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Modern assembly line systems utilize robotics to replace human resources to achieve higher level of automation and flexibility. This work studies the task assignment and robot allocation in a robotic U-shaped assembly line. Two new mixed-integer programming linear models are developed to minimize the cycle time when the number of workstations is fi...
Citations
... [14] işçi atamalı, Li vd. [15] robotik, Wang vd. [16] karışık akışlı, Pınarbaşı [17] atama kısıtlamalı türlerini ele almışlardır. ...
... Problem NP-zor bir yapıya sahip olduğundan çözüm için meta-sezgisel tekniklere sıkça başvurulmaktadır. U-şekilli tip-2 problemin ve çeşitli versiyonlarının ele alındığı çalışmalarda geliştirilen meta-sezgisel teknikler arasında genetik algoritmalar [8,9,13,16], tavlama benzetimi [9,13], tabu arama [18], göçmen kuşlar algoritması [14,15] olduğu görülmektedir. ...
... Saf tavlama benzetimi algoritmasında ise SATS algoritması için verilen tavlama planı kullanılmıştır. Çözülen problemler 29-111 arasında değişen görev sayılarına sahiptirler: Buxey (29,8,7,14), Sawyer (30,8,7,14), Lutz1 (32,5,8,12), Gunther (35,10,6,15), Kilbridge (45,9,3,11) . ...
Son yıllarda, tam zamanında üretim felsefesini benimseyen işletmelerin artmasıyla birlikte U-şekilli montaj hatlarının kullanımı yaygınlaşmıştır. Dolayısıyla, U-şekilli montaj hattı dengeleme problemlerinin çözüm yöntemleri üzerine yapılan çalışmalar çoğalmaktadır. Bu çalışmada, iş yükü düzgünleştirme amacını ikincil amaç olarak dikkate alan, tip-2 U-şekilli basit montaj hattı dengeleme probleminin çözümü için, literatürde daha önce geliştirilmiş ve farklı problemler üzerinde etkinliği gösterilmiş olan, iki adet farklı yapıda melez tavlama benzetimi-tabu arama algoritması kullanılmıştır. Biri tavlama benzetimi, diğeri tabu arama üzerine inşa edilmiş bu algoritmalar ilk defa U-şekilli bir montaj hattı dengeleme problemine uygulanmaktadır. Bunun yanında, bu iki melez algoritma, performans karşılaştırma amacıyla, ilk defa bir problemin çözümünde beraberce kullanılmıştır. Melez algoritmaların performansları, literatürden alınmış test problemleri üzerinde, birbirleriyle ve tavlama benzetimi ve tabu arama algoritmalarının saf versiyonlarıyla karşılaştırılmıştır. Hesaplama sonuçları, çekirdeğini tabu aramanın oluşturduğu melez algoritmanın diğerlerine üstünlük sağladığını göstermektedir.
... Among these algorithms, migrating birds optimization (MBO) algorithm is a meta-heuristic algorithm proposed by Duman et al. (2012) to solve the combinatorial optimization problem. Previous studies have applied this algorithm to solve many problems (Xiao et al. 2020;Li et al. 2019;Zhang et al. 2018). ...
In the mixed-model assembly line balancing and sequencing problem (MALBSP), workstations are assumed to be constantly available. The failure of any workstation will make the entire assembly line stop working. Preventive maintenance (PM) is a way to maintain the workstation before its failure, reduce unexpected downtime, and prolong its useful life. Previous studies have considered PM scenarios (PMS) in the simple and U-shaped assembly line to improve production efficiency and smoothness effectively, but not in the mixed-model assembly line. This paper fills this research gap, and the MALBSP considering PMS (MALBSP_PMS) is studied in this paper. A mixed-integer linear programming model is proposed to minimize makespan and task alteration. A migrating birds optimization algorithm is improved (IMBO) to obtain well-distributed Pareto frontier solutions. This algorithm designs a restart mechanism and an intra-population crossover operator to avoid falling into the local optimal and enhance its searchability. Experimental results demonstrate the effectiveness of two improvements and the IMBO algorithm. In addition, a real-world case study is introduced to illustrate the importance of considering PM scenarios in MALBSP.
