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Journal articles on the topic 'Balancing of assembly-lines'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Chen, Sihua, and Louis Plebani. "HEURISTIC FOR BALANCING U-SHAPED ASSEMBLY LINES WITH PARALLEL STATIONS." Journal of the Operations Research Society of Japan 51, no. 1 (2008): 1–14. http://dx.doi.org/10.15807/jorsj.51.1.

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2

Gökçen, Hadi, Kürşad Ağpak, and Recep Benzer. "Balancing of parallel assembly lines." International Journal of Production Economics 103, no. 2 (October 2006): 600–609. http://dx.doi.org/10.1016/j.ijpe.2005.12.001.

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3

Praça,, Isabel C., and Carlos Ramos,. "Balancing Assembly Lines With Simulation." Journal for Manufacturing Science and Production 3, no. 1 (March 2000): 29–40. http://dx.doi.org/10.1515/ijmsp.2000.3.1.29.

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4

Özcan, Uğur. "Balancing stochastic parallel assembly lines." Computers & Operations Research 99 (November 2018): 109–22. http://dx.doi.org/10.1016/j.cor.2018.05.006.

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5

Dolgui, Alexandre. "Balancing Assembly and Transfer Lines." European Journal of Operational Research 168, no. 3 (February 2006): 663–65. http://dx.doi.org/10.1016/j.ejor.2004.07.021.

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6

Özcan, Uğur, Hadi Gökçen, and Bilal Toklu. "Balancing parallel two-sided assembly lines." International Journal of Production Research 48, no. 16 (August 4, 2009): 4767–84. http://dx.doi.org/10.1080/00207540903074991.

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7

Chiang, Wen-Chyuan, Timothy L. Urban, and Chunyong Luo. "Balancing stochastic two-sided assembly lines." International Journal of Production Research 54, no. 20 (April 7, 2015): 6232–50. http://dx.doi.org/10.1080/00207543.2015.1029084.

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8

Lapierre, Sophie D., Angel Ruiz, and Patrick Soriano. "Balancing assembly lines with tabu search." European Journal of Operational Research 168, no. 3 (February 2006): 826–37. http://dx.doi.org/10.1016/j.ejor.2004.07.031.

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9

Nicosia, Gaia, Dario Pacciarelli, and Andrea Pacifici. "Optimally balancing assembly lines with different workstations." Discrete Applied Mathematics 118, no. 1-2 (April 2002): 99–113. http://dx.doi.org/10.1016/s0166-218x(01)00259-1.

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10

Matondang. "Soft Computing in Optimizing Assembly Lines Balancing." Journal of Computer Science 6, no. 2 (February 1, 2010): 141–62. http://dx.doi.org/10.3844/jcssp.2010.141.162.

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11

Lapierre, S. D., and A. B. Ruiz. "Balancing assembly lines: an industrial case study." Journal of the Operational Research Society 55, no. 6 (June 2004): 589–97. http://dx.doi.org/10.1057/palgrave.jors.2601708.

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12

Scholl, Armin, and Robert Klein. "Balancing assembly lines effectively – A computational comparison." European Journal of Operational Research 114, no. 1 (April 1999): 50–58. http://dx.doi.org/10.1016/s0377-2217(98)00173-8.

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13

AGNETIS, A., A. CIANCIMINO, M. LUCERTINI, and M. PIZZICHELLA. "Balancing flexible lines for car components assembly." International Journal of Production Research 33, no. 2 (February 1995): 333–50. http://dx.doi.org/10.1080/00207549508930152.

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14

Araújo, Felipe F. B., Alysson M. Costa, and Cristóbal Miralles. "Balancing parallel assembly lines with disabled workers." European J. of Industrial Engineering 9, no. 3 (2015): 344. http://dx.doi.org/10.1504/ejie.2015.069343.

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15

Johnson, Roger V. "Optimally Balancing Large Assembly Lines with “Fable”." Management Science 34, no. 2 (February 1988): 240–53. http://dx.doi.org/10.1287/mnsc.34.2.240.

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16

Kucukkoc, Ibrahim, and David Z. Zhang. "Balancing of parallel U-shaped assembly lines." Computers & Operations Research 64 (December 2015): 233–44. http://dx.doi.org/10.1016/j.cor.2015.05.014.

