A review of assembly optimisation applications using discrete event simulation

Prajapat, Neha; Tiwari, Ashutosh

doi:10.1080/0951192x.2016.1145812

Cited by 34 publications

(22 citation statements)

References 42 publications

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“…Evidence from previous studies indicates that an integral of Arena and OptQuest are the most used SBO software tools 65 . However, in any design problem, selection of the software to be used for simulation is very important.…”

Section: Literature Reviewmentioning

confidence: 99%

A complex garment assembly line balancing using simulation‐based optimization

Bongomin

Mwasiagi

Nganyi

et al. 2020

Engineering Reports

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The nascent wave of disruptive competition in the current business environment brought about by the fourth industrial revolution (Fashion 4.0 or Apparel 4.0) is enormous. Therefore, it is important for the apparel industry to be flexible enough to respond quickly to the unstable customers' demand through continuous improvement of their process efficiency and productivity. This study proposed assembly line balancing problem (ALBP) for complex garment assembly line using simulation-based optimization under stochastic task times. The proposed ALBP solution approach aimed at minimizing the cycle time for a given number of workstations with consideration of constraints on number of resources, precedence relations, and resource types. The empirical study was conducted at Southern Range Nyanza Limited (NYTIL) garment facility and a complex trouser assembly line with 69 workstations was considered. The discrete event simulation of the trouser assembly line was developed using Arena simulation software. The local optimal solution was obtained from simulation experiments which was adopted for the optimization process. The OptQuest tool was used to solve a single objective optimization with discrete control values. The results showed that the average throughput increased by 30% for local optimal line balancing and 55% for global optimal line balancing. Consequently, the cycle time reduced by 23% and 36%, respectively.

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Section: Literature Reviewmentioning

confidence: 99%

A complex garment assembly line balancing using simulation‐based optimization

Bongomin

Mwasiagi

Nganyi

et al. 2020

Engineering Reports

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“…In the case of the development of new processes or new scenarios, the difficulty associated with the availability of information on the process should be taken into consideration, as the process observation and timing are disabled, considering that the process implementation will be applied only after the virtual analysis. In assembly operations, in which scenario analysis is the most used optimization method (Prajapat & Tiwari, 2017), the availability of reliable data for the simulation of production alternatives becomes a critical factor.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Standard Time Variability on the Reliability of the Simulation of Assembly Operations in Manufacturing Systems

Machado

Helleno²,

Oliveira³

et al. 2019

Hum Factors

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Objective: The aim of this article is to analyze the influence of the variability of the standard time in the simulation of the assembly operations of manufacturing systems. Background: Discrete event simulation (DES) has been used to provide efficient analysis during the design of a process or scenario. However, the modeling activities of new configurations face the problem of data availability and reliability when it comes to seeking standard times that are effective in representing the actual process under analysis, especially when the process cannot be monitored. Method: The methods-time measurement (MTM) is used as a source of standard times for simulation. Assembly activities were performed at a Learning Factory facility, which provided the necessary structure for simulating real production processes. Simulation performances using different variability of standard times were analyzed to define the impact of data characteristics. Results: The MTM standard time presented an error of approximately 5%. The definition of the data variability of standard times and the statistical distribution impacts were shown in the simulation results, with errors above 6% being observed, interfering with the model reliability. Conclusion: Based on the study, to increase the adherence of a simulation to represent a real process, it is recommended to use triangular distributions with central values greater than those established via the MTM for the representation of the standard times of new assembly processes or scenarios using DES. Application: The study contributions can be applied in assembly line design, providing a reliable model representing real processes and scenarios.

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“…Recently, simulation applications in manufacturing have received the attention of researchers. A popular simulation technique for modeling, analyzing, and optimizing complex systems is discrete-event system simulation (DESS) [1]- [4].…”

Section: Introductionmentioning

confidence: 99%

“…Other applications include planning and scheduling operations [12]- [16]; planning and scheduling maintenance operations in manufacturing systems [17]- [19]; planning and optimizing quality inspection strategies in manufacturing systems [20]- [22]; analyzing and controlling energy and power consumption in manufacturing operations [11], [23]- [25]; and planning and operations of remanufacturing systems [26]- [28]. For comprehensive reviews on the applications of simulation in manufacturing, the reader is referred to [2]- [4] and [29].…”

Section: Introductionmentioning

confidence: 99%

Productivity Improvement Through Multi-Objective Simulation Optimization—A Case Study

AlDurgam

Alghadeer²,

Abdel-Aal

et al. 2019

IEEE Access

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To maximize profitability and meet customers' expectations, assembly plants strive to enhance operations and minimize costs. Using discrete-event system simulation and optimization, this paper investigates different scenarios to enhance operations efficiency and presents a decision support tool to aid operational decision making in an air conditioner assembly plant. Specifically, simulation is used to evaluate the system-wide impact of an optimal sequencing rule at a bottleneck station; in addition, a multi-objective simulation optimization problem is solved to enable manufacturers to evaluate their time/cost tradeoffs. Using actual data from a previous month, the simulation study illustrates possible savings throughout the evaluated alternatives. To sustain the study outcomes, we combine mathematical programming and simulation into an integrated decision support tool. Overall, this study illustrates the benefits of the solution approach to a real-life system.

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A review of assembly optimisation applications using discrete event simulation

Cited by 34 publications

References 42 publications

A complex garment assembly line balancing using simulation‐based optimization

A complex garment assembly line balancing using simulation‐based optimization

Analysis of the Influence of Standard Time Variability on the Reliability of the Simulation of Assembly Operations in Manufacturing Systems

Productivity Improvement Through Multi-Objective Simulation Optimization—A Case Study

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