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329293

Application of Statistical Techniques in Improving the Production Operations

Article

Last updated: 28 Dec 2024

Subjects

-

Tags

Industrial 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.

DOI

10.21608/msaeng.2023.229753.1341

Keywords

Statistical techniques, Variation Reduction, Taguchi Method

Authors

First Name

sameh

Last Name

Amin

MiddleName

Ahmed

Affiliation

Industrial system engineering department, MSA University

Email

ssalaheldein@msa.edu.eg

City

Cairo

Orcid

0000-0002-4061-4520

First Name

Prof Nahed

Last Name

Sobhi

MiddleName

-

Affiliation

Dean of faculty of engineering

Email

nsobhi@msa.edu.eg

City

Cairo

Orcid

-

Volume

2

Article Issue

4

Related Issue

44144

Issue Date

2023-12-01

Receive Date

2023-08-16

Publish Date

2023-12-01

Page Start

61

Page End

88

Print ISSN

2812-5339

Online ISSN

2812-4928

Link

https://msaeng.journals.ekb.eg/article_329293.html

Detail API

https://msaeng.journals.ekb.eg/service?article_code=329293

Order

5

Type

Original Article

Type Code

2,183

Publication Type

Journal

Publication Title

MSA Engineering Journal

Publication Link

https://msaeng.journals.ekb.eg/

MainTitle

Application of Statistical Techniques in Improving the Production Operations

Details

Type

Article

Created At

28 Dec 2024