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1 – 10 of over 71000Mohammad Kamal Uddin, Marian Cavia Soto and Jose L. Martinez Lastra
Design, 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…
Abstract
Purpose
Design, 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/approach
Different 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.
Findings
ALs 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/value
This 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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Muhamad Magffierah Razali, Nur Hairunnisa Kamarudin, Mohd Fadzil Faisae Ab. Rashid and Ahmad Nasser Mohd Rose
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…
Abstract
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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Abdolreza Roshani and Farnaz Ghazi Nezami
This paper aims to study a generalized type of mixed-model assembly line with multi-manned workstations where multiple workers simultaneously perform different tasks on the same…
Abstract
Purpose
This paper aims to study a generalized type of mixed-model assembly line with multi-manned workstations where multiple workers simultaneously perform different tasks on the same product. This special kind of assembly line is usually utilized to assemble different models of large products, such as buses and trucks, on the same production line.
Design/methodology/approach
To solve the mixed-model multi-manned assembly line balancing problem optimally, a new mixed-integer-programming (MIP) model is presented. The proposed MIP model is nondeterministic polynomial-time (NP)-hard, and as a result, a simulated annealing (SA) algorithm is developed to find the optimal or near-optimal solution in a small amount of computation time.
Findings
The performance of the proposed algorithm is examined for several test problems in terms of solution quality and running time. The experimental results show that the proposed algorithm has a satisfactory performance from computational time efficiency and solution accuracy.
Originality/value
This research is the very first study that minimizes the number of workers and workstations simultaneously, with a higher priority set for the number of workers, in a mixed-model multi-manned assembly line setting using a novel MIP model and an SA algorithm.
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Dongwook Kim, Dug Hee Moon and Ilkyeong Moon
The purpose of this paper is to present the process of balancing a mixed-model assembly line by incorporating unskilled temporary workers who enhance productivity. The authors…
Abstract
Purpose
The purpose of this paper is to present the process of balancing a mixed-model assembly line by incorporating unskilled temporary workers who enhance productivity. The authors develop three models to minimize the sum of the workstation costs and the labor costs of skilled and unskilled temporary workers, cycle time and potential work overloads.
Design/methodology/approach
This paper deals with the problem of designing an integrated mixed-model assembly line with the assignment of skilled and unskilled temporary workers. Three mathematical models are developed using integer linear programming and mixed integer linear programming. In addition, a hybrid genetic algorithm that minimizes total operation costs is developed.
Findings
Computational experiments demonstrate the superiority of the hybrid genetic algorithm over the mathematical model and reveal managerial insights. The experiments show the trade-off between the labor costs of unskilled temporary workers and the operation costs of workstations.
Originality/value
The developed models are based on practical features of a real-world problem, including simultaneous assignments of workers and precedence restrictions for tasks. Special genetic operators and heuristic algorithms are used to ensure the feasibility of solutions and make the hybrid genetic algorithm efficient. Through a case study, the authors demonstrated the validity of employing unskilled temporary workers in an assembly line.
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Hui Zhang, Xiyang Li, Za Kan, Xiaohai Zhang and Zhiyong Li
Reducing production auxiliary time is the key to improve the efficiency of the existing mixed-flow assembly line. This paper proposes a method combining improved genetic algorithm…
Abstract
Purpose
Reducing production auxiliary time is the key to improve the efficiency of the existing mixed-flow assembly line. This paper proposes a method combining improved genetic algorithm (GA) and Flexsim software. It also investigates mixed-flow assembly line scheduling and just-in-time (JIT) parts feeding scheme to reduce waste in production while taking the existing hill-drop mixed-flow assembly line as an example to verify the effectiveness of the method.
Design/methodology/approach
In this research, a method is presented to optimize the efficiency of the present assembly line. The multi-objective mathematical model is established based on the objective function of the minimum production cycle and part consumption balance, and the solution model is developed using multi-objective GA to obtain the mixed flow scheduling scheme of the hill-drop planter. Furthermore, modeling and simulation with Flexsim software are investigated along with the contents of line inventory, parts transportation means, daily feeding times and time points.
Findings
Theoretical analysis and simulation experiments are carried out in this paper while taking an example of a hill-drop planter mixed-flow assembly line. The results indicate that the method can effectively reduce the idle and overload of the assembly line, use the transportation resources rationally and decrease the accumulation of the line inventory.
