Nowadays, the speed of implementation of technological advances is increasing. Moreover, the economic challenges posed by technological and social developments have led industrial companies to increase their agility and responsiveness in order to be able to manage the entire value chain. On the other hand, one of the most interesting and at the same time one of the most important challenges facing supply chains is Industry 4.0, which is based on digital technology and varies greatly in scale and complexity. It is more than what humanity has experienced through previous industrial revolutions, and decisions need to be made faster and more accurately. Accordingly, in this paper, a comprehensive framework for accelerating supply chain decisions with respect to Industry 4.0 is provided. In this regard, first, Industry 4.0 is described in detail. Next, a framework for demand forecasting in the 4.0 industry-based supply chain is provided using artificial intelligence tools. In this context, the simultaneous use of time series methods and machine learning methods is emphasized. The analysis of the proposed framework demonstrates the suitable benefits of using it in different supply chains.
