The four experimental instances (the eight-part personal computer, the enhanced 10-part DLBP case, the 25-part cellular instance, and the size independent "a priori" benchmark with a known optimal solution) are described in chapter 11. Chapter 20 contains a detailed comparison of the six heuristic and metaheuristic techniques as applied to the DLBP with respect to several performance measures. Several complementary research results are reviewed in chapter 21 together with future research directions.<br /> <br /> Disassembly processes interact with other "before life", "useful", and "after life" periods of product usage and recovery. As a result, to make the picture complete, Part III addresses other areas of disassembly research such as product planning, line and facility design, operations scheduling and sequencing, inventory, "just-in-time", revenue and unbalanced lines (chapter 22 through 29).<br /> <br /> The authors of the book form a team who may be viewed as a fine and synergic combination of two complementary experiences and backgrounds from academia and industry. Seamus McGovern, an Electronics Engineer at the Volpe National Transportation System Center, holds a commission in the US Navy as an aerospace duty engineer as well as a part-time industrial engineering faculty appointment at the Northeastern University. Surendra M. Gupta is a professor of Mechanical and Industrial Engineering and a director of the Laboratory for Responsible Manufacturing at the Northeastern University. He has authored/co-authored over 400 technical papers and is a pioneer in the domain of the book.<br /> <br /> This book represents a very valuable work in a rather young research domain, which may be viewed as opened by the pioneering paper of Güngör and Gupta entitled "Disassembly Line in product Recovery (International Journal of Production Recovery, 40 (11), 2002). The volume mainly reflects the original studies of authors and their colleagues. It also makes an exhaustive and systematic review of the results which are reported in the domain scientific literature and are due to other scientists. The organization of the document is well thought and the presentation style is rigorous and clear. Subsequently, though information content is very dense and diverse, the book is accessible and its study is scientifically rewarding. Special remarks can be made to the uniform and coherent notation which is used throughout the book and to graphical illustrations. A final remark of appreciation is to be made to the excellent quality of editing and printing of the book due to the staff of McGraw-Hill Companies.<br /> <br /> In conclusion, the book is a timely work which contains relevant, inspiring and challenging information. Therefore, this reviewer warmly recommends it to the readers of academia and industry as well who are interested in modern manufacturing issues and combinatorial optimization methods and software.</p><p> </p>
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Paprocka, Iwona, and Bożena Skołud. "A Predictive Approach for Disassembly Line Balancing Problems." Sensors 22, no. 10 (May 22, 2022): 3920. http://dx.doi.org/10.3390/s22103920.

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In selective serial disassembly sequence planning, when the target node (component) is reached, the selective disassembly task is completed and the refurbished component is repaired, reused or remanufactured. Since the efficient utilization of existing resources is necessary, it is crucial to predict disassembly operation times and the condition of joints for recycling, reusing or remanufacturing. The method of estimating the disassembly times of a joint if it is intended for remanufacturing, recycling and reuse is an important and urgent requirement for research development and results. The aim of the paper is to investigate the disassembly system with predicted operation times and the quality of product connections (joints) in order to balance the line smoothness index, to minimize a line time factor, line efficiency and profit and minimize an ex post error. Disassembly times for remanufacturing, recycling and reuse are estimated separately based on the historical data of disassembly times and the quality of joints. The presented estimation method of disassembly operation times increases the reliability and efficiency of elaborated balances of tasks in lines. Underestimated disassembly operation times can be compensated for during the idle points in the successive cycles, provided that the transport operations are performed manually and that travel time determines the cycle time.
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Mete, Süleyman, Zeynel Abidin Çil, Eren Özceylan, and Kürşad Ağpak. "Resource Constrained Disassembly Line Balancing Problem." IFAC-PapersOnLine 49, no. 12 (2016): 921–25. http://dx.doi.org/10.1016/j.ifacol.2016.07.893.

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Kalayci, Can B., Olcay Polat, and Surendra M. Gupta. "A variable neighbourhood search algorithm for disassembly lines." Journal of Manufacturing Technology Management 26, no. 2 (March 2, 2015): 182–94. http://dx.doi.org/10.1108/jmtm-11-2013-0168.

