Smart Industrial Supply Chain Management and Prediction System

Abstract

The idea is to build a smart stock management and supplier chain management system. The users have to place the load sensors at different locations for monitoring their stocks. Weights will be mapped to the number of stocks/ any other suitable unit using scale factor. When the stock falls below a certain set threshold, the users will automatically be notified through an app. The users will be able to view the current levels of stocks at sensor locations dynamically on the app. The collected sensor data of the number of stocks sold can then be used by the manufacturer to forecast the future requirements to meet demands. On uploading the file containing the orders with the number of stocks and location for a specific period of time, a heatmap visualization can be created which can be used to draw conclusions about how to do transport optimization or choosing a proper location for the warehouse. This app connects the wholesalers to the manufacturers to order stocks in the required quantities. This system can also be used in restaurants, pharmaceuticals and manufacture industrial stores where it maybe a critical situation if some item is not available or is lesser than the prescribed quantity. So, we can maintain the optimum quantity as per JIT (Just in Time) system. This product eliminates manual labor required for frequent stock checks and the error associated with it.