An integrated approach for line balancing and AGV scheduling towards smart assembly systems

2020 ◽  
Vol 40 (2) ◽  
pp. 219-234 ◽  
Author(s):  
Humyun Fuad Rahman ◽  
Mukund Nilakantan Janardhanan ◽  
Peter Nielsen
Keyword(s):  
Material Handling ◽  
Assembly Line ◽  
Computational Study ◽  
Automated Guided Vehicles ◽  
Robotic Assembly ◽  
Line Balancing ◽  
Assembly Systems ◽  
Scheduling Problems ◽  
Content Type ◽  
Smart Assembly

Purpose Optimizing material handling within the factory is one of the key problems of modern assembly line systems. The purpose of this paper is to focus on simultaneously balancing a robotic assembly line and the scheduling of material handling required for the operation of such a system, a topic that has received limited attention in academia. Manufacturing industries focus on full autonomy because of the rapid advancements in different elements of Industry 4.0 such as the internet of things, big data and cloud computing. In smart assembly systems, this autonomy aims at the integration of automated material handling equipment such as automated guided vehicles (AGVs) to robotic assembly line systems to ensure a reliable and flexible production system. Design/methodology/approach This paper tackles the problem of designing a balanced robotic assembly line and the scheduling of AGVs to feed materials to these lines such that the cycle time and total tardiness of the assembly system are minimized. Because of the combination of two well-known complex problems such as line balancing and material handling and a heuristic- and metaheuristic-based integrated decision approach is proposed. Findings A detailed computational study demonstrates how an integrated decision approach can serve as an efficient managerial tool in designing/redesigning assembly line systems and support automated transportation infrastructure. Originality/value This study is beneficial for production managers in understanding the main decisional steps involved in the designing/redesigning of smart assembly systems and providing guidelines in decision-making. Moreover, this study explores the material distribution scheduling problems in assembly systems, which is not yet comprehensively explored in the literature.

An improved immune clonal selection algorithm for bi-objective robotic assemble line balancing problems considering time and space constraints

2019 ◽  
Vol 36 (6) ◽  
pp. 1868-1892 ◽  
Author(s):  
Binghai Zhou ◽  
Qiong Wu
Keyword(s):  
Assembly Line ◽  
Clonal Selection ◽  
Assembly Line Balancing ◽  
Robotic Assembly ◽  
Line Balancing ◽  
Clonal Selection Algorithm ◽  
Selection Algorithm ◽  
Assembly Lines ◽  
Content Type ◽  
Multi Objective

Purpose The extensive applications of the industrial robots have made the optimization of assembly lines more complicated. The purpose of this paper is to develop a balancing method of both workstation time and station area to improve the efficiency and productivity of the robotic assembly lines. A tradeoff was made between two conflicting objective functions, minimizing the number of workstations and minimizing the area of each workstation. Design/methodology/approach This research proposes an optimal method for balancing robotic assembly lines with space consideration and reducing robot changeover and area for tools and fixtures to further minimize assembly line area and cycle time. Due to the NP-hard nature of the considered problem, an improved multi-objective immune clonal selection algorithm is proposed to solve this constrained multi-objective optimization problem, and a special coding scheme is designed for the problem. To enhance the performance of the algorithm, several strategies including elite strategy and global search are introduced. Findings A set of instances of different problem scales are optimized and the results are compared with two other high-performing multi-objective algorithms to evaluate the efficiency and superiority of the proposed algorithm. It is found that the proposed method can efficiently solve the real-world size case of time and space robotic assembly line balancing problems. Originality/value For the first time in the robotic assembly line balancing problems, an assignment-based tool area and a sequence-based changeover time are took into consideration. Furthermore, a mathematical model with bi-objective functions of minimizing the number of workstations and area of each station was developed. To solve the proposed problem, an improved multi-objective immune clonal selection algorithm was proposed and a special coding scheme is designed.

scholarly journals Mathematical models and simulated annealing algorithms for the robotic assembly line balancing problem

2018 ◽  
Vol 38 (4) ◽  
pp. 420-436 ◽  
Author(s):  
Zixiang Li ◽  
Mukund Nilakantan Janardhanan ◽  
Peter Nielsen ◽  
Qiuhua Tang
Keyword(s):  
Simulated Annealing ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Upper Bounds ◽  
Robotic Assembly ◽  
Line Balancing ◽  
Content Type ◽  
Rsa Algorithm ◽  
Robotic Assembly Line Balancing ◽  
Annealing Algorithms

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 of the proposed methods. The results obtained by these algorithms on the benchmark instances show that 23 new upper bounds out of 32 tested cases are achieved. The RSA algorithm ranks first among the algorithms in the number of updated upper bounds. Originality/value Four models are developed for RALBP-II and their performance is evaluated for the first time. An RSA algorithm is developed to solve RALBP-II, where the restart mechanism is developed to replace the incumbent temperature with a new temperature. The proposed methods also use iterative mechanisms and a new objective to select the solution with fewer critical workstations.