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Purpose – The purpose of this paper is to efficiently solve disassembly line balancing problem (DLBP) and the sequence-dependent disassembly line balancing problem (SDDLBP) which are both known to be NP-complete. Design/methodology/approach – This manuscript utilizes a well-proven metaheuristics solution methodology, namely, variable neighborhood search (VNS), to address the problem. Findings – DLBPs are analyzed using the numerical instances from the literature to show the efficiency of the proposed approach. The proposed algorithm showed superior performance compared to other techniques provided in the literature in terms of robustness to reach better solutions. Practical implications – Since disassembly is the most critical step in end-of-life product treatment, every step toward improving disassembly line balancing brings us closer to cost savings and compelling practicality. Originality/value – This paper is the first adaptation of VNS algorithm for solving DLBP and SDDLBP.
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Jin, Liang, Xiao Zhang, Yilin Fang, and Duc Truong Pham. "Transfer Learning-Assisted Evolutionary Dynamic Optimisation for Dynamic Human-Robot Collaborative Disassembly Line Balancing." Applied Sciences 12, no. 21 (October 30, 2022): 11008. http://dx.doi.org/10.3390/app122111008.

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In a human-robot collaborative disassembly line, multiple people and robots collaboratively perform disassembly operations at each workstation. Due to dynamic factors, such as end-of-life product quality and human capabilities, the line balancing problem for the human-robot collaborative disassembly line is a dynamic optimisation problem. Therefore, this paper investigates this problem in detail and commits to finding the evolutionary dynamic optimisation. First, a task-based dynamic disassembly process model is proposed. The model can characterise all feasible task sequences of disassembly operations and the dynamic characteristics of tasks affected by uncertain product quality and human capabilities. Second, a multiobjective optimisation model and a feature-based transfer learning-assisted evolutionary dynamic optimisation algorithm for the dynamic human-robot collaborative disassembly line balancing problem are developed. Third, the proposed algorithm uses the balanced distribution adaptation method to transfer the knowledge of the optimal solutions between related problems in time series to track and respond to changes in the dynamic disassembly environment. Then, it obtains the optimal solution sets in a time-varying environment in time. Finally, based on a set of problem instances generated in this study, the proposed algorithm and several competitors are compared and analysed in terms of performance indicators, such as the mean inverted generational distance and the mean hypervolume, verifying the effectiveness of the proposed algorithm on dynamic human-robot collaborative disassembly line balancing.
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Xia, Xuhui, Wei Liu, Zelin Zhang, Lei Wang, Jianhua Cao, and Xiang Liu. "A Balancing Method of Mixed-model Disassembly Line in Random Working Environment." Sustainability 11, no. 8 (April 17, 2019): 2304. http://dx.doi.org/10.3390/su11082304.

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Disassembly is a necessary link in reverse supply chain and plays a significant role in green manufacturing and sustainable development. However, the mixed-model disassembly of multiple types of retired mechanical products is hard to be implemented by random influence factors such as service time of retired products, degree of wear and tear, proficiency level of workers and structural differences between products in the actual production process. Therefore, this paper presented a balancing method of mixed-model disassembly line in a random working environment. The random influence of structure similarity of multiple products on the disassembly line balance was considered and the workstation number, load balancing index, prior disassembly of high demand parts and cost minimization of invalid operations were taken as targets for the balancing model establishment of the mixed-model disassembly line. An improved algorithm, adaptive simulated annealing genetic algorithm (ASAGA), was adopted to solve the balancing model and the local and global optimization ability were enhanced obviously. Finally, we took the mixed-model disassembly of multi-engine products as an example and verified the practicability and effectiveness of the proposed model and algorithm through comparison with genetic algorithm (GA) and simulated annealing algorithm (SA).
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Dissertations / Theses on the topic "Disassembly line balancing"

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Altekin, Fatma Tevhide. "Profit Oriented Disassembly Line Balancing." Phd thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12605791/index.pdf.