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17

Weckenborg, Christian, Karsten Kieckhäfer, Christoph Müller, Martin Grunewald, and Thomas S. Spengler. "Balancing of assembly lines with collaborative robots." Business Research 13, no. 1 (August 6, 2019): 93–132. http://dx.doi.org/10.1007/s40685-019-0101-y.

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18

Scholl, Armin, Malte Fliedner, and Nils Boysen. "Absalom: Balancing assembly lines with assignment restrictions." European Journal of Operational Research 200, no. 3 (February 2010): 688–701. http://dx.doi.org/10.1016/j.ejor.2009.01.049.

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19

Purnomo, Hindriyanto Dwi, Hui-Ming Wee, and Hsin Rau. "Two-sided assembly lines balancing with assignment restrictions." Mathematical and Computer Modelling 57, no. 1-2 (January 2013): 189–99. http://dx.doi.org/10.1016/j.mcm.2011.06.010.

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20

JOHNSON, ROGER V. "Balancing assembly lines for teams and work groups." International Journal of Production Research 29, no. 6 (June 1991): 1205–14. http://dx.doi.org/10.1080/00207549108930128.

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21

BARTHOLDI, J. J. "Balancing two-sided assembly lines: a case study." International Journal of Production Research 31, no. 10 (October 1993): 2447–61. http://dx.doi.org/10.1080/00207549308956868.

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22

Merengo, C., F. Nava, and A. Pozzetti. "Balancing and sequencing manual mixed-model assembly lines." International Journal of Production Research 37, no. 12 (August 1999): 2835–60. http://dx.doi.org/10.1080/002075499190545.

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23

Scholl, A., and R. Klein. "ULINO: Optimally balancing U-shaped JIT assembly lines." International Journal of Production Research 37, no. 4 (March 1999): 721–36. http://dx.doi.org/10.1080/002075499191481.

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24

Urban, Timothy L. "Note. Optimal Balancing of U-Shaped Assembly Lines." Management Science 44, no. 5 (May 1998): 738–41. http://dx.doi.org/10.1287/mnsc.44.5.738.

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25

Pınarbaşı, Mehmet, Mustafa Yüzükırmızı, and Bilal Toklu. "Variability modelling and balancing of stochastic assembly lines." International Journal of Production Research 54, no. 19 (April 22, 2016): 5761–82. http://dx.doi.org/10.1080/00207543.2016.1177236.

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26

Özcan, Uğur, and Bilal Toklu. "Balancing of mixed-model two-sided assembly lines." Computers & Industrial Engineering 57, no. 1 (August 2009): 217–27. http://dx.doi.org/10.1016/j.cie.2008.11.012.

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27

Abdel-Shafi, Ahmed. "A Balancing Approach to Stochastic Assembly Lines.(Dept.M)." MEJ. Mansoura Engineering Journal 19, no. 1 (April 11, 2021): 124–35. http://dx.doi.org/10.21608/bfemu.2021.163078.

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28

Edokpia, Ralph O., and F. U. Owu. "Assembly Line Re-Balancing Using Ranked Positional Weight Technique and Longest Operating Time Technique: A Comparative Analysis." Advanced Materials Research 824 (September 2013): 568–78. http://dx.doi.org/10.4028/www.scientific.net/amr.824.568.

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Assembly line balancing is an attractive means of mass manufacturing and large-scale serial production systems. Traditionally, assembly lines are arranged in straight single-model lines and the problem is known as Simple Assembly Line balancing problem (SALBP). In this study, two heuristic assembly line balancing techniques known as the Ranked Positional Weight Technique, and the longest operational time technique, were applied to solve the problem of single-model line balancing problem in an assembling company with the aim of comparing the efficiencies of the application of the two algorithms. By using both methods, different restrictions were taken into consideration and two different lines balancing results were obtained. From the results obtained, Longest Operating Time Technique has higher line efficiency (85.16%) as compared to Ranked positional weight technique (79.28%) and it is easy to apply. The LOT technique gave the minimum number of workstations (27) as compared to the RPW technique (29); however the line efficiency and the number of workstation of the existing line are 74.67% and 31 respectively. This implies that the LOT technique has a better reduction in operating cost.

