Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

Li, Zixiang; Janardhanan, Mukund Nilakantan; Ashour, Amira S.; Dey, Nilanjan

doi:10.1007/s00521-018-3957-4

Cited by 25 publications

(11 citation statements)

References 48 publications

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“…Flexibility (Avikal et al, 2013;S ahin and Kellegöz, 2017) and re-configurability (Wang et al, 2009;Li et al, 2019) should be considered when designing a manufacturing system which should have the capability of adapting dynamic changes of product varieties and production volumes in a cost effective manner (Kara et al, 2011). Adapting these issues in manual assembly, WWALs are frequently used in industrial practices (Al-Zuheri et al, 2012;Wang and Bennett, 2014;Durmusoglu et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Baykaso glu and Dereli (2009) proposed a novel algorithm which integrates ranked positional weight heuristic, computer method for sequencing operations for assembly lines algorithm and ant colony optimization for solving UALBP to minimize the number of stations. Moreover, migrating birds optimization (Li et al, 2019) and grey wolf optimization (Zhang et al, 2019) are proposed for robotic UALBP.…”

Section: Literature Reviewmentioning

confidence: 99%

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A novel optimization approach for segmented rabbit chase oriented U-type assembly line design: an application from lighting industry

Çevikcan

Durmuşoğlu

2020

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Purpose Rabbit chase (RC) is used as one of the most effective techniques in manufacturing systems, as such systems have high level of adaptability and increased productivity in addition to providing uniform workload balancing and skill improving environment. In assembly systems, RC inspires the development of walking worker assembly line (WWAL). On the other hand, U-type assembly lines (UALs) may provide higher worker utilization, lower space requirement and more convenient internal logistics when compared to straight assembly lines. In this context, this study aims to improve assembly line performance by generating RC cycles on WWAL with respect to task assignment characteristics of UAL within reasonable walking distance and space requirement. Therefore, a novel line configuration, namely, segmented rabbit chase-oriented U-type assembly line (SRCUAL), emerges. Design/methodology/approach The mathematical programming approach treats SRCUAL balancing problem in a hierarchical manner to decrease computational burden. Firstly, segments are generated via the first linear programming model in the solution approach for balancing SRCUALs to minimize total number of workers. Then, stations are determined within each segment for forward and backward sections separately using two different pre-emptive goal programming models. Moreover, three heuristics are developed to provide solution quality with computational efficiency. Findings The proposed mathematical programming approach is applied to the light-emitting diode (LED) luminaire assembly section of a manufacturing company. The adaptation of SRCUAL decreased the number of workers by 15.4% and the space requirement by 17.7% for LED luminaire assembly system when compared to UAL. Moreover, satisfactory results for the proposed heuristics were obtained in terms of deviation from lower bound, especially for SRCUAL heuristics I and II. Moreover, the results indicate that the integration of RC not only decreased the number of workers in 40.28% (29 instances) of test problems in U-lines, but also yielded less number of buffer points (48.48%) with lower workload deviation (75%) among workers in terms of coefficient of variation. Practical implications This study provides convenience for capacity management (assessing capacity and adjusting capacity by changing the number of workers) for industrial SRCUAL applications. Meanwhile, SRCUAL applications give the opportunity to increase the capacity for a product or transfer the saved capacity to the assembly of other products. As it is possible to provide one-piece flow with equal workloads via walking workers, SRCUAL has the potential for quick realization of defects and better lead time performance. Originality/value To the best of the authors’ knowledge, forward–backward task assignments in U-type lines have not been adapted to WWALs. Moreover, as workers travel overall the line in WWALs, walking time increases drastically. Addressing this research gap and limitation, the main innovative aspect of this study can be considered as the proposal of a new line design (i.e. SRCUAL) which is sourced from the hybridization of UALs and WWAL as well as the segmentation of the line with RC cycles. The superiority of SRCUAL over WWAL and UAL was also discussed. Moreover, operating systematic for SRCUAL was devised. As for methodical aspect, this study is the first attempt to solve the balancing problem for SRCUAL design.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A novel optimization approach for segmented rabbit chase oriented U-type assembly line design: an application from lighting industry