... Therefore, this article mainly optimizes this new problem via a mixed-integer linear programming (MILP) model and an enhanced migrating birds optimization (EMBO) algorithm. Considering that migrating birds optimization has been successfully applied to tackle the generalized ALBPs (Zhang et al. 2019;Li et al. 2019), this article aims to extend this new algorithm. The main contributions of this article are presented as follows: ...
In multi-manned assembly lines, more than one operator is allowed on the same workstation. Limited research has been carried out on sequence-dependent set-up times. Therefore, this article optimizes the multi-manned assembly line balancing problem with sequence-dependent set-up times using an enhanced migrating birds optimization (EMBO) algorithm. Sequence-dependent set-up times are embedded in two ways: forward and backward set-ups. EMBO designs a mixed neighbourhood search and acceptance criteria to help it escape from local optima, and a diversification mechanism to enhance the global exploration ability. Three types of experiment and two scenarios, with low and high set-up times, are conducted to test the performance of the mixed-integer linear programming (MILP) model and EMBO. The first experiment compares three MILP models (no, low and high set-up times) to illustrate the significance of set-up times. The final two experiments demonstrate the effectiveness of EMBO by comparison with the MILP model and six state-of-the-art methods.
... Modelling/objectives/assumptions Solution tools [190] Min {cycle time} Robotic U-Shaped ALB Processing time of a task depends on the robot assigned in the workstation MBO [191] Min {cycle time} MILP model for two-sided AL with sequence-dependent setup times and robot setup times Comparing 13 metaheuristic algorithms [192] Min {cycle time} MIP model for balancing and scheduling ALs with collaborative robots ...
In this review paper, recent developments in robotic problems are cited. A robotic manufacturing system includes at least a robot- as a material handling device-, a co-worker with human or autonomous robot, and some other relevant systems. Due to the lack of a thorough analysis and listing of recent robotic articles which apply optimization techniques, this paper, thus, aims to report an extensive archive of robotic papers on a structured classification for robotic problems for the first time which includes robotic cell, robotic disassembly, and robotic assembly from 2005 to September 2021. Descriptive statistics are also provided which include the number of publications as well as the authorship analysis and as a final point, future trends towards the robotic studies are introduced. Moreover, the review shows that, heuristic or metaheuristic algorithms are the most frequently used tools to solve the robotic application problems. The author hopes that this review will open new windows in theoretical and applied studies of robots and establish a foundation for robotic problems in industry.
... Assuming that the starting point of the joint rotation angle of the robotic arm is θ(0), the two positions of the joint, rotation angle can be determined from the starting point and the ending point. To ensure continuous joint speed, the joint speed at the starting and ending time should be zero, so that the constraint conditions are obtained [12,13]. ...
With the rapid development of science and technology, the current ordinary industrial manipulator cannot complete the task well, because it is difficult to control. This research mainly discusses the planning and control of the mobile manipulator for the operation of restricted motion objects in an intelligent environment. In this study, the rapid search random tree (RRT) method is used to study the obstacle avoidance motion planning of the manipulator. The 6-axis robotic arm system uses CAN (controller area network) bus to connect each joint in series and then connect to the multi-axis controller Maestro, and the host computer and Maestro send and receive control commands based on the TCP/IP protocol. A 1-DOF grip is installed at the end of the robotic arm, and the grip is connected to the end of the robotic arm (i.e., at the wrist joint of the robotic arm) through a 6-dimensional force 1 torque sensor. The operating system of the host computer is Ubuntu 14.04. The position of the object is recognized through Kinect, and the position of the object is sent to the robotic arm control software. The PTP (precision time protocol) of the robotic arm moves to a certain distance in front of the object, and then the movement of the robotic arm is controlled by visual servoing to complete the object capture. Each joint of the manipulator uses a speed control mode. In a single control cycle, the joint angular velocity of the manipulator remains unchanged. The controller used by the robotic arm is a 51-core STC12C5410AD single-chip microcomputer, which ensures the response speed of the joint motor linkage. In the environment of multiple obstacles, the RRT algorithm has 10 simulation experiments, the average sampling time is 95.651 s, and the average sampling point is 1308. The results show that the RRT algorithm proposed in this study enables the manipulator to move from the starting point to the endpoint in the environment of multiple obstacles, while avoiding the obstacles, and the mobile manipulator can better operate the motion-limited objects.