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29

Nearchou, A. C. "Multi-objective balancing of assembly lines by population heuristics." International Journal of Production Research 46, no. 8 (April 15, 2008): 2275–97. http://dx.doi.org/10.1080/00207540600988089.

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30

Kara, Yakup, Hadi Gökçen, and Yakup Atasagun. "Balancing parallel assembly lines with precise and fuzzy goals." International Journal of Production Research 48, no. 6 (February 23, 2009): 1685–703. http://dx.doi.org/10.1080/00207540802534715.

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31

Özcan, Uğur, Hakan Çerçioğlu, Hadi Gökçen, and Bilal Toklu. "Balancing and sequencing of parallel mixed-model assembly lines." International Journal of Production Research 48, no. 17 (August 17, 2009): 5089–113. http://dx.doi.org/10.1080/00207540903055735.

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32

Daoud, Slim, Lionel Amodeo, Farouk Yalaoui, Hicham Chehade, and Philippe Duperray. "New mathematical model to solve robotic assembly lines balancing." IFAC Proceedings Volumes 45, no. 6 (May 2012): 1353–58. http://dx.doi.org/10.3182/20120523-3-ro-2023.00183.

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33

Öztürk, Cemalettin, Semra Tunalı, Brahim Hnich, and M. Arslan Örnek. "Balancing and scheduling of flexible mixed model assembly lines." Constraints 18, no. 3 (February 19, 2013): 434–69. http://dx.doi.org/10.1007/s10601-013-9142-6.

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34

Yang, Caijun, Jie Gao, and Jinlin Li. "Balancing mixed-model assembly lines with adjacent task duplication." International Journal of Production Research 52, no. 24 (July 23, 2014): 7454–71. http://dx.doi.org/10.1080/00207543.2014.937012.

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35

Petropoulos, Dimitris I., and Andreas C. Nearchou. "A particle swarm optimization algorithm for balancing assembly lines." Assembly Automation 31, no. 2 (April 12, 2011): 118–29. http://dx.doi.org/10.1108/01445151111117700.

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36

Xu, Huijuan, Bugao Xu, and Jiang Yan. "Balancing apparel assembly lines through adaptive ant colony optimization." Textile Research Journal 89, no. 18 (December 18, 2018): 3677–91. http://dx.doi.org/10.1177/0040517518819836.

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The goal of this study was to introduce an effective optimization method to balancing one-piece flow assembly lines by rearranging manufacturing tasks necessary for an apparel production to minimize the number of workstations and the idle time of the assembly line under certain conditions. In this paper, we firstly define an assembly-line-balancing (ALB) problem in apparel production and established an objective function for minimizing the smoothness index, a term that measures the difference between the worktime and the targeted cycle time of each workstation on an assembly line. We then illustrate an adaptive ant colony (AAC) algorithm with modifications made on the traditional ant colony algorithm for solving the ALB problem. Finally, we present the experiments using real-world data provided by an apparel manufacturer to compare the results generated from the AAC and the prior practice of the company. It was demonstrated that the AAC could help the company reduce the number of workstations on its assembly lines and cut the idle time at most of the workstations.

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37

MATANACHAI, SITTICHAI, and CANDACE ARAI YANO. "Balancing mixed-model assembly lines to reduce work overload." IIE Transactions 33, no. 1 (January 2001): 29–42. http://dx.doi.org/10.1080/07408170108936804.

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38

Aguilar, Harry, Alberto García-Villoria, and Rafael Pastor. "A survey of the parallel assembly lines balancing problem." Computers & Operations Research 124 (December 2020): 105061. http://dx.doi.org/10.1016/j.cor.2020.105061.

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39

Hu, Xiaomei, Yangyang Zhang, Ning Zeng, and Dong Wang. "A Novel Assembly Line Balancing Method Based on PSO Algorithm." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/743695.

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Assembly line is widely used in manufacturing system. Assembly line balancing problem is a crucial question during design and management of assembly lines since it directly affects the productivity of the whole manufacturing system. The model of assembly line balancing problem is put forward and a general optimization method is proposed. The key data on assembly line balancing problem is confirmed, and the precedence relations diagram is described. A double objective optimization model based on takt time and smoothness index is built, and balance optimization scheme based on PSO algorithm is proposed. Through the simulation experiments of examples, the feasibility and validity of the assembly line balancing method based on PSO algorithm is proved.

