A review on Robotic assembly line balancing and metaheuristic in manufacturing industry (original) (raw)
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Optimizing the Robot Traveling Time (ORTT) in Robot Assembly Line Balancing Problem (RALBP)
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. Advanced manufacturing technologies provide a great potential for improving manufacturing performance to compete in the global markets. Robot is one kind of the AMT and play an important role in flexible assembly systems. One important configuration of robots in flexible assembly is the use of robotic assembly lines. The rationale for performing assembly with robots in an assembly line configuration is due to specialization in operations. Flexibility and automation in assembly lines can be achieved by the use of robots. Optimizing the robotic assembly line balancing (RALB) is an important task it must done to aims at maximizing the production rate of the line. An attempt has been made in this paper to present a heuristic mathematical model to optimize the robot traveling time. Finally the optimization model was tested based on case study and the results show the comparison between the initial and optimization data.
Assembly Automation, 2018
Purpose Robots are used in assembly lines because of their higher flexibility and lower costs. The purpose of this paper is to develop mathematical models and simulated annealing algorithms to solve the robotic assembly line balancing (RALB-II) to minimize the cycle time. Design/methodology/approach Four mixed-integer linear programming models are developed and encoded in CPLEX solver to find optimal solutions for small-sized problem instances. Two simulated annealing algorithms, original simulated annealing algorithm and restarted simulated annealing (RSA) algorithm, are proposed to tackle large-sized problems. The restart mechanism in the RSA methodology replaces the incumbent temperature with a new temperature. In addition, the proposed methods use iterative mechanisms for updating cycle time and a new objective to select the solution with fewer critical workstations. Findings The comparative study among the tested algorithms and other methods adapted verifies the effectiveness o...
Applied Mathematical Modelling, 2019
Industries are incorporating robots into assembly lines due to their greater flexibility and reduced costs. Most of the reported studies did not consider scheduling of tasks or the sequencedependent setup times in an assembly line, which cannot be neglected in a real-world scenario. This paper presents a study on robotic assembly line balancing, with the aim of minimizing cycle time by considering sequence-dependent setup times. A mathematical model for the problem is formulated and CPLEX solver is utilized to solve small-sized problems. A recently developed metaheuristic Migrating Birds Optimization (MBO) algorithm and set of metaheuristics have been implemented to solve the problem. Three different scenarios are tested (with no setup time, and low and high setup times). The comparative experimental study demonstrates that the performance of the MBO algorithm is superior for the tested datasets. The outcomes of this study can help production managers improve their production system in order to perform the assembly tasks with high levels of efficiency and quality.
A beam search approach for solving type II robotic parallel assembly line balancing problem
Applied Soft Computing, 2017
Robotic assembly line Robotic parallel assembly lines Highlights This is the first adaptation of beam search algorithm to solve the RALB problem This is the first study which models a parallel RALB problem. Three different heuristic approaches based on beam search are developed The algorithm was thoroughly tested on small and large sized instances Comparison with DE and PSO proves the superiority of the proposed method The algorithm provides near optimal solution for this NP-complete problem Abstract-In a robotic assembly line, a series of stations are arranged along a conveyor belt and a robot performs on tasks at each station. Parallel assembly lines can provide improving line balance, productivity and so on. Combining robotic and parallel assembly lines ensure increasing flexibility of system, capacity and decreasing breakdown sensitivity. Although aforementioned benefits, balancing of robotic parallel assembly lines is lackingto the best knowledge of the authors-in the literature. Therefore, a mathematical model is proposed to define/solve the problem and also iterative beam search (IBS), best search method based on IBS (BIBS) and cutting BIBS (CBIBS) algorithms are presented to solve the large-size problem due to the complexity of the problem. The algorithm also tested on the generated benchmark problems for robotic parallel assembly line balancing problem. The superior performances of the proposed algorithms are verified by using a statistical test. The results show that the algorithms are very competitive and promising tool for further researches in the literature.
Literature review of assembly line balancing problems
The International Journal of Advanced Manufacturing Technology, 2014
Mass production system design is a key for the productivity of an organization. Mass production system can be classified into production line machining a component and production line assembling a product. In this paper, the production line assembling a product, which is alternatively called as assembly line system, is considered. In this system, balancing the assembly line as per a desired volume of production per shift is a challenging task. The main objectives of the assembly line design are to minimize the number of workstations for a given cycle time (type 1), to minimize the maximum of the times of workstations for a given number of workstations (type 2), and so forth. Because this problem comes under combinatorial category, the use of heuristics is inevitable. Development of a mathematical model may also be attempted, which will help researchers to compare the solutions of the heuristics with that of the model. In this paper, an attempt is made to present a comprehensive review of literature on the assembly line balancing. The assembly line balancing problems are classified into eight types based on three parameters, viz. the number of models (single-model and multi-model), the nature of task times (deterministic and probabilistic), and the type of assembly line (straight-type and U-type). The review of literature is organized as per the above classification. Further, directions for future research are also presented.
