AI Optimised Raw Material Restocking
Our AI-powered tool revolutionizes warehouse management by efficiently predicting product demand, reducing inventory costs, and enhancing sustainability. Leveraging historical data and domain knowledge, the solution optimizes restocking decision and enhances productivity.
noun /ˈbreɪk.θruː/
Solved for good
Reduced Inventory Costs
Efficiently managing warehouse space by minimizing storage of unwanted materials, thus lowering expenses.
Improved Sustainability
Optimizing material storage to minimize waste, leading to a positive environmental impact.
Enhanced Productivity
Accurate prediction of raw material needs eliminates unnecessary lead time and boosts overall operational efficiency.
Rising Costs and Complexity
To scrap or not scrap?
Warehousing raw materials can be costly with limited time and space, causing increased inventory costs when storing unneeded items. This also adds complexity to material storage and retrieval processes. On the other hand, prematurely disposing of materials leads to elevated production costs, longer lead times, and reduced productivity.
fabrications per day are impacted
Optimized Stocking
AI-Driven Solution
Traditional restocking methods based on simple statistics proved financially disadvantageous. Our AI tool overcomes these shortcomings by taking into account various factors, leveraging historical data, and collaborating with domain-savvy engineers and business teams for optimal material storage. This project showcases the power of AI and data in minimizing waste, enhancing sustainability, and contributing to a better planet. The tool predicts material restocking needs, forecasts sales orders, and simulates optimal order allocation to raw materials while maintaining full explainability through user-friendly interfaces.
What can be solved?
Everything.
However here are a few common pain points that we often see, which can be solved through our programs and will lead to an AI breakthrough.
Get started with AI
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