Challenges Hindering Growth
Component suppliers working with large corporations often face recurring difficulties. A lack of data on the actual usage of parts forces them to rely on past experiences. This results in errors: production either fails to meet order volumes or faces overproduction, leading to financial losses.
Additionally, unstable order volumes from parent companies exacerbate the issue. The inability to plan production and inventory in advance becomes a significant challenge.
AI GEEKS' Solution
The experts at AI GEEKS proposed a solution: a forecasting system based on the LSTM (Long Short-Term Memory) algorithm. It analyzes historical order data and allows suppliers to anticipate the volumes of components they will need in the future.
The company’s engineers collected data from production sites, including:
- Part numbers.
- Order creation times.
- Supply volumes.
- Planned demands.
The system operates through a centralized internet hub, processing this data with the help of artificial intelligence.
Early Successes
The results are impressive:
- Forecasting accuracy reached a deviation of just 1–2 units per order.
- Suppliers gained the ability to prepare materials in advance, avoiding shortages or overproduction.
- Financial losses associated with planning errors significantly decreased.
What Does This Mean for Businesses?
The forecasting system not only benefits suppliers but also strengthens trust between them and parent companies. AI GEEKS believes this solution marks an important milestone in optimizing supply chains and enhancing overall production efficiency.
"Artificial intelligence is a tool that enables businesses to foresee the future and avoid critical mistakes. We’re proud to have implemented this solution in real-world practice," said Stanislav Kim, Technical Manager at AI GEEKS.
Today, AI GEEKS continues to work on new projects that make manufacturing smarter and inventory management more efficient.