A review on hybrid metaheuristics in solving assembly line balancing problem
THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)
Recently, it is noteworthy that the solving of optimization problem has been shifted from heuristic towards hybrid metaheuristics. This paper demonstrates a review in solving assembly line balancing problem by using metaheuristics hybridization. Generally, hybrid metaheuristic is a combination of two or more algorithms. This combination is helpful in improving the weakness of these two algorithms. In this work, we provide a literature review of existing publications for the past years which from year 2002 to 2018. Hereby, this survey can recommend the important gap for future research assembly line balancing problem in applying the hybrid metaheuristics.
This paper presents a comprehensive review and evaluation of heuristics and meta-heuristics for the two-sided assembly line balancing problem. Though a few reviews have been presented, some latest methods are not included and there is no comparison of the meta-heuristics in terms of their performances. Furthermore, since various kinds of encoding schemes, decoding procedures and objective functions have been applied, the results cannot be generalized and the published comparison might be unfair. This paper contributes to knowledge by comparing the published methods, ranging from well-known simulated annealing to recent published iterated local search, and evaluating the six encoding schemes, 30 decoding procedures and five objective functions on the performances of the meta-heuristics meanwhile. The experimental design approach is applied to obtain valid and convincing results by testing algorithms under four termination criteria. Computational results demonstrate that the proper selection of encoding scheme, decoding procedure and objective function improves the performance of the algorithms by a significant margin. Another unique contribution of this paper is that 15 new best solutions are obtained for the large-sized type-II two-sided assembly line balancing problem during the re-implementation and evaluation of the meta-heuristics tested. Please cite this article as: Zixiang Li , Ibrahim Kucukkoc , J. Mukund Nilakantan , Comprehensive review and evaluation of heuristics and meta-heuristics for two-sided assembly line balancing problem ,
A genetic algorithm for robotic assembly line balancing
European Journal of Operational …, 2006
Flexibility and automation in assembly lines can be achieved by the use of robots. The robotic assembly line balancing (RALB) problem is defined for robotic assembly line, where different robots may be assigned to the assembly tasks, and each robot needs different assembly times to perform a given task, because of its capabilities and specialization. The solution to the RALB problem includes an attempt for optimal assignment of robots to line stations and a balanced distribution of work between different stations. It aims at maximizing the production rate of the line. A genetic algorithm (GA) is used to find a solution to this problem. Two different procedures for adapting the GA to the RALB problem, by assigning robots with different capabilities to workstations are introduced: a recursive assignment procedure and a consecutive assignment procedure. The results of the GA are improved by a local optimization (hill climbing) work-piece exchange procedure. Tests conducted on a set of randomly generated problems, show that the Consecutive Assignment procedure achieves, in general, better solution quality (measured by average cycle time). Further tests are conducted to determine the best combination of parameters for the GA procedure. Comparison of the GA algorithm results with a truncated Branch and Bound algorithm for the RALB problem, demonstrates that the GA gives consistently better results.
Comparative Analysis of Different Heuristics for Cost Oriented Assembly Line Balancing Problems
Abstract— Assembly line balancing problem consists of a finite set of tasks, where each of them has a duration time and precedence relations, which specify the acceptable ordering of the tasks. Line balancing is an attempt to locate tasks to each workstation on the assembly line. The basic ALB problem is to assign a set of tasks to an ordered set of workstations, so that the precedence relationships were satisfied, and performance factors were optimized. This paper shows the comparison of different heuristics for cost oriented assembly line balancing problem which has been taken from literature. Comparison is done on the basis of their smoothness index, cost and line efficiency. The computational results show that the proposed heuristic performs better and minimizes the production cost.
Journal of Manufacturing Systems, 2012
In this paper a different type II robotic assembly line balancing problem (RALB-II) is considered. One of the two main differences with the existing literature is objective function which is a multi-objective one. The aim is to minimize the cycle time, robot setup costs and robot costs. The second difference is on the procedure proposed to solve the problem. In addition, a new mixed-integer linear programming model is developed. Since the problem is NP-hard, three versions of multi-objective evolution strategies (MOES) are employed. Numerical results show that the proposed hybrid MOES is more efficient.