In this study by using the data from industrial sector, the images and relation structures of factors and observations causing any problem in process have been examineted using multidimensional scaling and cluster analysis.
📌 3 Key Takeaways
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Objective & Hypothesis:Multivariate statistical techniques used in applied quality control play important roles in problem-solving and decision making activities to improve the process.
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Key Findings & Data:Multivariate statistical techniques used in applied quality control play important roles in problem-solving and decision making activities to improve the process.
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Conclusion & Impact:In this study by using the data from industrial sector, the images and relation structures of factors and observations causing any problem in process have been examineted using multidimensional scaling and cluster analysis.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
Multivariate statistical techniques used in applied quality control play important roles in problem-solving and decision making activities to improve the process. In this study by using the data from industrial sector, the images and relation structures of factors and observations causing any problem in process have been examineted using multidimensional scaling and cluster analysis.
Özet
Kalite kontrolde uygulanan çok değişkenli istatistiksel teknikler süreç iyileştirmeye yönelik karar verme ve problem çözme faaliyetlerinde etkin rol oynamaktadır. Çalışmada üretim sektörüne ilişkin veriler kullanılarak çok boyutlu ölçekleme ve kümeleme analizi ile süreçteki herhangi bir probleme neden olan etkenlerin ve gözlemlerin ilişki yapıları ve görüntüleri incelenmiştir.
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Cite This Article
HAMURKAROĞLU, C., ÖZMEN, İ. (2022). The use of multidimensional scaling in the statistical quality control and its application. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 3 - Sayı: 2, 235–240. https://ajindex.com/articles/438512
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