A PCA-BPN approach for estimating simulation workload in cloud manufacturing

Cloud manufacturing is a novel manufacturing technology that supports factories distributed around the world with ubiquitous accesses to manufacturing resources. Estimating the simulation workload for simulating a factory online is an important topic to cloud manufacturing. To investigate this, a principal component analysis (PCA)-back propagation network (BPN) approach is proposed in this study. The real data of some simulation tasks have been collected to test the proposed methodology. The experimental results supported the superiority of the proposed methodology over some existing methods in terms of the estimation accuracy.