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40

Hu, Xiaofeng, and Chunaxun Wu. "Workload smoothing in two-sided assembly lines." Assembly Automation 38, no. 1 (February 5, 2018): 51–56. http://dx.doi.org/10.1108/aa-09-2016-112.

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Purpose The purpose of this paper is to define new criteria for measuring workload smoothness of two-sided assembly lines and propose an algorithm to solve a two-sided assembly line balancing problem focusing on distributing the idle time and the workload as evenly as possible among the workstations. Design/methodology/approach This paper points out that the mean absolute deviation (MAD) and the smoothness index (SI) used to measure the workload smoothing in one-sided assembly lines are both inappropriate to evaluate the workload balance among workstations in two-sided assembly lines, as the idle time occur at the beginning and in the middle of a cycle within workstations. Then, the finish-time-based SI and MAD (FSI and FMAD) are defined, and a heuristic procedure based on the core mechanism of Moodie and Young method is proposed to smooth the assembly workload in two-sided assembly lines. Findings The computational results indicate that the proposed heuristic algorithm combined with the FMAD is effective in distributing the idle time and the workload among workstations as evenly as possible in two-sided assembly lines. Practical implications The two-sided assembly line balancing problem with the objective of the line efficiency can be effectively solved by the proposed approach. Originality/value The FMAD is proposed to effectively improve the workload smoothing in two-sided assembly lines.

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41

Chutima, Parames. "Research Trends and Outlooks in Assembly Line Balancing Problems." Engineering Journal 24, no. 5 (September 30, 2020): 93–134. http://dx.doi.org/10.4186/ej.2020.24.5.93.

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This paper presents the findings from the survey of articles published on the assembly line balancing problems (ALBPs) during 2014-2018. Before proceeding a comprehensive literature review, the ineffectiveness of the previous ALBP classification structures is discussed and a new classification scheme based on the layout configurations of assembly lines is subsequently proposed. The research trend in each layout of assembly lines is highlighted through the graphical presentations. The challenges in the ALBPs are also pinpointed as a technical guideline for future research works.

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42

Fathi, Masood, Amir Nourmohammadi, Morteza Ghobakhloo, and Milad Yousefi. "Production Sustainability via Supermarket Location Optimization in Assembly Lines." Sustainability 12, no. 11 (June 9, 2020): 4728. http://dx.doi.org/10.3390/su12114728.

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Manufacturers worldwide are nowadays in pursuit of sustainability. In the Industry 4.0 era, it is a common practice to implement decentralized logistics areas, known as supermarkets, to achieve production sustainability via Just-in-Time material delivery at assembly lines. In this environment, manufacturers are commonly struggling with the Supermarket Location Problem (SLP), striving to efficiently decide on the number and location of supermarkets to minimize the logistics cost. To address this prevalent issue, this paper proposed a Simulated Annealing (SA) algorithm for minimizing the supermarket cost, via optimally locating supermarkets in assembly lines. The efficiency of the SA algorithm was tested by solving a set of test problems. In doing so, a holistic performance index, namely the total cost of supermarkets, was developed that included both shipment cost and the installation cost across the assembly line. The effect of workload balancing on the supermarket cost was also investigated in this study. For this purpose, the SLP was solved both before and after balancing the workload. The results of the comparison revealed that workload balancing could significantly reduce the total supermarket cost and contribute to the overall production and economic sustainability. It was also observed that the optimization of material shipment cost across the assembly line is the most influencing factor in reducing the total supermarket cost.

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43

Kamal Uddin, Mohammad, Marian Cavia Soto, and Jose L. Martinez Lastra. "An integrated approach to mixed‐model assembly line balancing and sequencing." Assembly Automation 30, no. 2 (April 20, 2010): 164–72. http://dx.doi.org/10.1108/01445151011029808.

