Demonstrating computer vision to small- and medium-sized enterprises in manufacturing: Toward overcoming costs and implementation challenges

Abstract

Computer vision (CV) systems are crucial in various fields, such as manufacturing. However, the general feedback from small and medium-sized enterprises (SMEs) in manufacturing indicates that implementing CV systems are out of reach due to their high costs, the need for expertise, and the complexities of Machine Learning (ML). To demonstrate the feasibility and applicability for SMEs, we present a cost-effective portable CV-based demonstrator for SMEs in manufacturing. Incorporating low-cost hardware components, the system integrates open-source software and employs Transfer Learning to adapt pre-existing ML models. We present two illustrative use cases with fault detection and inventory management based on plastic brick datasets including various colors and shapes to demonstrate the system's effectiveness. Bringing this into a showable demonstrator, all components are integrated into a portable suitcase as a plug and play demonstration. We showcase the portable demonstrator at German television and four different industrial fairs, leveraging these dynamic platforms for direct interaction with SMEs and stakeholders. Firsthand insights and feedback from SMEs regarding our demonstration and their challenges, as well as opportunities for CV in manufacturing were received and summarized in this research.