Simulation, through discrete events, of industrial processes in productive environments

Garriz, Carlos; Domingo, Rafael

doi:10.1016/j.promfg.2017.09.137

Cited by 6 publications

(6 citation statements)

References 9 publications

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“…Process changes are then suggested for improved efficiency and throughput while reducing WIP. Gárriz & Domingo, (2017) simulate a production cell in a car factory. Alternatives are suggested to improve productivity of the cell and validated with the real system.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving Performance in an Aluminum Extrusion Plant Using Discrete Event Simulation: A Case Study

Al-Hawari

Naimi

Zurikat

et al. 2019

mijst

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Simulation has been used in many industrial applications for performance improvement. It excels over other system analysis methods in its high flexibility and ability to model system details with high accuracy. In this study, Discrete Event Simulation (DES) is used to improve the performance of an aluminum extrusion plant. A case study is presented in a local factory in which problems are identified, and their effects on efficiency are monitored. The main problem noticed was high production rates with respect to demand rates which resulted in large amounts of work-in-process (WIP) inventory. It was found that the current base system is unstable and suggestions were made to lower production rates in order to stabilize it. Average WIP was reduced by 324% once the system was stabilized with only 1.77% difference in weekly throughput which improved the system

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Section: Literature Reviewmentioning

confidence: 99%

Improving Performance in an Aluminum Extrusion Plant Using Discrete Event Simulation: A Case Study

Al-Hawari

Naimi

Zurikat

et al. 2019

mijst

View full text Add to dashboard Cite

show abstract

“…This automatization through robots could increase even more in Industry 4.0 environments, where robots, including collaborative robots, emerge and could be more dominant in the production process [ 1 ]; in these contexts, robotic integration can lead to higher levels of performance, reliability, sustainability, accuracy and protection from hazardous environments, as well as enable more rational decision making [ 2 ]. All of this is common in the automotive sector, where simulation allows verifying multiobjective situations and consequently decreases risks in decision-making [ 3 ]. The place where the future vehicle body takes its final shape, called the body shop, is the most automated area.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry

Garriz

Domingo

2022

Sensors

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Currently, the high demand for new products in the automotive sector requires large investments in factories. The automotive industry is characterized by high automatization, largely achieved by manipulator robots capable of multitasking. This work presents a method for the optimization of trajectories in robots with six degrees of freedom and a spherical wrist. The optimization of trajectories is based on the maximization of manipulability and the minimization of electrical energy. For this purpose, it is necessary to take into account the kinematics and dynamics of the manipulator in order to integrate an algorithm for calculation. The algorithm is based on the Kalman method. This algorithm was implemented in a simulation of the trajectories of a serial industrial robot, in which the robot has a sealer gun located on its sixth axis and the quality of the sealer application depends directly on the orientation of the gun. During the optimization of the trajectory, the application of the sealer must be guaranteed. This method was also applied to three different trajectories in the automotive sector. The obtained results for manipulability and electrical energy consumption prove the efficiency of the algorithm. Therefore, this method searches for the optimal solution within the limits of the manipulator and maintains the orientation of the final effector. This can be used for a known trajectory.

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“…This means that the system is modelled as a series of events, that is, instants in time when a state change occurs [9,10]. Discrete event simulation has been used extensively in garment manufacturing and other manual or semi-automatic production systems such as footwear, electronics and automotive assembly lines [11]. For instance, Guner & Unal [12] investigated the application of computer simulation for the design of a manufacturing process for T-shirt production in a virtual-reality environment.…”

Section: Introductionmentioning

confidence: 99%

Simulation metamodeling approach to complex design of garment assembly lines

et al. 2020

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The today's competitive advantage of ready-made garment industry depends on the ability to improve the efficiency and effectiveness of resource utilization. Ready-made garment industry has long historically adopted fewer technological and process advancement as compared to automotive, electronics and semiconductor industries. Simulation modeling of garment assembly line has attracted a number of researchers as one way for insightful analysis of the system behaviour and improving its performance. However, most of simulation studies have considered ill-defined experimental design which cannot fully explore the assembly line design alternatives and does not uncover the interaction effects of the input variables. Simulation metamodeling is an approach to assembly line design which has recently been of interest to researchers. However, its application in garment assembly line design has never been well explored. In this paper, simulation metamodeling of trouser assembly line with 72 operations was demonstrated. The linear regression metamodel technique with resolution-V design was used. The effects of five factors: bundle size, job release policy, task assignment pattern, machine number and helper number on throughput of the trouser assembly line were studied. An increase of the production throughput by 28.63% was achieved for the best factors' setting of the metamodel.

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Simulation, through discrete events, of industrial processes in productive environments

Cited by 6 publications

References 9 publications

Improving Performance in an Aluminum Extrusion Plant Using Discrete Event Simulation: A Case Study

Improving Performance in an Aluminum Extrusion Plant Using Discrete Event Simulation: A Case Study

Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry

Simulation metamodeling approach to complex design of garment assembly lines

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