Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications

Year : 2025 | Volume : 12 | Issue : 03 | Page : 36 48
    By

    Prithviraj Singh Rathore,

  1. Assistant Professor, Department of Computer Sciences and Applications Mandsaur University, Mandsaur, Madhya Pradesh, India

Abstract

Automation and robotics technologies have rapidly evolved, transforming modern manufacturing processes by improving productivity, quality, and operational efficiency. This review examines key advancements such as cloud robotics, machine vision, Industry 4.0 robotics, Building Information Modeling (BIM) combined with Computer Numerical Control (CNC), joystick-controlled automation, and intelligent manufacturing systems. These technologies utilize artificial intelligence (AI), machine learning (ML), digital twins, collaborative robots, programmable logic controllers (PLCs), and cyber-physical systems (CPS) to enable flexible, adaptive, and precise industrial operations. Despite their benefits, challenges like system interoperability, data security, shortage of skilled personnel, and safety concerns remain. The integration of blockchain technology further enhances supply chain traceability and transparency by enabling decentralized and tamper-proof record-keeping. This study highlights the need for standardized frameworks and interoperable platforms to support seamless integration. It focuses on advancing human-robot collaboration (cobots), bridging simulation-to-reality gaps, improving cybersecurity, and expanding adoption to small and medium-sized enterprises (SMEs). Incorporating sustainability metrics will be essential for responsible and inclusive industrial growth in the Industry 4.0 era. The study examines the integration of machine vision, artificial intelligence (AI), the Internet of Things (IoT), and sensor-based systems that enhance defect detection, process monitoring, and real-time decision-making. Various robotic inspection systems—such as automated optical inspection (AOI), robotic non-destructive testing (NDT), and collaborative robots for in-line quality assurance—are discussed in terms of their design, accuracy, and adaptability across diverse manufacturing environments. Furthermore, the review highlights the benefits of these technologies, including improved reliability, reduced human error, and increased production throughput, while also addressing implementation challenges such as high initial costs, data management, and system integration. The paper concludes with insights into emerging trends, including AI-driven predictive quality control and digital twins, outlining future directions for fully automated, intelligent manufacturing systems.

Keywords: Automation, robotics, cloud robotics, machine vision, industry 4.0, BIM-CNC Integration, intelligent manufacturing, blockchain, supply chain traceability, human-robot collaboration, cyber-physical systems, smart manufacturing

[This article belongs to Journal of Mechatronics and Automation ]

How to cite this article:
Prithviraj Singh Rathore. Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications. Journal of Mechatronics and Automation. 2025; 12(03):36-48.
How to cite this URL:
Prithviraj Singh Rathore. Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications. Journal of Mechatronics and Automation. 2025; 12(03):36-48. Available from: https://journals.stmjournals.com/joma/article=2025/view=234092


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Regular Issue Subscription Review Article
Volume 12
Issue 03
Received 11/07/2025
Accepted 10/10/2025
Published 22/10/2025
Publication Time 103 Days
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