Quality Control Analysis of Painting Results in Steel Construction Projects Using Statistical Quality Control Methods and Failure Mode Effect Analysis at PT. BSB
PT BSB is a company engaged in construction specialising in steel fabrication. There are various projects carried out at the company, namely bridges, steel structures, buildings, towers, and others. The research was conducted to analyse the quality of results in the painting process at PT BSB using...
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| Main Authors: | , |
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| Format: | Article |
| Language: | Indonesian |
| Published: |
Universitas Islam Negeri Sultan Syarif Kasim
2024-05-01
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| Series: | Jurnal Teknik Industri: Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri |
| Online Access: | https://ejournal.uin-suska.ac.id/index.php/jti/article/view/29580 |
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| Summary: | PT BSB is a company engaged in construction specialising in steel fabrication. There are various projects carried out at the company, namely bridges, steel structures, buildings, towers, and others. The research was conducted to analyse the quality of results in the painting process at PT BSB using statistical quality control (SQC) and failure mode effect analysis (FMEA) methods. Data collection is done by collecting primary and secondary data used in this study. The four types of painting defects obtained from the research results are Sagging/Runs, Orange Peel, Pin Hole and Seeds/Dirt. Based on the FMEA method, the level of defects can be determined based on the cumulative percentage value produced, where the highest defect value is 1750 Sagging/Runs defects. One of the factors causing the defect is the uneven spraying of paint, causing a layer of paint that is too thick, resulting in excessive accumulation of paint in certain parts that flow vertically and unevenly. From this research, it can be concluded that the company must use the SQC method to determine the causes of defects in the painting process and analyse improvements that must be prioritised.
Keywords: Failure Mode Effect Analysis (FMEA), Painting Process Analysis, Statistical Quality Control (SQC) |
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| ISSN: | 2460-898X 2714-6235 |