A Quality Prediction as a Service for Manufacturing Small and Medium-sized Enterprises (SMEs)

Abstract

The reconfigurable manufacturing is an essential functionality of smart factories in the future. In order to implement such reconfigurable manufacturing; collecting, analyzing, and monitoring large amounts of sensor data are becoming a key enable technology. And nowadays, the manufacturing industry is in the midst of a data-driven revolution, which means sensor data has become more accessible, ubiquitous and in the end generating large amounts of stored sensor data. This phenomenon would make it challenging for manufacturing SMEs to store and analyze them into useful and actionable information. However, it is not easy for SMEs to implement such actions due to their limited budgets and lack of ICT infrastructure. Thus, in this paper, we proposed a real-time quality prediction service, which is affordable to such manufacturing SMEs. The proposed service incorporates machine-learning algorithms that learn from historical production sensor data and generate the classifiers to determine the product quality patterns. An injection-molding example is illustrated to verify the proposed quality prediction as a service model.