An optimization methodology for multi model walking-worker assembly systems: an application from busbar energy distribution systems

2016 ◽  
Vol 36 (4) ◽  
pp. 439-459 ◽  
Author(s):  
Emre Cevikcan
Keyword(s):  
Mathematical Programming ◽  
Assembly Line ◽  
Heuristic Algorithms ◽  
Assembly Line Balancing ◽  
Working Environment ◽  
Programming Models ◽  
Line Balancing ◽  
Assembly Systems ◽  
Content Type ◽  
Optimization Methodology

Purpose Walking-worker assembly lines can be regarded as an effective method to achieve the above-mentioned characteristics. In such systems, workers, following each other, travel workstations in sequence by performing all of the required tasks of their own product. As the eventual stage of assembly line design, efforts should be made for capacity adjustments to meet the demand in terms of allocating tasks to workers via assembly line balancing. In this context, the purpose of this study is to address the balancing problem for multi-model walking-worker assembly systems, with the aim of improving planning capability for such systems by means of developing an optimization methodology. Design/methodology/approach Two linear integer programming models are proposed to balance a multi-model walking-worker assembly line optimally in a sequential manner. The first mathematical programming model attempts to determine number of workers in each segment (i.e. rabbit chase loop) for each model. The second model generates stations in each segment to smooth workflow. What is more, heuristic algorithms are provided due to computational burden of mathematical programming models. Two segment generation heuristic algorithms and a station generation heuristic algorithm are provided for the addressed problem. Findings The application of the mathematical programming approach improved the performance of a tap-off box assembly line in terms of number of workers (9.1 per cent) and non-value-added time ratio (between 27.9 and 26.1 per cent for different models) when compared to a classical assembly system design. In addition, the proposed approach (i.e. segmented walking-worker assembly line) provided a more convenient working environment (28.1 and 40.8 per cent shorter walking distance for different models) in contrast with the overall walking-worker assembly line. Meanwhile, segment generation heuristics yielded reduction in labour requirement for a considerable number (43.7 and 49.1 per cent) of test problems. Finally, gaps between the objective values and the lower bounds have been observed as 8.3 per cent (Segment Generation Heuristic 1) and 6.1 (Segment Generation Heuristic 2). Practical implications The proposed study presents a decision support for walking-worker line balancing with high level of solution quality and computational performance for even large-sized assembly systems. That being the case, it contributes to the management of real-life assembly systems in terms of labour planning and ergonomics. Owing to the fact that the methodology has the potential of reducing labour requirement, it will present the opportunity of utilizing freed-up capacity for new lines in the start-up period or other bottleneck processes. In addition, this study offers a working environment where skill of the workers can be improved within reasonable walking distances. Originality/value To the best knowledge of the author, workload balancing on multi-model walking-worker assembly lines with rabbit chase loop(s) has not yet been handled. Addressing this research gap, this paper presents a methodology including mathematical programming models and heuristic algorithms to solve the multi-model walking-worker assembly line balancing problem for the first time.

A multi-manned assembly line balancing problem with classified teams: a new approach

2016 ◽  
Vol 36 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Hamid Yilmaz ◽  
Mustafa Yilmaz
Keyword(s):  
Design Methodology ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Test Problems ◽  
New Approach ◽  
Content Type ◽  
Line Test ◽  
Assembly Line Balancing Problem ◽  
First Time

Purpose – Within team-oriented approaches, tasks are assigned to teams before being assigned to workstations as a reality of industry. So it becomes clear, which workers assemble which tasks. Design/methodology/approach – Team numbers of the assembly line can increase with the number of tasks, but at the same time, due to physical situations of the stations, there will be limitations of maximum working team numbers in a station. For this purpose, heuristic assembly line balancing (ALB) procedure is used and mathematical model is developed for the problem. Findings – Well-known assembly line test problems widely used in the literature are solved to indicate the effectiveness and applicability of the proposed approach in practice. Originality/value – This paper draws attention to ALB problem in which workers have been assigned to teams in advance due to the need for specialized skills or equipment on the line for the first time.

Recent trend in mixed-model assembly line balancing optimization using soft computing approaches

2019 ◽  
Vol 36 (2) ◽  
pp. 622-645 ◽  
Author(s):  
Muhamad Magffierah Razali ◽  
Nur Hairunnisa Kamarudin ◽  
Mohd Fadzil Faisae Ab. Rashid ◽  
Ahmad Nasser Mohd Rose
Keyword(s):  
Assembly Line ◽  
Mixed Model ◽  
Assembly Line Balancing ◽  
Line Balancing ◽  
Research Trend ◽  
Content Type ◽  
Publication Number ◽  
The Future ◽  
Mixed Model Assembly Line ◽  
Mixed Model Assembly

Purpose This paper aims to review and discuss four aspects of mixed-model assembly line balancing (MMALB) problem mainly on the optimization angle. MMALB is a non-deterministic polynomial-time hard problem which requires an effective algorithm for solution. This problem has attracted a number of research fields: manufacturing, mathematics and computer science. Design/methodology/approach This paper review 59 published research works on MMALB from indexed journal. The review includes MMALB problem varieties, optimization algorithm, objective function and constraints in the problem. Findings Based on research trend, this topic is still growing with the highest publication number observed in 2016 and 2017. The review indicated that the future research direction should focus on human factors and sustainable issues in the problem modeling. As the assembly cost becomes crucial, resource utilization in the assembly line should also be considered. Apart from that, the growth of new optimization algorithms is predicted to influence the MMALB optimization, which currently relies on well-established algorithms. Originality/value The originality of this paper is on the research trend in MMALB. It provides the future direction for the researchers in this field.

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