Improving Productivity in a Bank System by Using Computer Simulation

Hatami, Milad; Zahraee, Seyed Mojib; Ahmadi, Milad; Golroudbary, Saeed Rahimpour; Rohani, Jafri Mohd

doi:10.4028/www.scientific.net/amm.606.259

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Manufacturing systems is comprised of complex combination of resources such as material, labor, machines. It would be a difficult task to find the root of problem in timely manner and effectively when a production line is faced with a problem [7]. For solving these difficulties, engineers can use the experimental design to determine the significant factors that have a considerable effect on the efficiency of production line.…”

Section: Introductionmentioning

confidence: 99%

Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency

Assadi¹,

Zahraee²

2016

Int J Swarm Intel Evol Comput

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The goal of this paper is to optimize the productivity of manufacturing system by integrating computer simulation, design of experiments (DOE) and particle swarm optimization (PSO) algorithm. Optimizing productivity of colour factory was considered as the case of this study. To evaluate and estimate the effect of main factors, 2 n factorial design with higher and upper levels and centre points was considered. After obtaining the significant factors, the local optimum setting of the significant factors was determined using the steepest ascent method and response surface methodology (RSM) approach. Finally, the global optimum productivity was achieved by computer programing of PSO method. Base on the final result, maximum productivity occurs in the point of 87.23 that is relevant to number of labour (B) = 26 and failure time of lifter (C) = 78.04 min. In addition, other two factors A (Service rate of Delpak mixer) and D (Number of permil) should be located at low level to obtain maximum productivity.

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Section: Introductionmentioning

confidence: 99%

Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency

Assadi¹,

Zahraee²

2016

Int J Swarm Intel Evol Comput

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“…Computer simulations have been widely applied to solve operational problems and to improve the productivity and performance in different fields, such as manufacturing systems , port container terminal (Shahpanah, Poursafary, Shariatmadari, Gholamkhasi & Zahraee, 2014;Shahpanah, Hashemi, Nouredin, Zahraee & Helmi, 2014), supply chain management (Memari, Zahraee, Anjomanshoae & Rahim, 2013), different services such as bank system (Hatami, Zahraee, Ahmadi, Golroudbary & Rohani, 2014) and construction management (Zahraee, Rezaei, Shahpanah, Chegeni & Rohani, 2014), which are not easy to model. There are many advantages of using manufacturing simulation in the manufacturing systems through saving the money investment, enhancing the resource utilization, reducing the process cycle time, and incrementing of the throughput .…”

Section: Literature Reviewmentioning

confidence: 99%

The optimal parameter design for a welding unit of manufacturing industry by Taguchi method and computer simulation

Zahraee

Chegeni

Toghtamish

2016

JIEM

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Abstract:Purpose: Manufacturing systems include a complicated combination of resources, such as materials, labors, and machines. Hence, when the manufacturing systems are faced with a problem related to the availability of resources it is difficult to identify the root of the problem accurately and effectively. Managers and engineers in companies are trying to achieve a robust production line based on the maximum productivity. The main goal of this paper is to design a robust production line, taking productivity into account in the selected manufacturing industry.Design/methodology/approach: This paper presents the application of Taguchi method along with computer simulation for finding an optimum factor setting for three controllable factors, which are a number of welding machines, hydraulic machines, and cutting machines by analyzing the effect of noise factors in a selected manufacturing industry.Findings and Originality/value: Based on the final results, the optimal design parameter of welding unit of in the selected manufacturing industry will be obtained when factor A is located at level 2 and B and C are located at level 1. Therefore, maximum productive desirability is achieved when the number of welding machines, hydraulic machines, and cutting machines is equal to 17, -487-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1425 2, and 1, respectively. This paper has a significant role in designing a robust production line by considering the lowest cost and timely manner based on the Taguchi method.

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Characterization of Manufacturing System Computer Simulation using Taguchi Method

2015

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In the manufacturing industry, managers and engineers are trying to sustain their competitiveness by achieving high output and productivity. There are some common problems such as waiting times, failures, reworks in production line that impose extra cost to the companies. Therefore, companies are striving to find methods in order to determine and deal with problems using different methods such as mathematical, statistical and computer simulation. The goal of this paper is to increase the total output production and to improve productivity using computer simulation and Taguchi method. This paper introduces a color manufacturing line as a case study which is simulated using arena 13.9 software. Following that the Taguchi method is applied to assess the effect of controllable and uncontrollable factors on the total output production. According to the result of JMP 10 software to conduct Taguchi experiment, the maximum desirability of productivity will be achieved when the value of factors such service rate of delpak machine=UNIF (30, 40), number of labor=14, inspection time=120 and number of Permil=5. Taguchi Method plays an efficient and suitable role in the process improvement, proposing adjustments that will provide an improvement in the productivity.

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Improving Productivity in a Bank System by Using Computer Simulation

Cited by 3 publications

References 10 publications

Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency

Integration of Computer Simulation, Design of Experiments and Particle Swarm Optimization to Optimize the Production Line Efficiency

The optimal parameter design for a welding unit of manufacturing industry by Taguchi method and computer simulation

Characterization of Manufacturing System Computer Simulation using Taguchi Method

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