Hello Readers, welcome back to our blog. Today's post will discover how Artificial Intelligence (AI) is transforming Inventory Management systems in order to supply businesses. Large enterprises face many challenges in management of its inventory (Seeloz, 2021). Managing and spot-checking stock is a repetitive process which enables warehouse operatives to miss important data analysis of company’s stock which can result a negative impact on the business. Warehouse companies today have identified two major issues: obstacles in business planning and high operational budget costs (Fedyk, 2020). The overabundance of data and tracking issues can become resolute. Using machine learning, algorithms and other dimensions of Artificial Intelligence, new insights, accurate demand forecasting, better regulated inventory, and successful operations of a warehouse can be accomplished. Manyika et al (2017) states that Warehousing has 57 percent automation potential. Autonomous patent-pending drones have the potential to scan ten-thousand pallets a day. A drone is equipped with cameras and optical scanners enabling the Unmanned Aerial Vehicle (UAV) to scan bar codes, QR codes, text codes and Radio-frequency Identification (RFID) tags. Inventory discrepancy reports are generated to compare real-time data and the Warehouse Management System (WMS). This results in faster stocktaking, increased safety, reduced operational downtime, increased stock, and improved accuracy through automated reports (Infinium Robotics, 2019). Smart inventory management in a warehouse allows suppliers to place data metric codes onto pallets. The pallets are tracked as they enter a warehouse, and processes can become modified. This reduces human error and allows statistics to value items and evaluate what improvements can be added to the item (Lenovo, 2019). Image Source: https://www.youtube.com/watch?v=C2sIfxx0PfI (Lenovo, 2019) Custom Inventory Management models are able to create new packages through the process of uploading zip files or ML folders. After including the required information, and uploading the package, a workflow model is produced. The data stored in the file is sent back to the AI centre to improve the virtual model that was previously created. The robot navigates product information through the inventory and begins to capture previous sales data of each product. This information is once again sent back to the AI centre, to predict the ideal quantity of products that should be kept at any given time. The AI management tool completes its process by purchasing the listed products in the inventory (UiPath, 2021). Bossa Nova is a robot that is currently being used in retail shopping. This machine not only identifies human error but also improves customer experience. The autonomous robot uses LiDAR to navigate through a store which scans shelves using two dimensional (2D) and three- dimensional (3D) displays, collecting images of shelves, freezers and produce display. The robots’ AI software uses data points to identify items that are out-of-stock, misplaced or mispriced. The data is then sent to store associates to assess if the stock has been correctly managed and allows employees to correct their errors (Ko, 2019). Image Source: https://digital.hbs.edu/platform-digit/submission/bossa-nova-robotics-ai-and-groceries/ (Ko, 2019) Artificial Intelligence has improved and resolved many challenges in Inventory management. Stores can now be in control of its’ stock, out-of-stock items can be greatly reduced, overstocking can be easier to identify and prevent, important data can now be detected, and companies can better predict their investments to avoid investments that will produce little or no growth (BE-terna International, 2021). Thank you for reading! We would appreciate any feedback or insights on any topics of our blog. Follow our social media channels for regular updates relating to Artificial Intelligence in real-world applications. REFERENCES BE-terna International (2021) How Artificial Intelligence is improving your inventory optimization. Available at: https://www.youtube.com/watch?v=WD28kRbAjHQ [Accessed 20 March 2022]. Fedyk, Y. (2020) ‘5 Ways to Improve Inventory Management Using AI’, inVerita, 2 June. Available at: https://inveritasoft.com/blog/4-ways-to-improve-inventory-management-using-ai#:~:text=Artificial%20Intelligence%20is%20capable%20of,and%20acting%20on%20the%20predictions. [Accessed 20 March 2022]. Infinium Robotics (2019) Infinium Scan - Automated Stocktaking Drone for Warehouse Inventory management. Available at: https://www.youtube.com/watch?v=9WmjabZrB3c [Accessed 20 March 2022]. Ko (2019) Bossa Nova: Robotics, AI and Groceries. Available at: https://digital.hbs.edu/platform-digit/submission/bossa-nova-robotics-ai-and-groceries/ [Accessed 20 March 2022]. Lenovo (2019) Smart Inventory Management In Action at Accelerate 2019. Available at: https://www.youtube.com/watch?v=C2sIfxx0PfI [Accessed 20 March 2022]. Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P. and Dewhurst, M. (2017) ‘A future that works: AI, Automation, Employment, and Productivity’, Open Access Library Journal, 5(9), Scientific Research. Available at: https://www.mckinsey.com/~/media/mckinsey/featured%20insights/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works-Executive-summary.ashx [Accessed 20 March 2022]. Seeloz (2021) SCAS Distribution Supply Chain Planning. Powered by Seeloz AI. Available at: https://www.youtube.com/watch?v=DyqCbC4_n8w [Accessed 20 March 2022]. UiPath (2021) AI Use Case: Inventory Management. Available at: https://www.youtube.com/watch?v=tjQBiIdinLI [Accessed 20 March 2022].
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