... For the studies on the RUALBP, Nilakantan and Ponnambalam (2016) formulated this problem to minimize the cycle time for the first time and develop the particle swarm optimization to solve this problem. Li et al. (2019a) presented two new MILP models with the objective of minimizing the cycle time and develop an improved migrating birds optimization algorithm, which outperforms seven other implemented algorithms. Zhang et al. (2019b) considered the energy consumption and the cycle time in the RUALBP. ...
... One possible drawback of this method is that the decoding procedure is conducted for many times to obtain the proper initial cycle time for one encoding scheme. Hence, on the basis of Li et al. (2019a and several others, this study proposes the iterative mechanism to update the initial cycle time during the algorithm' evolution. The proposed iterative mechanism is presented in Algorithm 2, where is the best cycle time during the evolution. ...
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.
... And there are also some studies to consider different line configurations and different products (models). Specifically, the RALBP is extended to other line layouts including U-shaped line Li et al. 2019a;Zhang et al. 2018Zhang et al. , 2019, two-sided line (Li et al. 2016(Li et al. , b, 2018aAghajani et al. 2014) and parallel line (Çil et al. 2017b). Çil et al. (2017a), Rabbani et al. (2016) and Aghajani et al. (2014) consider the mixed-model RALBP, and Li et al. (2018c) tackle the balancing and sequencing of mixed-model robotic assembly line. ...
Robots are extensively used during the era of Industry 4.0 to achieve high productivity, better quality and lower cost. While designing a robotic assembly line, production managers are concerned about the cost involved in such a system development. Most of the research reported till date did not consider purchasing cost while optimizing the design of a robotic assembly line. This study presents the first attempt to study the cost-oriented robotic assembly line balancing problem with setup times to minimize the cycle time and total purchasing cost simultaneously. A mixed-integer linear programming model is developed to formulate this problem. The elitist non-dominated sorting genetic algorithm (NSGA-II) and improved multi-objective artificial bee colony (IMABC) algorithm are developed to achieve a set of Pareto solutions for the production managers to utilize for selecting the better design solution. The proposed IMABC develops new employed bee phase and scout phase, which selects one solution in the permanent Pareto archive to replace the abandoned solution, to enhance exploration and exploitation. The comparative study on a set of generated instances demonstrates that the proposed model is capable of achieving the proper tradeoff between line efficiency and purchasing cost, and the proposed NSGA-II and IMABC achieve competing performance in comparison with several other multi-objective algorithms.
... Type-E maximizes the line efficiency with a variable number of workstations and a variable cycle time (Mozdgir et al., 2013) for continuous improvement. Based on the above, many variants are extended to consider more features existing in practical application, i.e. the mixed-model (Akpınar and Mirac Bayhan, 2011;Çil et al., 2020;Hacı et al., 2020;Zhao et al., 2016), two-sided/Ushaped assembly lines (Zhang et al., 2019a(Zhang et al., , 2020b, the existence of multi-skilled workers or assembly robots (Çil et al., 2020;Li et al., 2019;Sabar et al., 2009;Zacharia and Nearchou, 2016), etc. It is worth noting that in all of the above literature, machines are assumed available and the shutdown of any workstation is not taken into account, which is impractical. ...
