Optimization of two sided assembly line balancing with resource constraint

Two-sided assembly line balancing (2S-ALB) problems are practically useful in improving the production of large-sized high-volume products. Many research has proposed various approaches to study and balance this well-known ALB problem. Although much attention has been given to solve and optimize 2S-ALB, the majority of the research assumed the workstation has similar capabilities. This research has been conducted in an automotive assembly line, where most of the equipment used in assembly is different from one workstation to another. The assumption that all workstation has similar capabilities lead to inefficient resource utilization in assembly line design. This research aims to model and optimize 2S-ALB with resource constraints. Besides optimizing the line balancing, the proposed model also will minimize the number of resources in the two-sided assembly line. The research begins with problem formulation by establishing four optimization objectives. The considered optimization objectives were to minimize the number of workstations, number of mated-workstation, total idle time, and number of resources. For optimization purpose, Particle Swarm Optimization is modified to find the best solution besides reducing the dependencies on a single best solution. This is conducted by replacing the best solution with the top three solutions in the reproduction process. A set of benchmark problems for 2S-ALB were used to test the proposed Modified Particle Swarm Optimization (MPSO) in the computational experiment. Later, the proposed 2S-ALB with resource constraint model and algorithm was validated using a case study problem. The computational experiment result using benchmark test problems indicated that the proposed MPSO was able to search for better solution in 91.6% of the benchmark problems. The good performance of MPSO is attributed to its ability to maintain particle diversity over the iteration. Meanwhile, the case study result indicated that the proposed 2S-ALB with resource constraint model and MPSO algorithm are able to be utilized for the real problem. In the future, the multiobjective optimization problem will be considered to be optimized for other types of general assembly lines

Optimization of Automotive Manufacturing Layout for Productivity Improvement / Muhamad Magffierah Razali ...[et al.]

This paper deal with an optimization of automotive manufacturing layout by using meta-heuristics approach aided with discrete event simulation (WITNESS Simulation). The objective of this study is to balance the workload, increase line efficiency, and improve productivity by optimizing assembly line balancing (ALB) using Genetic Algorithm. The current assembly line layout operated under the circumstance where idle time is high due to unbalance workload. After the optimization process takes place, the workload distribution in each workstation has shown a significant improvement. Furthermore, productivity improvement was gained after the optimization followed by increment in term of line efficiency by 18%. In addition, the number of workstation needed to assemble the product can be reduced from current layout (17 workstations) to an improved layout (14 workstations). The current study contributes to the implementation of Genetic Algorithm in ALB to improve productivity of related automotive manufacturing industry

Optimisation of two-sided assembly line balancing with resource constraints using modified particle swarm optimisation

Two-sided Assembly Line Balancing (2S-ALB) is important in assembly plants that produce large-sized high-volume products, such as in automotive production. The 2S-ALB problem involves different assembly resources such as worker skills, tools, and machines required for the assembly. This research modelled and optimised the 2S-ALB with resource constraints. In the end, besides having good workload balance, the number of resources can also be optimised. For optimisation purpose, Particle Swarm Optimisation was modified to reduce the dependencies on a single best solution. This was conducted by replacing the best solution with top three solutions in the reproduction process. Computational experiment result using 12 benchmark test problems indicated that the 2S-ALB with resource constraints model was able to reduce the number of resources in an assembly line. Furthermore, the proposed modified Particle Swarm Optimisation (MPSO) was capable of searching for minimum solutions in 11 out of 12 test problems. The good performance of MPSO was attributed to its ability to maintain the particle diversity over the iteration. The proposed 2S-ALB model and MPSO algorithm were later validated using industrial case study. This research has a twofold contribution; novel 2S-ALB with resource constraints model and also modified PSO algorithm with enhanced performance

