Application of Statistical Techniques in Improving the Production Operations | ||||
| MSA Engineering Journal | ||||
| Article 5, Volume 2, Issue 4, December 2023, Page 61-88 PDF (1.47 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/msaeng.2023.229753.1341 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
sameh Ahmed Amin   1; Prof Nahed Sobhi2
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| 1Industrial system engineering department, MSA University | ||||
| 2Dean of faculty of engineering | ||||
| Abstract | ||||
| The central problem in lack of quality is the failure to understand variation. Variation is the main enemy of achieving quality in the production. Statistical techniques are used to minimize the process variability for achieving high efficiency and quality of the products. This work focuses on identifying and reducing the variation in the manufacturing process of fan blade. The whole process of blade manufacturing is investigated to detect the sources of variations in the blades’ weight. Taguchi method is applied in manufacturing processes for well identifying all operating parameters which critically affecting the behavior of the process, and try to improve those operating parameters. The optimization of the parameters of the experiment is applied with Minitab 19 statistical package software. The achieved results showed that the optimization parameters of the electrostatic painting machine are at a voltage of 100 KV, speed of 35 m/s, a distance of 300 mm, and a pressure of 2.5 bar. The achieved results showed that there is a significant improvement in the standard deviation of coating thickness by 52%, and an increase in the process performance indices (Cpk) from (-0.21 to 0.52). Similarly, the process capability indices (Cp) are increased from (0.47 to 1.38). These results indicate that the process of electrostatic painting has a great reduction in variability. Also, the results showed a significant reduction in powder consumption which led to a significant decrease in the cost of blade paint by 40%, with total annual saving of 3,456,000 LE/Year. | ||||
| Keywords | ||||
| Statistical techniques, Variation Reduction; Taguchi Method | ||||
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