Characterization of Manufacturing System Computer Simulation using Taguchi Method

Abstract

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.

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

“…In order to conduct the simulation experiments, model of manufacturing system was created using the Arena software. After conducting the DOE experiment the two factors which are B (Number of labor) and C (Failure time of lifter) were significant [22]. After obtaining the significant factors, the local optimum setting of the significant factors was determined using the steepest ascent method and response surface methodology approach.…”

Application of Computer Simulation for Productivity Improvement of Welding Unit in a Heater Manufacturing Industry: A Case Study Based on Arena

“…Hatami et al [13] assessed the importance of different parameters on a production line using simulation and design of experiments (DOE) to improve productivity. In another study, the statistical Taguchi method and computer simulation were combined to investigate the impacts of main and uncontrollable parameters on the overall production output in the paint factory [14]. Dengiz et al [15] showed how the combination of regression meta-modeling techniques and simulation modeling can be applied to design and improve a real automotive manufacturing system.…”

Use of the Taguchi Method to Optimize an Immunodetection System for Quantitative Analysis of a Rapid Test

“…The Taguchi method is a statistical tool, which through the process parameter levels and the experimental plan, simplifies the number of experiments and improve the method used for data analyses. It can be applied to engineering [19][20][21], manufacturing [22,23], and the supply chain [24].…”