Quality Improvement Application in The Conductor Industry with Statistical Process Control

İrem Meran; Hacer Güner Gören

Makale detayları

Quality Improvement Application in The Conductor Industry with Statistical Process Control

Yazarlar:

İrem Meran | Hacer Güner Gören

Yayıncı:

Bursa Uludağ University

Ana Başlıklar:

Endüstri Mühendisliği

Dergi:

Uludağ Üniversitesi Mühendislik Fakültesi Dergisi Vol.29 Issue 1, pp.67-84

Belge Tipi:

Makale

Yayın Tarihi:

4/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001313349

pISSN:

2148-4155

Anahtar kelimeler:

Özet:

 Using quality tools, it is possible to obtain high quality products, reduce scrap rate and ensure customer satisfaction control by keeping the process under control. The most widely used tool among these is Statistical process control SPC with the aim of controlling, monitoring and improving a process. In this study, quality improvement studies were conducted in a company in conductor industry. Firstly, the current situation analysis of one product was analyzed using basic statistical methods such as histograms, pareto analysis, pareto analysis, scatter plot and control charts. Brainstorming and ishikawa diagram were used to determine the root causes of a decrease in the process capability index. Then, multivariate regression analysis was used to analyze the inputs thought to be effective in the process. Based on the results of the regression analysis, the experimental designs were developed and the correlation equation was constructed again. The production was carried out with the parameters obtained from experiments designed to achieve the target process adequacy and the process was observed to be improved based on the results obtained. This study has revealed that the use of statistical process control techniques in industrial applications can provide workforce, time, resource use efficiency and customer satisfaction.

 Using quality tools, it is possible to obtain high quality products, reduce scrap rate and ensure customer satisfaction control by keeping the process under control. The most widely used tool among these is Statistical process control SPC with the aim of controlling, monitoring and improving a process. In this study, quality improvement studies were conducted in a company in conductor industry. Firstly, the current situation analysis of one product was analyzed using basic statistical methods such as histograms, pareto analysis, pareto analysis, scatter plot and control charts. Brainstorming and ishikawa diagram were used to determine the root causes of a decrease in the process capability index. Then, multivariate regression analysis was used to analyze the inputs thought to be effective in the process. Based on the results of the regression analysis, the experimental designs were developed and the correlation equation was constructed again. The production was carried out with the parameters obtained from experiments designed to achieve the target process adequacy and the process was observed to be improved based on the results obtained. This study has revealed that the use of statistical process control techniques in industrial applications can provide workforce, time, resource use efficiency and customer satisfaction.

 Using quality tools, it is possible to obtain high quality products, reduce scrap rate and ensure customer satisfaction control by keeping the process under control. The most widely used tool among these is Statistical process control SPC with the aim of controlling, monitoring and improving a process. In this study, quality improvement studies were conducted in a company in conductor industry. Firstly, the current situation analysis of one product was analyzed using basic statistical methods such as histograms, pareto analysis, pareto analysis, scatter plot and control charts. Brainstorming and ishikawa diagram were used to determine the root causes of a decrease in the process capability index. Then, multivariate regression analysis was used to analyze the inputs thought to be effective in the process. Based on the results of the regression analysis, the experimental designs were developed and the correlation equation was constructed again. The production was carried out with the parameters obtained from experiments designed to achieve the target process adequacy and the process was observed to be improved based on the results obtained. This study has revealed that the use of statistical process control techniques in industrial applications can provide workforce, time, resource use efficiency and customer satisfaction.

 Süreci kontrol altında tutarak yüksek kalitede ürün elde etmek, hurda oranını azaltmak ve müşteri memnuniyetini sağlamak kalite araçları kullanarak mümkündür. Bunlardan en yaygın kullanılanı bir süreci kontrol altında tutmak, izlemek ve iyileştirmek amacını taşıyan İstatistiksel süreç kontrolüdür IPK. Bu çalışmada iletken endüstrisinde faaliyet gösteren bir firma için istatistik süreç kontrol teknikleri ile kalite iyileştirme çalışmaları yapılmıştır. Öncelikle, temel istatistiksel süreç kontrol tekniklerinden histogram, pareto analizi, serpilme diyagramları ve kontrol çizelgeleri kullanılarak bir ürün için sürecin mevcut durum analizi yapılmıştır. Beyin fırtınası ve balık kılçığı diyagramı yardımıyla sürecin yeterliliğinin düşmesine sebep olduğu düşünülen kök nedenler belirlenmiştir. Daha sonra, çok değişkenli regresyon analizi ile süreçte etkili olduğu düşünülen girdiler analiz edilmiştir. Regresyon analizinin sonucuna göre deney tasarımları geliştirilmiş ve tekrar ilişki denklemi kurulmuştur. Hedef süreç yeterliliğine ulaşabilmek için tasarlanmış deneylerden elde edilen parametreler ile üretim yapılmış ve elde edilen sonuçlara göre sürecin müşteri isteği doğrultusunda iyileştirildiği gözlenmiştir. Bu çalışma, istatistiksel süreç kontrol tekniklerinin endüstriyel uygulamalarda kullanımının iş gücü, zaman, kaynak kullanım verimliliği ve müşteri memnuniyeti sağlayabileceğini göstermiştir.

Makale detayları

Quality Improvement Application in The Conductor Industry with Statistical Process Control

Yazarlar:

İrem Meran | Hacer Güner Gören

Yayıncı:

Bursa Uludağ University

Ana Başlıklar:

Endüstri Mühendisliği

Dergi:

Uludağ Üniversitesi Mühendislik Fakültesi Dergisi Vol.29 Issue 1, pp.67-84

Belge Tipi:

Makale

Yayın Tarihi:

4/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001313349

pISSN:

2148-4155

Statistical Process Control

Univariate and Multivariate Statistical Process Control

Control Charts

Experimental Design.İstatistiksel Proses Kontrol

Tek Değişkenli ve Çok Değişkenli İstatistiksel Proses Kontrol

Kontrol Çizelgeleri

Deneysel Tasarım

Sayı

Makale detayları

Yazarlar: İrem Meran | Hacer Güner Gören

Yayıncı: Bursa Uludağ University

Ana Başlıklar: Endüstri Mühendisliği

Dergi: Uludağ Üniversitesi Mühendislik Fakültesi Dergisi Vol.29 Issue 1, pp.67-84

Belge Tipi: Makale

Yayın Tarihi: 4/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001313349

pISSN: 2148-4155

Sayı

Yazarlar:

İrem Meran | Hacer Güner Gören

Yayıncı:

Bursa Uludağ University

Ana Başlıklar:

Endüstri Mühendisliği

Dergi:

Uludağ Üniversitesi Mühendislik Fakültesi Dergisi Vol.29 Issue 1, pp.67-84

Belge Tipi:

Makale

Yayın Tarihi:

4/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001313349

pISSN:

2148-4155