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In this study, we deal with the profit oriented partial disassembly line balancing problem which seeks a feasible assignment of selected disassembly tasks to stations such that the precedence relations among the tasks are satisfied and the profit is maximized. We consider two versions of this problem. In the profit maximization per cycle problem (PC), we maximize the profit for a single disassembly cycle given the task times and costs, part revenues and demands and station costs. We propose a heuristic solution approach for PC based on the liner programming relaxation of our mixed integer programming formulation. In the profit maximization over the planning horizon problem (PH), the planning horizon is divided into time zones each of which may have a different disassembly rate and a different line balance. We also incorporate other issues such as finite supply of discarded product, subassembly and released part inventories availability, and smoothing of the number of stations across the zones. PH is decomposed into a number of successive per cycle problems, which are solved by a similar heuristic approach. Computational analysis is conducted for both problems and results are reported.
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Goksoy, Eda. "Disassembly Line Balancing Problem With Fixed Number Of Workstations And Finite Supply." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612060/index.pdf.

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In this thesis, we consider a Disassembly Line Balancing Problem (DLBP) with fixed number of workstations. We aim to maximize the total value of the recovered parts. We assume that there is a limited supply for the products to be disassembled. Different components can be obtained by disassembling different units of the product. Our aim is to assign the tasks to the workstations of the disassembly line so as to maximize the total value of the recovered parts. We present several upper and one lower bounding procedure. The results of our computational study have revealed the satisfactory behavior of our bounding mechanisms.
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Hu, Peng. "Stochastic and multi-criteria optimization for remanufacturing industry." Electronic Thesis or Diss., université Paris-Saclay, 2023. https://www.biblio.univ-evry.fr/theses/2023/interne/2023UPASG070.pdf.

