Sanayi 4.0 için hazırlık ve olgunluk endeksi modeli geliştirilmesi
Development of readiness and maturity index model for industry 4.0
Yazar: CİHAN ÜNAL
Danışman: PROF. DR. CEMİL SUNGUR ; DR. ÖĞR. ÜYESİ HAKAN YILDIRIM
Selçuk Üniversitesi / Fen Bilimleri Enstitüsü / Bilişim Teknolojileri Mühendisliği Ana Bilim Dalı
Derece: Doktora, 2022
Konu: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol = Computer Engineering and Computer Science and Control
Dizin: Endüstri 4.0 = Industrial 4.0 ; Olgunlaşma = Maturation ; Olgunluk modeli = Maturity model ; Sayısallaştırma = Digitization ; Yapay zeka = Artificial intelligence

Özet:
Endüstri 4.0 özellikle sanayide çok sık duyulan bir kavram olmuştur. Kuşkusuz bu kavrama duyulan ilgi çok doğru ve rasyonel bir alana oturması ve çağdaş bilim ve teknoloji hedeflerine ulaşılması için farkındalık yaratması ile açıklanabilir. Ancak birbirinden çok farklı büyüklükte ve farklı alanlarda üretim bulunan sanayi kuruluşları düşünüldüğünde işletmelere yol göstermek, bu konudaki duyarlılıklarını artırmak ve Endüstri 4.0 kavramı karşısındaki kendi durumlarını anlamak bir diğer ifadeyle kendilerine ayna tutmak için Hazırlık ve Olgunluk modelleri kullanılmaktadır. Bu çalışmada öncül çalışmalardaki modeller taranmış ve görülen eksikler doğrultusunda daha ayrıntılı ve doğrudan sanayide test edilerek geliştirilen bir model oluşturulması amaçlanmıştır.
Ayrıca anket yapmanın zor ve zaman alması, maliyetlerinin yüksek olması nedeniyle özellikle sanayi bölgelerinde bulunan çok sayıda işletmenin sanayi olgunluk endeksi değerlendirmelerini daha hızlı, ucuz ve kolay yapabilmek amacıyla bu çalışmada makine öğreniminin başarısı araştırılmıştır.
Bu çalışma sadece akademik bir boşluğu gidermekle kalmamıştır, aynı zamanda Endüstri 4.0 gibi bir kavramın farkındalığını artırmıştır. Ayrıca her boyuttaki işletmelerin Endüstri 4.0 kavramını anlamasını ve kendi özelinde uygulamasını da kolaylaştırıcı bir rehber özelliğini taşımaktadır. Model yurt içi ve yurt dışında rahatlıkla uygulanabilirliğini ispat etmiştir. Bu çalışmanın ardıl çalışmalara ilham olması beklenmektedir.

Abstract:
Industry 4.0 has been a concept that has been heard very often, especially in the industry. Undoubtedly, the interest in this concept can be explained by the fact that it fits in a very correct and rational area and creates awareness in order to achieve the goals of modern science and technology. However, in the production of industrial enterprises in different areas have different sizes from each other and to guide businesses in considering this topic to understand their own situation and to increase the sensitivity across the concept of Industry 4.0, in other words, to a mirror to themselves in readiness and maturity models are used. In this study, the models in the preliminary studies were scanned and it was aimed to create a model that was developed by testing in more detail and directly in the industry in line with the shortcomings seen.
In line with the literature review, the opinions of the sector leaders and the opinions of the academic staff, different dimensions were added from the existing models and AHP (Analytical Hierarchy Process) was used to test their validity. On the one hand, the questionnaire developed to measure the scope of research and maturity-readiness status through field research has been modified and improved accordingly, and a comprehensive model called SANOL (Industrial Maturity Model) has been developed. The model can be applied face-to-face as well as online. In particular, the dimension of benefiting from Legal Regulations and Incentives that are not available in existing models and the sub-dimension of Corporate Culture have been added to our model and the gaps seen in the field have been filled.
In addition, the success of machine learning was also investigated in this study in order to make the industrial maturity index assessments of many enterprises located in industrial zones faster, cheaper and easier, due to the difficulty and time consuming of surveys and the high costs.
This study has not only addressed an academic gap; it has also increased awareness of a concept such as Industry 4.0. In addition, it also carries the feature of a guide that facilitates businesses of all sizes to understand the concept of Industry 4.0 and apply it in their own way. The model has proved its applicability easily at home and abroad. It is expected that this study will inspire future studiesIndustry 4.0 has been a concept that has been heard very often, especially in the industry. Undoubtedly, the interest in this concept can be explained by the fact that it fits in a very correct and rational area and creates awareness in order to achieve the goals of modern science and technology. However, in the production of industrial enterprises in different areas have different sizes from each other and to guide businesses in considering this topic to understand their own situation and to increase the sensitivity across the concept of Industry 4.0, in other words, to a mirror to themselves in readiness and maturity models are used. In this study, the models in the preliminary studies were scanned and it was aimed to create a model that was developed by testing in more detail and directly in the industry in line with the shortcomings seen.
In addition, the success of machine learning was also investigated in this study in order to make the industrial maturity index assessments of many enterprises located in industrial zones faster, cheaper and easier, due to the difficulty and time consuming of surveys and the high costs.
This study has not only addressed an academic gap; it has also increased awareness of a concept such as Industry 4.0. In addition, it also carries the feature of a guide that facilitates businesses of all sizes to understand the concept of Industry 4.0 and apply it in their own way. The model has proved its applicability easily at home and abroad. It is expected that this study will inspire future studies