%0 Journal Article
	%A Ioannis Andrianakis and  Vasileios Gkatas and  Nikos Eleftheriadis and  Alexios Ellinidis and  Ermioni Avramidou
	%D 2024
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 207, 2024
	%T PredictionSCMS: The Implementation of an AI-Powered Supply Chain Management System
	%U https://publications.waset.org/pdf/10013537
	%V 207
	%X The paper discusses the main aspects involved in the development of a supply chain management system using the developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.
	%P 65 - 71