A Review of Two-sided Assembly Line Balancing Problem

Assembly line balancing (ALB) is concerned with assigning tasks within an assembly line to meet the required production rate for optimization purposes. On the other hand, two-sided ALB performs double-sided assembly operation on a single assembly line. In this paper, we have focused the survey on two-sided assembly line balancing (2S-ALB) research problems. The numerous factors mentioned in 2SALB literature were actually based on problem resolutions, and this paper will quote any preferred literature considering the frequent citation. In particular, this review explores in detail the ALB problems, optimization methods, objective functions, and specific constraints used in solving 2S-ALB problems. Among the purposes of ALB problems is that it traditionally focuses on simple ALB with various engaging approaches. General ALB comes second because of its complexity and nondeterministic polynomial (NP)-hard-classified problems. However, due to the current manufacturing issues, GALB problems, such as 2S-ALB, are forced to be examined and this comprehensive literature will specify anything necessary for the optimization purposes. Finally, future research direction has been discovered and put forward as the suggestion

Mathematical Modelling of Mixed-Model Assembly Line Balancing Problem with Resources Constraints

Modern manufacturing industries nowadays encounter with the challenges to provide a product variety in their production at a cheaper cost. This situation requires for a system that flexible with cost competent such as Mixed-Model Assembly Line. This paper developed a mathematical model for Mixed-Model Assembly Line Balancing Problem (MMALBP). In addition to the existing works that consider minimize cycle time, workstation and product rate variation, this paper also consider the resources constraint in the problem modelling. Based on the finding, the modelling results achieved by using computational method were in line with the manual calculation for the evaluated objective functions. Hence, it provided an evidence to verify the developed mathematical model for MMALBP. Implications of the results and future research directions were also presented in this paper

Modelling of Two-sided Assembly Line Balancing Problem with Resource Constraints

Two-sided assembly line balancing (2S-ALB) problems is practically useful in improving the production of large-sized high-volume products. Many published papers have proposed various approaches to balance this well-known ALB problem. However, little attention is given in formulating the 2S-ALB problems. In this paper, 2S-ALB is modelled with four different objective functions comprising minimization of workstations, mated- workstation, idle time and resource constraints. In different with existing model, this paper also considers resource constraint with a mathematical modelling formulation in solving the 2S- ALB problems. The modelling procedures are present for each objective functions with a simple 2S-ALB example problem. Then, the anticipated performance solution is obtained from the test problem

Optimization of Automotive Manufacturing Layout for Productivity Improvement

This paper deal with an optimization of automotive manufacturing layout by using meta-heuristics approach aided with discrete event simulation (WITNESS Simulation). The objective of this study is to balance the workload, increase line efficiency, and improve productivity by optimizing assembly line balancing (ALB) using Genetic Algorithm. The current assembly line layout operated under the circumstance where idle time is high due to unbalance workload. After the optimization process takes place, the workload distribution in each workstation has shown a significant improvement. Furthermore, productivity improvement was gained after the optimization followed by increment in term of line efficiency by 18%. In addition, the number of workstation needed to assemble the product can be reduced from current layout (17 workstations) to an improved layout (14 workstations). The current study contributes to the implementation of Genetic Algorithm in ALB to improve productivity of related automotive manufacturing industry

Assembly Line Balancing using Heuristic Approaches in Manufacturing Industry / Muhammad Razif Abdullah Make...[et al.]

Assembly Line Balancing (ALB) plays a vital function especially in the production line. The installation of an assembly line is a long-term decision and requires large capital of investments. It is important that such a system is designed and balanced so that it able to work efficiently as possible. Many previous researches have proposed different heuristic approach in optimizing the assembly line. However little attention is given toward simulation analysis as proved of the proposed method. In this paper, a real industrial data of simple ALB problem is optimized and simulated for minimizing the number of workstation. Three proposed heuristics in order to improve the efficiency of the production are reviewed before a discrete simulation approach is used to compare the optimized performance. The anticipated performance of computational result is obtained from the problem comprising the workstation and labour performance output

Assembly Line Balancing using Heuristic Approaches in Manufacturing Industry

Assembly Line Balancing (ALB) plays a vital function especially in the production line. The installation of an assembly line is a long-term decision and requires large capital of investments. It is important that such a system is designed and balanced so that it able to work efficiently as possible. Many previous researches have proposed different heuristic approach in optimizing the assembly line. However little attention is given toward simulation analysis as proved of the proposed method. In this paper, a real industrial data of simple ALB problem is optimized and simulated for minimizing the number of workstation. Three proposed heuristics in order to improve the efficiency of the production are reviewed before a discrete simulation approach is used to compare the optimized performance. The anticipated performance of computational result is obtained from the problem comprising the workstation and labour performance output