Originality/value
The method of combining improved GA and Flexsim software was used here for the first time intuitively and efficiently to study the balance of existing production lines and JIT feeding of parts. Investigating the production scheduling scheme provides a reference for the enterprise production line accompanied by the quantity allocation of transportation tools, the inventory consumption of the spare parts along the line and the utilization rate of each station to reduce the auxiliary time and apply practically.
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The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.
Abstract
Purpose
The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.
Design/methodology/approach
Scenario planning approach is used to represent the input data uncertainty in the decision model. Two kinds of robust criteria are provided: one is min‐max related; and the other is α‐worst scenario based. Corresponding optimization models are formulated, respectively. A genetic algorithm‐based robust optimization framework is designed. Comprehensive computational experiments are done to study the effect of these robust approaches.
Findings
With min‐max related robust criteria, the solutions can provide an optimal worst‐case hedge against uncertainties without a significant sacrifice in the long‐run performance; α‐worst scenario‐based criteria can generate flexible robust solutions: through rationally tuning the value of α, the decision maker can obtain a balance between robustness and conservatism of an assembly line task elements assignment.
Research limitations/implications
This paper is an attempt to robust mixed model assembly line balancing. Some more efficient and effective robust approaches – including robust criteria and optimization algorithms – may be designed in the future.
Practical implications
In an assembly line with significant uncertainty, the robust approaches proposed in this paper can hedge against the risk of poor system performance in bad scenarios.
Originality/value
Using robust optimization approaches to balance mixed model assembly line.
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T.K. Bhattacharjee and S. Sahu
This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored…
Abstract
This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.
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Adalberto Sato Michels and Alysson M. Costa
Resource-constrained assembly lines are widely found in industries that manufacture complex products. In such lines, tasks may require specific resources to be processed…
Abstract
Purpose
Resource-constrained assembly lines are widely found in industries that manufacture complex products. In such lines, tasks may require specific resources to be processed. Therefore, decisions on which tasks and resources will be assigned to each station must be made. When the number of available stations is fixed, the problem’s main goal becomes the minimisation of cycle time (type-II version). This paper aims to explore this variant of the problem that lacks investigation in the literature.
Design/methodology/approach
In this paper, the authors propose mixed-integer linear programming (MILP) models to minimise cycle time in resource-constrained assembly lines, given a limited number of stations and resources. Dedicated and alternative resource types for tasks are considered in different scenarios.
Findings
Besides, past modelling decisions and assumptions are questioned. The authors discuss how they were leading to suboptimal solutions and offer a rectification.
Practical implications
The proposed models and data set fulfil more practical concerns by taking into account characteristics found in real-world assembly lines.
Originality/value
The proposed MILP models are applied to an existing data set, results are compared against a constraint programming model, and new optimal solutions are obtained. Moreover, a data set extension is proposed due to the simplicity of the current one and instances up to 70 tasks are optimally solved.
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Veronique Limère, Hendrik Van Landeghem and Marc Goetschalckx
The purpose of this paper is to propose a decision model to choose between kitting and line stocking at the level of single parts, while taking into account the variable operator…
Abstract
Purpose
The purpose of this paper is to propose a decision model to choose between kitting and line stocking at the level of single parts, while taking into account the variable operator walking distances. Different ways of feeding assembly lines, such as kitting and line stocking not only have an impact on in-plant logistics flows but also determine the amount of stock that is available at the line. This, in turn, has an impact on operator walking distances during assembly.
Design/methodology/approach
A mixed integer linear programming model is developed for the assignment of parts to one of both methods, and to be able to extensively test the model, an algorithm is created for the construction of representative datasets.
Findings
Parts are often kitted because of a space constraint at the line, but even without a space constraint, the shorter walking distances might give preference to kitting. An analysis is presented that demonstrates how specific part characteristics influence the chances of a part being kitted.
Research limitations/implications
Our research model can be extended to include, e.g., the study of alternative in-plant logistic designs and the outsourcing of kitting to a third-party logistics provider (3PL) or to the suppliers.
Practical implications
The objective assignment model and the insights obtained from it are valuable for logistics and production engineers that otherwise have to rely solely on intuition. In situations with thousands of components, intuition mostly falls far short.
Originality/value
First, existing models do not consider variable walking distances, which are shown to have a crucial impact on the decision. Second, the data instances created allow for a systematic comparison of future research in the field.
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Zixiang Li, Mukund Nilakantan Janardhanan, Peter Nielsen and Qiuhua Tang
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…
Abstract
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.
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