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Le désassemblage des produits en fin de vie (EOL) dans la remanufacturation a attiré une attention considérable ces dernières années en raison de ses avantages en matière d'économie de ressources non renouvelables, de protection de l'environnement et de promotion de la croissance économique. Dans la littérature existante, 1) la plupart des problèmes stochastiques d'équilibrage de la ligne de désassemblage supposent que les distributions de probabilité des paramètres incertains soient connues ; 2) la majorité des problèmes d'équilibrage de la ligne de désassemblage se concentrent sur un seul produit ; 3) peu de travaux portent sur les problèmes de conception de la chaîne logistique inversée (RSC) liés à l'équilibrage de la ligne de désassemblage. En réalité, plusieurs RSC liées au désassemblage de produits EOL existent dans les industries de la remanufacturation, telles que l'automobile, les téléphones mobiles, etc. Pour combler ces lacunes dans la littérature, trois nouveaux problèmes liés à l'équilibrage de la ligne de désassemblage sont étudiés dans cette thèse.Tout d'abord, une DLBP à produit unique avec des informations partielles sur les temps de traitement des tâches est étudiée, où seules la moyenne, la borne inférieure et la borne supérieure des temps de traitement des tâches sont connues. L'objectif est de minimiser le coût de désassemblage. Pour le problème étudié, un modèle conjoint à contraintes de probabilités est proposé. Ensuite, une nouvelle formulation sans distribution et une formulation basée sur une approximation de programme de cônes de second ordre sont construites en fonction des propriétés du problème. Les résultats expérimentaux sur 7 instances de référence et sur 81 instances générées aléatoirement montrent l'efficacité de l'approche proposée.Deuxièmement, une nouve DLBP stochastique multi-produits avec un temps de traitement de tâche incertain est abordée, où seules la moyenne, l'écart type et la limite supérieure des temps de tâche sont disponibles. L'objectif est de minimiser le coût de désassemblage. Pour le problème, un modèle conjoint à contraintes de probabilités est formulé. Ensuite, sur la base de l'analyse du problème, le modèle conjoint à contraintes de probabilités est approximativement transformé en un modèle sans distribution. Ensuite, plusieurs inégalités valides et une méthode exacte de coupe et de résolution sont conçues pour résoudre efficacement le problème. Les résultats des expériences sur un exemple illustratif et sur 490 instances générées aléatoirement démontrent les bonnes performances du modèle proposé, des inégalités valides et de la méthode de résolution.Enfin, un nouveau problème de conception de la RSC lié à l'équilibrage de la ligne de désassemblage multi-produits est étudié, où l'approvisionnement en produits EOL, la demande en composants et les temps de traitement des tâches sont supposés incertains. Les objectifs sont de maximiser le profit attendu et de minimiser simultanément les émissions de dioxyde de carbone. Pour le problème, un modèle bi-objectif de programmation stochastique à deux étapes et non linéaire est formulé, et approximativement transformé en un modèle sans distribution linéaire en fonction des propriétés du problème. Ensuite, une méthode basée sur des contraintes epsilon-construites est proposée, dans laquelle une décomposition de Benders améliorée est conçue pour résoudre les problèmes transformés à objectif unique. Des expériences numériques comprenant une étude de cas et sur 200 instances générées aléatoirement sont menées pour évaluer les performances des méthodes proposées. De plus, une analyse de sensibilité est réalisée pour tirer des enseignements en matière de gestion
End-of-Life (EOL) products disassembly in remanufacturing has received extensive attention in recent years owing to their advantages in saving non-renewable resources, protecting the environment and promoting economic growth. In the existing literature, 1) most of stochastic disassembly line balancing problems assume that the probability distributions of uncertain parameters are known; 2) majority of disassembly line balancing problems focus on single product; 3) few works study the disassembly line balancing related reverse supply chain (RSC) design problems. In reality, multiple EOL products disassembly related RSC exist in remanufacturing industries, such as automobile, mobile phone, etc. To bring these research gaps, three new disassembly line balancing related problems are investigated in this thesis.Firstly, a single product disassembly line balancing problem (DLBP) with partial information of task processing times is studied, where only the mean, lower and upper bounds of task processing times are known. The objective is to minimize the disassembly cost. For the studied problem, a joint chance-constrained model is proposed. Then, a new distribution-free formulation and a second-order cone program approximation-based formulation are constructed based on problem properties. Experimental results on 7 benchmark instances and 81 randomly generated instances show the effectiveness and efficiency of the proposed approach.Secondly, a new stochastic multi-product DLBP with uncertain task processing time is addressed, where only the mean, standard deviation and upper bound of task times are available. The objective is to minimize the disassembly cost. For the problem, a joint chance-constrained model is formulated. Then, based on problem analysis, the joint chance-constrained model is approximately transformed into a distribution-free model. Subsequently, several valid inequalities and an exact lifted cut-and-solve method are designed to efficiently solve the problem. Experiments results on an illustrative example and 490 randomly generated instances demonstrate the good performances of the proposed model, valid inequalities and solution method.Finally, a novel multi-product disassembly line balancing related RSC design problem is investigated, where EOL products supply, components demand and task processing times are assumed to be uncertain. The objectives are to maximize the expected profit and minimize carbon dioxide emissions, simultaneously. For the problem, a bi-objective nonlinear two-stage stochastic programming model is formulated and approximately transformed to a linear distribution-free model based on problem properties. Then, an exact epsilon-constrained based method is proposed, in which an improved Benders decomposition is designed to solve the transformed single objective problems. Numerical experiments including one case study and 200 randomly generated instances are conducted to evaluate the performance of proposed methods. Moreover, sensitivity analysis is made to draw managerial insights
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Bentaha, Mohand Lounes. "Conception combinatoire des lignes de désassemblage sous incertitudes." Thesis, Saint-Etienne, EMSE, 2014. http://www.theses.fr/2014EMSE0758/document.

