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].…”

Design and Implementation of Cloud-Dust Based Intelligent System

“…It effectively reduces the computing time of feature extraction. Chung-Lin Huang [6] develop the cloud computing based scheduling system using optimized layout method for manufacturing quality in the research. And the advantages of low cost, just good quality, production fluency and flexible management are proposed.…”