2014•Jurnal TeknologiOpen access

Application of Design of Experiment and Computer Simulation to Improve the Color Industry Productivity: Case Study

Seyed Mojib Zahraee, Shahab Shariatmadari, Hadi Badri Ahmadi, Saeed Hakimi, Ataollah Shahpanah

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Abstract

One of the controversial issues in manufacturing companies is bottleneck. Managers and engineers try to deal with this difficulty to improve the productivity such as increasing resource utilization and throughput. One color factory is selected as a case study in this paper. This company tries to identify and decrease the bottlenecks in the production line. The goal of this paper is building the simulation model of production line to improve the productivity by analyzing the bottleneck. To achieve this goal, statistical method named design of experiment (DOE) was performed in order to find the optimum combination of factors that have the significant effect on the process productivity. The analysis shows that all of the main factors have a significant effect on the production line productivity. The optimum value of productivity is achieved when the number of delpak mixer (C) and number of lifter (D) to be located at high level that is equal to 2 and 2 respectively. The most significant conclusion of this study is that 3.2 labors are required to reach maximum productivity based on the resource utilization and cost. It means that 3 full time labors and one part time labor should be employed for the production line.

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What this paper is about

One of the controversial issues in manufacturing companies is bottleneck. Managers and engineers try to deal with this difficulty to improve the productivity such as increasing resource utilization and throughput. One color factory is selected as a case study in this paper. This company tries to identify and decrease the bottlenecks in the production line. The goal of this paper is building the simulation model of production line to improve the productivity by analyzing the bottleneck. To achieve this goal, statistical method named design of experiment (DOE) was performed in order to find the optimum combination of factors that have the significant effect on the process productivity. The analysis shows that all of the main factors have a significant effect on the production line productivity. The optimum value of productivity is achieved when the number of delpak mixer (C) and number of lifter (D) to be located at high level that is equal to 2 and 2 respectively. The most significant conclusion of this study is that 3.2 labors are required to reach maximum productivity based on the resource utilization and cost. It means that 3 full time labors and one part time labor should be employed for the production line.

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Available abstract

One of the controversial issues in manufacturing companies is bottleneck. Managers and engineers try to deal with this difficulty to improve the productivity such as increasing resource utilization and throughput. One color factory is selected as a case study in this paper. This company tries to identify and decrease the bottlenecks in the production line. The goal of this paper is building the simulation model of production line to improve the productivity by analyzing the bottleneck. To achieve this goal, statistical method named design of experiment (DOE) was performed in order to find the optimum combination of factors that have the significant effect on the process productivity. The analysis shows that all of the main factors have a significant effect on the production line productivity. The optimum value of productivity is achieved when the number of delpak mixer (C) and number of lifter (D) to be located at high level that is equal to 2 and 2 respectively. The most significant conclusion of this study is that 3.2 labors are required to reach maximum productivity based on the resource utilization and cost. It means that 3 full time labors and one part time labor should be employed for the production line.

Key concepts: Bottleneck, Productivity, Production line, Throughput, Production (economics), Factory (object-oriented programming), Productivity model, Industrial engineering

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