Cloud Computing Based Intelligent Manufacturing Scheduling System Using the Quality Prediction Method

Abstract

This paper proposes the development of a cloud computing based intelligent manufacturing scheduling system (CBIMS) using the quality prediction method. A CBIMS continuously builds up many different production line layout modes. We use the cloud database for scattering and storing data, and the scheduling engine contains a sequence score system of products, an optimized layout system, and a monitoring system for all available resources. The results show the advantages, including low cost, good quality, production fluency, and flexible management.

Performance Prediction through OEE-Model

“…It states that the simulation model demonstrates Predictions, recommendations, and dynamic optimization [17]. The Cloud computing-based simulation model manufacturing system is employed to improve efficiency and reduce costs related to production [18]. Prediction of OEE by applying statistical tools are employed to correlate assessment and predict the shutdowns for maintenance [19].…”