Çevikcan

Durmuşoğlu

2020

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“…Faced with increased labor cost and concerns of efficiency, one of the trend that is being adopted in industries are the replacement of the human workers with robots. U-shaped assembly line with robots to complete all the tasks are referred to as robotic U-shaped assembly line (Li et al, 2019a). This type of line will help to reduced labor cost, higher accuracy and higher stability.…”

Section: Nomenclaturementioning

confidence: 99%

Models and algorithms for U-shaped assembly line balancing problem with collaborative robots

Janardhanan

Tang

et al. 2022

Preprint

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The collaborative robot (cobot) are increasingly being utilized in industries due to the advancement in the field of robotic technology and also due the increase in labor costs. The cobots on the assembly line can be utilized to complete the tasks independently or assist the workers to complete the tasks. This study considers the U-shaped assembly line balancing problem with cobots, where several cobots with different purchasing costs are selected under the budget constraint. Three mixed-integer programming models are formulated to optimize the cycle time and the built models are capable of solving the small-sized instances optimally. Two algorithms, artificial bee colony algorithm and migrating bird optimization algorithm are developed and improved to tackle the large-sized instances, where new encoding scheme and decoding procedure are developed for this new problem. The computational tests demonstrate that the utilization of collaborative robots reduces the cycle time effectively in the assembly line. The comparative study on a set of instances shows that the proposed methodologies obtain competing performance in comparison with other 12 implemented algorithms.

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“…The experiments showed that the SAs are superior to other algorithms under the same problem assumptions. In addition to the study of one-sided straight assembly line, Li et al proposed a discrete cuckoo search algorithm [13] and a migrating birds optimization [14] to solve the two-sided and U-type RALB problems, respectively. Moreover, there are also some papers considering the reduction of energy consumption brought by robots in robotic assembly lines [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

An estimation of distribution algorithm with branch-and-bound based knowledge for robotic assembly line balancing

Sun

2020

Complex Intell. Syst.

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Robotic assembly lines are widely used in manufacturing industries. The robotic assembly line balancing (RALB) problem aims to balance the workloads among different workstations and optimize the assembly line efficiency. This paper addresses a particular type of RALB problem, which minimizes the assembly line cycle time by determining the task and robot assignment in each workstation under precedence constraints. To solve the problem, we present an effective hybrid algorithm fusing the estimation of distribution algorithm and branch-and-bound (B&B) based knowledge. A problem-specific probability model is designed to describe the probabilities of each task being assigned to different workstations. Based on the probability model, an incremental learning method is developed and a sampling mechanism with B&B based knowledge is proposed to generate new feasible solutions. The fuse of B&B based knowledge is able to reduce the search space of EDA while focusing the search on the promising area. To enhance the exploitation ability, a problem-specific local search is developed based on the critical workstation to further improve the quality of elite solutions. The computational complexity of the proposed algorithm is analyzed, and the effectiveness of the B&B based knowledge and the problem-specific local search is demonstrated through numerical experiments. Moreover, the performance of the proposed algorithm is compared with existing algorithms on a set of widely-used benchmark instances. Comparative results demonstrate the effectiveness and efficiency of the proposed algorithm.

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Mathematical models and migrating birds optimization for robotic U-shaped assembly line balancing problem

Cited by 25 publications

References 48 publications

A novel optimization approach for segmented rabbit chase oriented U-type assembly line design: an application from lighting industry

A novel optimization approach for segmented rabbit chase oriented U-type assembly line design: an application from lighting industry

Models and algorithms for U-shaped assembly line balancing problem with collaborative robots

An estimation of distribution algorithm with branch-and-bound based knowledge for robotic assembly line balancing

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