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Journals / Advances in Artificial Intelligence Research / 2025 / Cilt: 5 Sayı: 2

The Impact of Artificial Intelligence-Based Quality Control Systems on Production Efficiency in the Context of Industry 4.0: An Empirical Study

Endüstri 4.0 Bağlamında Yapay Zekâ Tabanlı Kalite Kontrol Sistemlerinin Üretim Verimliliğine Etkisi: Uygulamalı Bir İnceleme

Begüm Acar(Şafak Makina A.Ş.)0000-0002-7062-501X
Özkan Şahin(DÜZCE ÜNİVERSİTESİ, İŞLETME FAKÜLTESİ)0000-0001-5341-1274
Pages
56–65
Publication Date
2025-12-23
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

By integrating measurement, visual, and identity data into a single traceability chain, the study proposes a practical and scalable model for transitioning from reactive inspection to proactive/preventive quality assurance.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study presents an integrated quality control architecture designed in line with Industry 4.0 principles for an automotive-focused production line.
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Key Findings & Data:A three-tier software stack (data acquisition, processing/analysis, decision/feedback) operates in real time through a microservices architecture with MES/PLC integration.
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Conclusion & Impact:By integrating measurement, visual, and identity data into a single traceability chain, the study proposes a practical and scalable model for transitioning from reactive inspection to proactive/preventive quality assurance.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:endüstri 4.0 · havalı mastar · montaj doğrulama

Abstract

This study presents an integrated quality control architecture designed in line with Industry 4.0 principles for an automotive-focused production line. The architecture unifies micron-level dimensional inspection via air gauges, assembly verification through CNN-based computer vision, and full traceability based on DMC/QR + OCR within a single decision layer. A three-tier software stack (data acquisition, processing/analysis, decision/feedback) operates in real time through a microservices architecture with MES/PLC integration. Decision fusion triggers the right intervention without stopping the line through an “accept–gray zone–segregate” policy; SPC-based online monitoring makes minor drifts visible at an early stage. The implementation increased assembly accuracy and measurement reliability, strengthened traceability by catching duplicate identity assignments in process, reduced the risk of shipping defects, and lowered manual inspection burden. By integrating measurement, visual, and identity data into a single traceability chain, the study proposes a practical and scalable model for transitioning from reactive inspection to proactive/preventive quality assurance.

Özet

Bu çalışma, otomotiv odaklı bir üretim hattında Endüstri 4.0 ilkeleriyle tasarlanan entegre bir kalite kontrol mimarisini sunmaktadır. Mimari; mikron düzeyinde boyutsal denetim sağlayan havalı mastar, CNN tabanlı görüntü işleme ile montaj doğrulama ve DMC/QR + OCR temelli tam izlenebilirliği tek bir karar katmanında birleştirir. Üç katmanlı yazılım yapısı (veri toplama, işleme/analiz, karar/geri bildirim), mikroservis mimarisi ve MES/PLC entegrasyonuyla gerçek zamanlı çalışır. Karar füzyonu “kabul–gri alan–ayır” politikasıyla üretim akışını durdurmadan doğru müdahaleyi tetikler; SPC tabanlı çevrimiçi izleme küçük sapmaları erken aşamada görünür kılar. Uygulama, montaj doğruluğunu ve ölçüm güvenilirliğini artırırken mükerrer kimlik atamalarını süreç içinde yakalayarak izlenebilirliği güçlendirmiş, hatalı ürün sevkiyat riskini azaltmış ve manuel denetim yükünü düşürmüştür. Çalışma, ölçüm–görsel–kimlik verilerini tek bir izlenebilirlik zincirinde bütünleştirerek reaktif kontrolden proaktif/önleyici kalite güvence yaklaşımına geçiş için uygulanabilir ve ölçeklenebilir bir model önermektedir.

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Cite This Article

Acar, B., Şahin, Ö. (2025). The Impact of Artificial Intelligence-Based Quality Control Systems on Production Efficiency in the Context of Industry 4.0: An Empirical Study. Advances in Artificial Intelligence Research, Cilt: 5 Sayı: 2, 56–65. https://doi.org/10.54569/aair.1808940

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