Optimizing the Voice of Customer (VoC) Strategy through Agentic AI-Based Quality Control System

  • Restin Meilina Fakultas Ekonomi dan Bisnis, Universitas Nusantara PGRI Kediri
  • Rachmad Santoso Fakultas Ekonomi dan Bisnis, Universitas Nusantara PGRI Kediri
  • Moh Syaiful Anam Al Manshur Fakultas Ekonomi dan Bisnis, Universitas Nusantara PGRI Kediri
Keywords: Voice of Customer, Agentic AI, Quality Control, Customer Feedback, Industry 5.0

Abstract

In today’s customer-driven industrial landscape, the ability of companies to align product quality with evolving customer expectations has become a critical success factor. This study proposes an integrative model that incorporates Voice of Customer (VoC) into a Quality Control (QC) system powered by Agentic Artificial Intelligence (AI). The system is designed to autonomously analyze customer feedback, adjust quality parameters, and execute improvements within the production process without human intervention. Using a quantitative approach, the study evaluates the effectiveness of the system through key strategic indicators such as customer satisfaction, cost efficiency, and marketing performance. The findings reveal that implementing Agentic AI in QC not only enhances product quality but also transforms QC into a data-driven marketing tool that is both proactive and adaptive. This model aligns with the vision of Industry 5.0, where technology and human-centric needs converge to enable continuous and intelligent quality improvement.

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References

Griffin, A., & Hauser, J. R. (2021). “The Voice of the Customer Revisited: Modern Applications in Customer Experience Management.” Journal of Marketing Research 58(6):1123–1138.

Hassan, S., & Ahmad, M. (2023). “Enhancing Manufacturing Quality through AI and Voice of Customer Integration.” Journal of Manufacturing Processes, 79 79:142–153.

He, H., & Deng, X. (2022). Application of AI in Customer Complaint Prediction and Management in Manufacturing. Computers in Industry, 140, 103672.

Huang, J., & Wang, Y. (2022). Exploring AI in Real-Time Quality Control Systems: Applications and Challenges. Journal of Industrial Engineering and Management, 15(1), 33-49.

Jiang, L., & Li, M. (2020). Intelligent Quality Control System Using Deep Learning for Product Defect Detection. International Journal of Advanced Manufacturing Technology, 108(3), 821-831.

Kamaruddin, A., & Rahman, R. (2021). Penggunaan Machine Learning untuk Meningkatkan Proses Quality Control Berbasis Data Pelanggan pada Industri Elektronik. Jurnal Teknik Industri, 22(3), 160-172. (Jurnal Nasional).

Khan, F., & Ahsan, M. (2021). Artificial Intelligence-Based Real-Time Quality Monitoring for Automated Manufacturing Systems. Journal of Manufacturing Science and Engineering, 143(5), 051008.

Kumar, V., & Shah, D. (2020). Customer Satisfaction and Feedback Analysis in the Age of Artificial Intelligence: A Survey. International Journal of Customer Relationship Marketing and Management, 11(3), 58–74.

Kusumawati, D. M., & Utami, N. S. (2021). Penerapan Kecerdasan Buatan dalam Pengendalian Kualitas Produk pada Industri Otomotif. Jurnal Rekayasa Sistem dan Teknologi, 12(2), 85-94. (Jurnal Nasional).

Kim, D., Park, J., & Choi, S. (2020). Machine Learning Applications for Defect Detection in Manufacturing Processes. International Journal of Production Research, 58(17), 5256–5271.

Li, Y., & Chen, H. (2021). AI-Driven Predictive Maintenance and Quality Control in Smart Manufacturing Systems. Computers & Industrial Engineering, 156, 107244.

Liu, Y., & Zhang, Z. (2021). Advanced AI applications in quality management systems: A global perspective. International Journal of Advanced Manufacturing Technology, 113(3), 939-948.

Montgomery, D. C. (2020). Introduction to Statistical Quality Control (8th ed.). Wiley.

Rahman, M., & Lee, K. (2022). Voice of Customer Analysis Using Natural Language Processing: Insights for Quality Improvement. Total Quality Management & Business Excellence, 33(11–12), 1219–1234.

Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson Education.

Sari, M. A., & Rahardjo, B. (2021). Aplikasi Teknologi AI dalam Pengendalian Kualitas di Industri Manufaktur: Studi Kasus pada Perusahaan Elektronik. Jurnal Teknologi Industri, 12(2), 67-75. (Jurnal Nasional)

Wang, T., & Lu, C. (2021). A Systematic Approach to Quality Control Using AI and Customer Data Analysis. Journal of Manufacturing Science and Engineering, 143(2), 021015.

Wang, Y., Yu, X., Zhang, C., & Zhao, H. (2023). Agentic Artificial Intelligence for Industry 5.0: A Framework for Human–AI Collaboration in Adaptive Manufacturing Systems. Journal of Intelligent Manufacturing, 34(4), 1073–1089.

Wang, Z., Li, X., & Zhang, H. (2023). Agentic AI in decision-making systems: A new approach for proactive industrial applications. AI and Society, 38(2), 459-475.

Yang, Y., & Li, F. (2020). AI-Driven Predictive Maintenance and Quality Control in Smart Manufacturing: A Case Study. Journal of Intelligent Manufacturing, 31(1), 127-141.

Zhao, Y., Xu, L., & Sun, Y. (2021). AI for quality control in manufacturing: A systematic review. Journal of Intelligent Manufacturing, 32(4), 893-911.

Zhang, S., & Xie, Y. (2022). “Leveraging AI to Bridge the Gap Between Customer Expectations and Quality Management.” Journal of Business Research 142:131–139.

Published
2025-04-16
How to Cite
Meilina, R., Santoso, R., & Anam Al Manshur, M. S. (2025). Optimizing the Voice of Customer (VoC) Strategy through Agentic AI-Based Quality Control System. Jurnal MANDIRI: Ilmu Pengetahuan, Seni, Dan Teknologi, 8(2), 117 - 123. https://doi.org/10.33753/mandiri.v8i2.332
Section
Articles