Computer vision applications for SMEs in retail and manufacturing to automate quality control and inventory management processes: Artificial Intelligence /Machine Learning Enhancements

Friday Ugbebor (), Olushola O. Aina () and John O. Ugbebor ()

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2024, vol. 5, issue 1, 460-500

Abstract: Introduction: In the modern world SMEs in the manufacturing and retail sector have learnt the need to employ computer vision with features in artificial intelligence and machine learning to automate quality control and inventory control processes and methods for optimal efficiency. Small and medium-sized enterprises (SMEs) are also investing in computer vision applications that use AI/ML to improve quality assurance and inventory tracking. This research focuses on the extent and implementation of the above-stated technologies among SMEs, the challenges, and prospects of these technologies. Materials and Methods: A comprehensive literature review was conducted, analysing relevant studies, reports, and industry publications focused on AI/ML applications in SMEs' quality control and inventory management. Furthermore, experiences from case and field studies were explored to provide understanding of implementation approaches and benchmarks. Results: The research indicates that AI/ML-based computer vision applications can drastically improve several aspects of the SMEs, including operational performance, product quality, and inventory reliability. Applying these technologies for conducting quality check and tracking inventories also reduces the human intervention, which in turn reduces costs and enhances the satisfaction level of the customers. However, there are difficulties connected with data quality, integration with legacy systems, and talents that can use it. Discussion: The study under discussion also uncovered such a critical issue as the absence of a clear and vast plan for AI/ML integration for SMEs: data management, IT infrastructure improvements, and employees’ education. Proper integration and implementation of these technologies require close cooperation with the providers of technology solutions and other professionals to increase effectiveness. Conclusion: AI/ML-powered computer vision applications offer SMEs in retail and manufacturing a competitive edge by optimizing quality control and inventory management processes. Mitigating the risks and exploiting the opportunities that come with such technologies help SMEs to continue keeping up and adapting to changes in the new digitized environment.

Keywords: Computer Vision; Artificial Intelligence (AI); Machine Learning (ML); Small and Medium Enterprises (SMEs); Quality Control; Inventory Management; Manufacturing Automation; Retail Operations; Edge Computing (search for similar items in EconPapers)
Date: 2024
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