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Les travaux présentés dans ce manuscrit portent sur la conception des lignes de désassemblageen contexte incertain. Une ligne de désassemblage consiste en unesuccession de postes de travail où les tâches sont exécutées séquentiellement au niveau de chaque poste. La conception d'un tel système, de revalorisationdes produits en fin de vie, peut être ramenée à un problème d'optimisation combinatoire.Ce dernier cherche à obtenir une configuration permettant d'optimiser certains objectifs enrespectant des contraintes techniques, économiques et écologiques.Dans un premier temps, nous décrivons les activités principales de la revalorisation des produitsen fin de vie, en particulier le désassemblage. Puis, après présentation des travaux de la littératureportant sur la prise en compte des incertitudes des durées opératoires lors de la conception des lignesde production, nous nous focalisons sur l'étude des incertitudes des durées opératoires des tâches de désassemblage.Ainsi, nous présentons trois modélisations principales avec leurs approches de résolution.La première s'intéresse à la minimisation des arrêts de la ligne causés par les incertitudes des durées des opérationsde désassemblage. La deuxième cherche à garantir un niveau opérationnel de la ligne lié à sa cadence de fonctionnement.Le but de la troisième modélisation est l'intégration des problématiques de conception des ligneset de séquencement des tâches de désassemblage. Enfin, les performances des méthodes de résolutionproposées sont présentées en analysant les résultats d'optimisation sur un ensemble d'instances de taille industrielle
This thesis is dedicated to the problem of disassembly line design in uncertain context. A disassembly linecan be represented as a succession of workstations where tasks are performed sequentially at each workstation.The design of such a product recovery system can be reduced to a combinatorial optimization problem which seeksa line configuration that optimizes certain objectives under technical, economical and environmental constraints.We begin by describing the principal product recovery activities especially disassembly. Then, after a literaturereview on the design of production lines under uncertainty of task processing times, we focus our study on the consideration of the disassembly task time uncertainties. Hence, we present three main models as well as the associatedsolution approaches. The first one is interested in minimizing the line stoppages caused by the task processing timeuncertainties. The second one seeks to guarantee an operational level closely related with the line speed. The goal of thethird model is to integrate the line design and sequencing problems. At last, the performances of the proposed solutionapproaches are presented by analyzing the optimization results on a set of instances of industrial size
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"Profit Oriented Disassembly Line Balancing." Phd thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12605791/index.pdf.

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Yang, Yu-Chia, and 楊育佳. "Applying Adaptive Genetic Algorithm and AND/OR Graph to Disassembly Line Balancing Problems." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/7tjxr7.

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碩士
國立清華大學
工業工程與工程管理學系所
105
Due to increasing environmental concerns, manufacturers are forced to take back their products at the end of products’ useful functional life. Manufacturers need to arrange how to recover product components and subassemblies for reuse, remanufacture, and recycle to extend the life of materials in use and reduce the disposal volume. However, disassembly is the first essential step on product recovery. The disassembly line balancing problem (DLBP) is the process of allocating a set of disassembly tasks to an ordered sequence of workstations in such a way that optimizes performance (e.g., number of stations, hazardous components number, cycle time and work load). Therefore, in this study, a mathematical model is presented for the DLBP by considering resource and labor constraints. Utilizing a transformed AND/OR Graph (TAOG) as the main input is to ensure the feasibility of the precedence relations among the tasks. The objective of this model is to minimize the number of labors used under determined cycle time. This research proposed a three-phase heuristic adaptive genetic algorithm (AGA) to optimize the labors number in the disassembly line. The experimental results indicate that the proposed method is superior to the existing approaches for medium and large scale in DLBPs.
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Books on the topic "Disassembly line balancing"

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M, Gupta Surendra, ed. The disassembly line: Balancing and modeling. New York: McGraw-Hill, 2011.

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Book chapters on the topic "Disassembly line balancing"

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Weckenborg, Christian. "Disassembly Line Balancing with Collaborative Robots." In Operations Research Proceedings 2021, 389–94. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08623-6_57.

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Laili, Yuanjun, Yongjing Wang, Yilin Fang, and Duc Truong Pham. "Solutions for Robotic Disassembly Line Balancing." In Springer Series in Advanced Manufacturing, 143–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81799-2_10.

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Laili, Yuanjun, Yongjing Wang, Yilin Fang, and Duc Truong Pham. "Modelling of Robotic Disassembly Line Balancing." In Springer Series in Advanced Manufacturing, 71–83. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81799-2_6.

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Bentaha, Mohand Lounes, Olga Battaïa, and Alexandre Dolgui. "A Stochastic Formulation of the Disassembly Line Balancing Problem." In IFIP Advances in Information and Communication Technology, 397–404. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40352-1_50.

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Kalayci, Can B., Surendra M. Gupta, and Kenichi Nakashima. "A Simulated Annealing Algorithm for Balancing a Disassembly Line." In Design for Innovative Value Towards a Sustainable Society, 714–19. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3010-6_143.

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Laili, Yuanjun, Yongjing Wang, Yilin Fang, and Duc Truong Pham. "Evolutionary Optimisation for Robotic Disassembly Sequence Planning and Line Balancing." In Springer Series in Advanced Manufacturing, 85–110. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81799-2_7.

