Iterated Local Search for dynamic assembly line rebalancing problem

Antoine, Manceaux; Hind, Bril El-Haouzi; Chérif-Khettaf, Wahiba Ramdane; Bentaha, Mohand Lounes

doi:10.1016/j.ifacol.2016.07.679

Cited by 12 publications

(18 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The study found that the modified-DE was able to solve the assembly line with a limit of the machine types, as well as minimize workstations. The work carried out by Antoine et al (2016) [23] presented an iterative local search (ILS) for a dynamic assembly line rebalancing problem. The study found that the method could solve the problem well.…”

Section: Introductionmentioning

confidence: 99%

Simple Assembly Line Balancing Problem Type 2 By Variable Neighborhood Strategy Adaptive Search: A Case Study Garment Industry

Jirasirilerd

Pitakaso

Sethanan

et al. 2020

Journal of Open Innovation: Technology, Market, and Complexity

View full text Add to dashboard Cite

This article aims to minimize cycle time for a simple assembly line balancing problem type 2 by presenting a variable neighborhood strategy adaptive search method (VaNSAS) in a case study of the garment industry considering the number and types of machines used in each workstation in a simple assembly line balancing problem type 2 (SALBP-2M). The variable neighborhood strategy adaptive search method (VaNSAS) is a new method that includes five main steps, which are (1) generate a set of tracks, (2) make all tracks operate in a specified black box, (3)operate the black box, (4) update the track, and (5) repeat the second to fourth steps until the termination condition is met. The proposed methods have been tested with two groups of test instances, which are datasets of (1) SALBP-2 and (2) SALBP-2M. The computational results show that the proposed methods outperform the best existing solution found by the LINGO modeling program. Therefore, the VaNSAS method provides a better solution and features a much lower computational time.objective of this research is to develop an appropriate method for solving a simple assembly line balancing problem type 2, presenting a case study of the garment industry.Chesbrough [1] said that large organizations work together to drive innovation and create sustainable growth by using the concept of open innovation, which is considered to be related to industry that has adopted "technology, tools, or methods" for the industry in production systems, as well as making products according to the various needs of consumers. However, the industry still has to maintain production efficiency in order to meet the required quality. In addition, new technology, tools, and methods must be also studied and selected to be suitable for the production system and the current knowledge. Many industries still rely on human labor for production, especially the garment industry. When a problem occurs, it will be solved immediately without applying technology or any new methods to resolve it, which causes production efficiency to be at a low level. Therefore, to increase the capacity of the production system, in order to compete with other industries, it is necessary to use the concept of open innovation to help in production planning, reduce the time required for industry operations, and increase production efficiency.The assembly line balancing problem is a form of production planning used for task assignments [2] or to assign work to each station to let each work station operate with the same average production time and allow the process flow system to be flexible and eliminate delay or bottlenecks in order to be able to produce products correctly and eliminate mistakes during production. The precedence diagram or table of relationships determines the operation according to the workflow that is clearly specified in the production process. There are different objectives for problem solving, such as reducing production time, reducing the number of workstations, determining the efficiency of assembly line bal...

show abstract

Section: Introductionmentioning

confidence: 99%

Simple Assembly Line Balancing Problem Type 2 By Variable Neighborhood Strategy Adaptive Search: A Case Study Garment Industry

Jirasirilerd

Pitakaso

Sethanan

et al. 2020

Journal of Open Innovation: Technology, Market, and Complexity

View full text Add to dashboard Cite

show abstract

“…Objective functions New constraints proposed [1], "An expert system to minimize operational costs in mixed-model sequencing problems with activity factor" Minimize total production loss due to work overload and idle time Idle time: the difference between available processing time and applied processing time [2], "Iterated local search for dynamic assembly line rebalancing problem"…”

Section: Literaturementioning

confidence: 99%

“…When operations of an assembly line deviate from the prescribed parameters determined in line balancing, the assembly line must be rebalanced to minimize the impact caused by worker fatigue and lack of motivation, extra machine setup time, material shortage, machine breakdowns, or other disturbances. Rebalancing of assembly lines occurs in almost every production facility that owns a flow-based production [2,36]. Foremen of assembly lines are responsible for rebalancing [33].…”

Section: Introductionmentioning

confidence: 99%

“…Many studies about line balancing focus on planning for manufacturing systems. Relatively few studies were conducted to investigate line balancing for service systems [25] and reconfiguration or rebalancing of assembly lines after disturbances occur [2,16,22,38]. The requirement for line rebalancing changes in response to different disturbances.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Pace making and worker reassignment for assembly line rebalancing

Budak

Chen

2020

SN Appl. Sci.

View full text Add to dashboard Cite

The objective of this article is to develop a mathematical model that helps foremen rebalance assembly lines in real time. Assembly lines with a large number of workstations go through extensive line balancing to determine production rates. Once production begins, one or more workstations may not operate at predetermined production rates due to disturbances, and the assembly line requires rebalancing. Previous research largely focused on task reassignment for rebalancing. Effective and efficient tools for real-time line rebalancing are needed. This research focuses on rebalancing of unpaced and asynchronous assembly lines through pace making and worker reassignment. A mixed integer programming model is developed and its optimal solution determines which workstations pace up (increase production rates) and the amount of increase, which workstations pace down (decrease production rates) and the amount of decrease, and whether workers from certain workstations are reassigned to work at other workstations to decrease the production rates of the former and increase the production rates of the latter. Foremen may use these recommendations to rebalance assembly lines by adjusting production rates and reassigning workers. Numerical results show that the solution time of the model is less than one second, which enables real-time line rebalancing for large assembly lines.

show abstract

“…In these two studies, a task failure can be seen as a disruption and the authors proposed remedial actions to deal with such short-term disturbances. A first study to deal dynamically with real time production line disturbances is proposed in Antoine et al (2016). A binary bi-objective non-linear programme was developed in Aydemir-Karadag and Turkbey (2013) for disassembly line design and balancing under uncertainty of the task times.…”

Section: Previous Workmentioning

confidence: 99%

Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty

Bentaha

Dolgui

Battaïa

et al. 2018

International Journal of Production Research

View full text Add to dashboard Cite

This paper addresses the problem of profit-oriented disassembly line design and balancing considering partial disassembly, presence of hazardous parts and uncertainty of task processing times. Few papers have studied the stochastic disassembly line balancing problem and existing approaches have focused on heuristic and metaheuristic methods. Most existing work has concentrated on complete disassembly where task times are assumed to be normal random variables and where AND/OR graphs are not considered. The objective of this paper is the design of a serial line that obtains the maximum revenue and then balances the workload under uncertainty. The processing time of a disassembly task is assumed to be a random variable with any known probability distribution. An AND/OR graph is used to model the precedence relationships among tasks. Stochastic programming models and exact-based solution approaches combining the L-shaped algorithm and Monte Carlo sampling techniques are proposed. The relevance and applicability of the proposed models and solution methods are shown by solving efficiently a set of disassembly problem instances from the literature.

show abstract

Iterated Local Search for dynamic assembly line rebalancing problem

Cited by 12 publications

References 15 publications

Simple Assembly Line Balancing Problem Type 2 By Variable Neighborhood Strategy Adaptive Search: A Case Study Garment Industry

Simple Assembly Line Balancing Problem Type 2 By Variable Neighborhood Strategy Adaptive Search: A Case Study Garment Industry

Pace making and worker reassignment for assembly line rebalancing

Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty

Contact Info

Product

Resources

About