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Inventory Management & Demand Forecasting - EOQ

Inventory Check & EOQ

This workflow upon execution checks current inventory levels for various products located in various warehouses. The end user then has the option to edit their confidence level of not wanting to experience a stock out. This will then display the products and related warehouse in need of instant re-order based on current inventory, average daily demand, and delivery lead times.

The next portion will lead us to a page which allows the consumer the ability to notice historic demand trends and take notice for any outliers or changes in demand trends.

Next will be some basic linear regression testing, to make future demand predictions. The results of this can then be applied into the EOQ formula along with holding and ordering cost for each associated product.

This shows an example of how your team can use KNIME for inventory management and demand forecasting for topics such as Economic Order Quantity (EOQ). For more information see the workflow metadata in View -> Description. This component gives the user the option to set the confidence level of howthey want to manage stocking out risk. Once refreshed the table will thendisplay the products that need to be re-orederd. Prior to calculating EOQ, this page gives the user the ability to view thedifferent products historic demand trends. Finally, this follows-through with a linear regression model to predict futuredemand. This is just an example and can be replaced with any demandforecasting techniques. Confidence Restock Demand Review ML Modeling This shows an example of how your team can use KNIME for inventory management and demand forecasting for topics such as Economic Order Quantity (EOQ). For more information see the workflow metadata in View -> Description. This component gives the user the option to set the confidence level of howthey want to manage stocking out risk. Once refreshed the table will thendisplay the products that need to be re-orederd. Prior to calculating EOQ, this page gives the user the ability to view thedifferent products historic demand trends. Finally, this follows-through with a linear regression model to predict futuredemand. This is just an example and can be replaced with any demandforecasting techniques. Confidence Restock Demand Review ML Modeling

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: ryanrudd
Created at: 2021-10-13
On NodePit since: 2023-12-19
Last update: 2024-12-17
Created with KNIME version: v4.5.0
Tags: ManufacturingEconomic Order QuantityInventory ManagementSupply Chain

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