Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System

Abstract

Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the embedded intelligence analytics. This research applied this trend to the control of a key supplier’s real-time production planning for solving joint production goals with downstream producers. As a key supplier has several downstream producers in general, several uncertainties are embedded on the supply chain network such as the quality issue in the supplier and the occurrence of unexpected orders from the downstream industries. While the control of a supply plan is difficult considering these dynamics in traditional frameworks, the proposed framework detects the dynamic changes accurately using the constructed cloud system. Moreover, the real-time control considering uncertain scenarios as well as the extracted knowledge is achieved using the provided Industrial Internet of Things (IIoT) and simulation-based control model using stochastic network. To show the effective of the suggested framework, real manufacturing cases and their numerical analyses are provided.