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Shwetank Avikal. "A Heuristic Based on AHP and TOPSIS for Disassembly Line Balancing." In Advances in Intelligent Systems and Computing, 833–42. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0448-3_69.

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Laili, Yuanjun, Yongjing Wang, Yilin Fang, and Duc Truong Pham. "Solutions for Mixed-Model Disassembly Line Balancing with Multi-robot Workstations." In Springer Series in Advanced Manufacturing, 153–80. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81799-2_11.

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Singh, Rakshit Kumar, Amit Raj Singh, and Ravindra Kumar Yadav. "Disassembly Line Balancing Using Recursive Optimization in Presence of Task-Failure." In Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 430–40. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85906-0_48.

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Kaya, Ümran, Halil İbrahim Koruca, and Samia Chehbi-Gamoura. "Development of a Flexible Software for Disassembly Line Balancing with Heuristic Algorithms." In Artificial Intelligence and Applied Mathematics in Engineering Problems, 1014–26. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36178-5_90.

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Conference papers on the topic "Disassembly line balancing"

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Gungor, Askiner, Surendra M. Gupta, Kishore Pochampally, and Sagar V. Kamarthi. "Complications in disassembly line balancing." In Intelligent Systems and Smart Manufacturing, edited by Surendra M. Gupta. SPIE, 2001. http://dx.doi.org/10.1117/12.417274.

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Chen, Qinglian, Bitao Yao, and Duc Truong Pham. "Sequence-Dependent Robotic Disassembly Line Balancing Problem Considering Disassembly Path." In ASME 2020 15th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/msec2020-8268.

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Abstract For the realization of environmental protection and resource conservation, remanufacturing is of great significance. Disassembly is a key step in remanufacturing, the disassembly line system is the main scenario for product disassembly, usually consisting of multiple workstations, and has prolific productivity. The application of the robots in the disassembly line will eliminate various problems caused by manual disassembly. Moreover, the disassembly line balancing problem (DLBP) is of great importance for environmental remanufacturing. In the past, disassembly work was usually done manually with high cost and relatively low efficiency. Therefore, more and more researches are focusing on the automatic DLBP due to its high efficiency. This research solves the sequence-dependent robotic disassembly line balancing problem (SDRDLBP) with multiple objectives. It considers the sequence-dependent time increments and requires the generated feasible disassembly sequence to be assigned to ordered disassembly workstations according to the specific robotic workstation assignment method. In robotic DLBP, due to the special characteristics of robotic disassembly, we need to consider the moving time of the robots’ disassembly path during the disassembly process. This is also the first time to consider sequence-dependent time increments while considering the disassembly path of the robots. Then with the help of crossover and mutation operators, multi-objective evolutionary algorithms (MOEAs) are proposed to solve SDRDLBP. Based on the gear pump model, the performance of the used algorithm under different cycle times is analyzed and compared with another two algorithms. The average values of the HV and IGD indicators have been calculated, respectively. The results show the NSGA-II algorithm presents outstanding performance among the three MOEAs, and hence demonstrate the superiority of the NSGA-II algorithm.
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Liu, Bin, Wenjun Xu, Jiayi Liu, Bitao Yao, Zude Zhou, and Duc Truong Pham. "Human-Robot Collaboration for Disassembly Line Balancing Problem in Remanufacturing." In ASME 2019 14th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/msec2019-2919.

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Abstract Remanufacturing is able to reduce the environmental pollution and the manufacturing cost by recycling the end-of-life products. Disassembly is a critical step for the production process of remanufacturing. Traditional disassembly process is finished by either manual disassembly that has low efficiency or robotic disassembly that has low flexibility. Human-robot collaboration for disassembly integrates the advantages of manual disassembly and robotic disassembly, which has both high efficiency and high flexibility. For the design step of human-robot collaborative disassembly line, how to balance the human-robot collaboration workstation is an important optimization objective. The major difference between the human-robot collaboration for disassembly line and the traditional disassembly line is that it is necessary to ensure safety of the operator. This paper develops a set of models for the human-robot collaboration for disassembly line balancing problem, and the task classification and the allocation of human-robot collaborative disassembly are conducted. In order to ensure the safety of human-robot collaboration in disassembly, the safety strategy between the operator and the robot is considered in disassembly workstations. Subsequently, human-robot collaboration for disassembly line balancing problem with three objectives is solved by an improved discrete bees algorithm. Finally, the case studies based on disassembling bearing parts are conducted to verify the proposed method.
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McGovern, Seamus M., and Surendra M. Gupta. "Combinatorial optimization methods for disassembly line balancing." In Optics East, edited by Surendra M. Gupta. SPIE, 2004. http://dx.doi.org/10.1117/12.570493.

