Completed Materials & Manufacturing Computing & AI

Perspectives and Challenges in the Adoption of AI-Based Quality Control in Manufacturing SMEs: A Comparative Study of the UK and South Africa

Funder AMS (part of Academy)
Recipient organisation University of the Free State
Funding £25K
Period Mar 2025 — Mar 2026

In plain English

AI plain-English summary

UK manufacturing small and medium enterprises are being left behind in the shift to AI-driven quality control, while their South African counterparts face even steeper barriers. This matters because quality control—checking products for defects, reducing waste, and ensuring consistency—is essential for any manufacturer. AI can automate this process, catching faults faster and more reliably than human inspectors. But smaller firms often lack the capital, infrastructure, or expertise to adopt such systems. The UK and South Africa offer a useful contrast: UK SMEs generally have better access to technology and export markets, while South African SMEs struggle with weak infrastructure and limited funding. This study will compare the obstacles and opportunities in both countries. If the research succeeds, it will give SMEs, policymakers, and AI suppliers a practical roadmap for adoption. That could help smaller manufacturers stay competitive, reduce waste, and comply with regulations more easily. The project supports sustainable industrialisation and inclusive economic growth, aligning with UN Sustainable Development Goals 8 and 9. It does not promise a breakthrough in AI itself, but rather a clearer understanding of how to make existing AI tools work for the businesses that need them most.

View original technical description
In 2023, the UK had over 268,175 manufacturing small and medium enterprises (SMEs) (Statsta, 2023), while South Africa had approximately 17,981 (SEDA, 2023). Both industries significantly contribute to economic growth by promoting innovation and providing jobs. However, UK SMEs often benefit from stronger access to modern technology and worldwide export markets, whereas South African SMEs confront obstacles such as weak infrastructure and restricted capital. Quality control is vital for manufacturing SMEs, assuring consistent product quality, decreasing faults, and saving waste (Alshahrani & Husain, 2024). It promotes consumer satisfaction, strengthens brand reputation, and boosts profitability by boosting efficiency and decreasing expenses. Moreover, it helps SMEs comply with industry regulations more effectively. Recent research highlights the increasing integration of AI in quality control systems, enabling automation, real-time monitoring, predictive maintenance, and faster fault identification. AI-driven quality control may minimize human error, enhance efficiency, and improve scalability, making SMEs more competitive globally (Ibrahim et al., 2024). This study will evaluate the obstacles and potential in adopting AI-based quality control in UK and South African SMEs. It will provide assistance for key stakeholders, including SMEs, policymakers, and AI technology suppliers, to establish effective AI adoption plans, supporting programs like the AI Sector Deal and Industry 4.0. Aligned with UNSDGs, particularly SDG 9 and SDG 8, the project encourages sustainable industrialization and inclusive growth.

View the original record at the funder ↗

Researchers

Sandile Shongwe (EPMC Awardee)

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Original classification

Networking Grants

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