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PurposeDesign, balancing, and sequencing are the key issues associated with assembly lines (ALs). The purpose of this paper is to identify AL design issues and to develop an integrated methodology for mixed‐model assembly line balancing (MMALB) and sequencing. Primarily, mixed‐model lines are utilized for high‐variety, low‐volume job shop or batch production. Variation of a generic product is important for the manufacturers as the demand is mostly customer driven in the present global market.Design/methodology/approachDifferent AL design norms, performance indexes, and AL workstation indexes have been identified in the initial stage of this work. As the paper progresses, it has focused towards an integrated approach for MMALB and sequencing addressed for small‐ and medium‐scale assembly plants. A small‐scale practical problem has been justified with this integrated methodology implemented by MATLAB.FindingsALs execution in the production floor require many important factors to be considered. Different line orientations, production approaches, line characteristics, performance and workstation indexes, problem definitions, balancing and product sequencing in accordance with the objective functions are needed to be taken into account by the line designer.Originality/valueThis paper has highlighted the important AL design characteristics and also provided an integrated approach for balancing mixed‐model assembly lines (MMALs) combined with sequencing heuristic. The findings of this paper can be helpful for the designers while designing an AL. The integrated approach for balancing and sequencing of MMALs can be used as a functional tool for assembly‐based contemporary industries.

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44

Zeltzer, L., V. Limère, E. H. Aghezzaf, and H. Van Landeghem. "Balancing Mixed-Model Assembly Lines in Real World Complex Workstations." IFAC Proceedings Volumes 46, no. 9 (2013): 1714–19. http://dx.doi.org/10.3182/20130619-3-ru-3018.00424.

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45

Özcan, Uğur, and Bilal Toklu. "Balancing two-sided assembly lines with sequence-dependent setup times." International Journal of Production Research 48, no. 18 (September 2009): 5363–83. http://dx.doi.org/10.1080/00207540903140750.

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46

Shahanaghi, K., A. M. Yolmeh, and U. Bahalke. "Scheduling and balancing assembly lines with the task deterioration effect." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 224, no. 7 (January 7, 2010): 1145–53. http://dx.doi.org/10.1243/09544054jem1757.

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47

Gurevsky, E., Ö. Hazır, O. Battaïa, and A. Dolgui. "Robust balancing of straight assembly lines with interval task times." Journal of the Operational Research Society 64, no. 11 (November 2013): 1607–13. http://dx.doi.org/10.1057/jors.2012.139.

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48

Kellegöz, Talip. "Balancing Lexicographic Multi-Objective Assembly Lines with Multi-Manned Stations." Mathematical Problems in Engineering 2016 (2016): 1–20. http://dx.doi.org/10.1155/2016/9315024.

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In a multi-manned assembly line, tasks of the same workpiece can be executed simultaneously by different workers working in the same station. This line has significant advantages over a simple assembly line such as shorter line length, less work-in-process, smaller installation space, and less product flow time. In many realistic line balancing situations, there are usually more than one objective conflicting with each other. This paper presents a preemptive goal programming model and some heuristic methods based on variable neighborhood search approach for multi-objective assembly line balancing problems with multi-manned stations. Three different objectives are considered, minimizing the total number of multi-manned stations as the primary objective, minimizing the total number of workers as the secondary objective, and smoothing the number of workers at stations as the tertiary objective. A set of test instances taken from the literature is solved to compare the performance of all methods, and results are presented.

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49

Zamzam, Nessren, Amin K. El-Kharbotly, and Yomna Sadek. "Balancing time and physical effort in two-sided assembly lines." Ain Shams Engineering Journal 12, no. 3 (September 2021): 2921–33. http://dx.doi.org/10.1016/j.asej.2021.02.009.

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50

Nie, Li, Yue Wei Bai, Jun Wu, and Chang Tao Pang. "Integrated Approach for Flexible Mixed Model Assembly Lines Balancing and Model Sequencing Problem." Applied Mechanics and Materials 670-671 (October 2014): 1593–600. http://dx.doi.org/10.4028/www.scientific.net/amm.670-671.1593.

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The manufacturers nowadays are forced to respond very quickly to changes in the market conditions. To adopt flexible mixed model assembly lines (MMAL) is a preferred way for manufacturers to improve competitiveness. Managing a mixed model assembly line involves two problems: assigning assembly tasks to stations (balancing problem) and determining the sequence of products at each station (sequencing problem). In order to solve both balancing and sequencing problem in MMAL simultaneously, an integrated mathematical model based on mixed integer programming (MIP) is developed to describe the problem. In the model, general type precedence relations and task duplications are considered. Due to the NP-hardness of the balancing and sequencing problem of MMAL, GA is designed to search the optimal solution. The efficiency of the GA is demonstrated by a case study.

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