... Meta-heuristic algorithms are often regarded as an efficient technique for tackling large-scale practical problems, attributing to their excellent balance between exploration and exploitation in search spaces. In previous studies, a group of meta-heuristic algorithms is hired to solve the ALBP-related problems, including genetic algorithm (Foroughi and Gökçen, 2019), water flow algorithm (Nourmohammadi et al., 2019), imperialist competitive algorithm (Zhang et al., 2019a), migrating birds optimization (Li et al., 2019), particle swarm optimization (Ab Rashid et al., 2019), artificial fish swarm optimization algorithm (Zhong et al., 2019), etc. ...
The current assembly line balancing studies ignore the preventive maintenance (PM) of machines in some workstations, implying that the already-known PM information has been completely missed. Moreover, PM may bring about a production stoppage for a considerable time. Hence, this paper considers PM scenarios into the assembly line balancing problem to improve the production efficiency and smoothness simultaneously. For this multi-objective problem, a heuristic rule relying on the tacit knowledge is dug up via gene expression programming to obtain an acceptable solution quickly. Then, an enhanced grey wolf optimizer algorithm with two improvements is proposed to achieve Pareto front solutions. Specifically, a variable step-size decoding mechanism accelerates the speed of the algorithm; the specially-designed neighbor operators prevent the algorithm from trapping in local optima. Experiment results demonstrate that the discovered heuristic rule outperforms other existing rules; the joint of improvements endows the proposed meta-heuristic with significant superiority over three variants and other six well-known algorithms. Besides, a real-world case study is conducted to validate the discovered rule and the proposed meta-heuristic.
... The presented techniques follow a few core steps such as data normalization before processing to the next step, ROI detection, extraction of useful features through traditional techniques, and recognition [11]. The more recent, the selection of best features from the original vector is a key challenge and many studies are proposed like Genetic Algorithm (GA) [12], entropy-based techniques [13,14], distance-based methods [15], and name a few [16][17][18][19]. The involvement of deep learning also gives prominent results when the input data is too large in numbers [11]. ...
Human Activities Recognition (HAR) is an important research topic and its applications are spread in all the fields of computer vision and machine learning including video surveillance, robotics, and name a few more. In this paper, a new traditional feature fusion and selection-based method is proposed for automated HAR. The proposed methodology consists of three core steps- optical flow-based motion region extraction and later ROI detection, shape and gray level difference matrix (GLDM) features are combined in one matrix based on seniority value indexes, and finally, Reyni entropy-controlled Euclidean classifier based best features selection. The final selected features are put to Cubic SVM for final recognition. The validation of the proposed technique is conducted on three datasets- KTH, YouTube, and Weizmann and achieved an accuracy of 99.30%, 99.80%, and 99.60%, respectively. Overall, Cubic SVM outperforms among existing techniques.
... Meanwhile, this algorithm has successfully applied in related combination optimization problems. For instance, Pan applied MBO to mixed flow shop scheduling [33]; Zhang et al. [34] studied the problem of hybrid flow shop hybridizing with lot streaming (HLFS) with the objective of minimizing the total flow time with Migratory bird optimization algorithm; Zhang et al. [35] solved the u-shaped assembly line balance problem and worker assignment problem with MBO; Li et al. [36] applied improved MBO to the mathematical model of robot U-shaped assembly Line Balance problem; Janardhanan et al. [37] solved the problem of assignment and balance of two-sided assembly line workers with migratory bird optimization algorithm. Hence this work aims to extend a new version of MBO to tackle this proposed problem. ...
To address the printed circuit board shop scheduling problem, a dynamic based on multiindicator bottleneck degree is proposed to formulate this complex flexible job shop scheduling problem (FJSP). Then, a bottleneck degree-based migrating birds optimization algorithm (MBO) is proposed to tackle this NP-hard problem. Specifically, a multi-indicator assessment model is first developed to obtain the bottleneck degree, and then a two-layer code-decoding structure based on the variable domain structure and the addition of the improved migratory bird algorithm with competitive mechanisms are employed to improve the effectiveness. Finally, the computational experiments demonstrate that the proposed dynamic scheduling approach based on bottleneck degrees and improved migrating bird algorithms can obtain promising results and it outperforms several other algorithms.