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Fang, Yilin, and Xiao Zhang. "Individual-Based Transfer Learning for Dynamic Human-Robot Collaborative Disassembly Line Balancing." In ASME 2022 17th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/msec2022-85362.

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Abstract This paper analyzed the human-robot collaborative disassembly line balancing problem, which is significantly different from the traditional disassembly line balancing problem. In a human-robot collaborative disassembly line, multiple people and robots perform disassembly tasks at each workstation. Due to the uncertainties such as product quality and human capabilities, the human-robot collaborative disassembly line balancing problem is a dynamic optimization problem. We take into account the uncertainty of product quality and personnel capabilities. In addition, dynamic optimization problems require fast and accurate tracking of Pareto’s optimal solution set in a changing environment, and transfer learning has been proven appropriate. Therefore, an individual-based transfer learning-assisted evolutionary dynamic optimization algorithm has been developed to handle the human-robot collaborative disassembly line balancing problem. The algorithm uses an individual-based transfer learning technique to reuse experience, which accelerates the generation of the initial population and improves the convergence speed of solutions. Finally, based on a set of problem examples generated in this paper, the proposed algorithm is compared and analyzed with several competitors in terms of the mean inverted generational distance and the mean hyper-volume, verifying the effectiveness of the proposed algorithm on the dynamic human-robot collaborative disassembly line balancing. The results show that the proposed algorithm has good performance in large scale problems.
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Shuwei, Wang, Guo Xiuping, and Liu Jia. "The disassembly line balancing problem of type II." In Proceedings of the 2018 3rd Joint International Information Technology，Mechanical and Electronic Engineering Conference (JIMEC 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/jimec-18.2018.6.

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Liu, Ming, Zhongzheng Liu, Xin Liu, and Feng Chu. "Entropy-based bi-objective disassembly line balancing problem." In 2019 International Conference on Industrial Engineering and Systems Management (IESM). IEEE, 2019. http://dx.doi.org/10.1109/iesm45758.2019.8948166.

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Xu, Yunli, Bitao Yao, and Duc Truong Pham. "Research on Intelligent Optimization Algorithm for Multi-Objective Disassembly Line Balancing Problem." In ASME 2020 15th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/msec2020-8269.

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Abstract For resource reutilization and environmental protection, remanufacturing gets more and more attention in many countries. Disassembly is a critical part of traditional manufacturing industry, but the traditional disassembly operation is mainly done by workers, which is low-efficiency. Now the use of robots can improve production efficiency a lot, which involves the problem of disassembly line balancing. Due to the constraints such as product complexity and precedence relationship between tasks, when the number of tasks increases, the combination scheme between tasks increases geometrically, and conventional algorithms are difficult to solve the problems, the Disassembly Line Balancing Problem (DLBP) is generally necessary to optimize multiple objectives. In this research, the author selects a variety of intelligent optimization algorithms to resolve the complex disassembly line balancing problem in different dimensional objective space. Four representative algorithms are selected from three angles to be compared through three performance indicators. It is concluded that these algorithms have different search capabilities for different specifications and objective space. Researchers should carefully select the algorithm according to the specific disassembly problem. The appropriate algorithm should be selected according to the scale of the disassembly line problem and the number of optimization objectives in actual production practice.
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Liu, Ming, Rongfan Liu, and Feng Chu. "Distribution-free and Risk-averse Disassembly Line Balancing Problem." In 2019 International Conference on Industrial Engineering and Systems Management (IESM). IEEE, 2019. http://dx.doi.org/10.1109/iesm45758.2019.8948079.

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Johar, Badr O., and Surendra M. Gupta. "Balancing inventory generated from a disassembly line: mathematical approach." In Optics East 2006, edited by Surendra M. Gupta. SPIE, 2006. http://dx.doi.org/10.1117/12.686072.

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