Capability Process to Optimize Specification by Impact of Wavelet Analysis

This study investigates the impact of wavelet analysis on optimizing specification in the capability process. A new approach called the New Hybrid Capability Wavelet Approach (NHCWA) is proposed, which utilizes wavelet analysis to filter noise and outliers in the data. The study compares the NHCWA w...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Mağallaẗ ğāmiʻaẗ Ğīhān- Arbīl li-l-ʻulūm al-insāniyyaẗ wa-al-iğtimāʻiyyaẗ Ročník 9; číslo 1; s. 53 - 60
Hlavní autoři: Qader, Hogr M., Birdawod, Hawkar Q., Qader, Hevi M., Sedeeq, Bekhal S.
Médium: Journal Article
Jazyk:arabština
angličtina
Vydáno: Cihan University-Erbil 20.01.2025
Témata:
ISSN:2707-6342, 2707-6342
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This study investigates the impact of wavelet analysis on optimizing specification in the capability process. A new approach called the New Hybrid Capability Wavelet Approach (NHCWA) is proposed, which utilizes wavelet analysis to filter noise and outliers in the data. The study compares the NHCWA with the classical capability process using a dataset from a cake factory. The Coiflet 4 wavelet family and soft thresholding are employed to denoise the data. The results demonstrate that the NHCWA significantly improves the capability indices, achieving a 50% increase in Cp and a 30% increase in Cpk compared to the classical approach. Additionally, the NHCWA reduces the standard deviation of the process by 20%. These findings highlight the potential of wavelet analysis in enhancing the accuracy and effectiveness of capability analysis, leading to improved quality control in manufacturing processes.
ISSN:2707-6342
2707-6342
DOI:10.24086/cuejhss.v9n1y2025.pp53-60