G-nous supports a world-leading multinational tire manufacturer to perform industrial research and deliver process optimization solutions.
In the context of industrial manufacturing, the inefficiencies related to the storage and transport of semi-finished products within production cycles is the main cause of cost increase and income reduction.
A correct logistic programming enables cost reduction and production increase, with the same resources and instruments.
The project demonstrates how optimized logistic processes come from data science, business process analysis and process constraints identification.
The customer needed to optimize the interoperational stock designed for safety storage of semi-finished products in their manufacturing line.
G-nous Tech applied numerical simulations to replicate production processes and optimize the manufacturing cycle.
The project involved the evaluation of the maximum possible reduction of storage in order to maintain the same stock-out probability or risk and simultaneously reduce the space allocated for semi-finished products.
As a result, the service level of production is maintained by reaching a trade-off between the storage maintenance costs and income loss caused by possible stock-out.
G-nous tech performs the statistical data analysis of production and the design of the optimal safety stock space.
Those results are achieved by processing the production rate variability between the upstream and downstream production lines, comprising the interoperational storage.