Logistic optimization through custom algorithms
Highlight
The analysis conducted in collaboration with a leading tire manufacturer yielded impactful optimisation solutions for the buffer storage and transport of semi-finished products within the production processes.
Scenario
In the context of industrial manufacturing, minimising storage and transport inefficiencies in production cycles brings cost savings and productivity increases. So the manufacturer faced several challenges:
- improper utilisation of storage space, leading to increased warehousing costs
- inefficient transport routes and schedules for semi-finished products between production stages
- excessive handling of materials, resulting in increased labour costs and potential product damage
- difficulty in accurately tracking inventory levels of semi-finished products
- integrating the company's existing resources and database with advanced data science methods resulted in optimised storage allocation.
Solution
Using data acquired from the company's internal database, data science techniques and numerical simulations were employed to streamline logistics processes and identify operational constraints. Analysis of the data demonstrated the potential to optimise safety stock storage, balancing space reduction while maintaining the same level of production service indexes. Consequently, it became possible to achieve more cost-effective production rates.
Outcomes
The data-driven analysis and simulation approach produced several key advantages for the company:
- Concrete evidence of the optimal economic production quantity, allowing for more informed decision-making
- Efficient storage management, reducing storage needs while maintaining equivalent service indexes
- Unlocked data potential, uncovering hidden insights that drive operational improvements
- Enhanced production continuity, reducing the risk of production disruptions caused by lack of semi-finished products
- Bottleneck identification within the production line, enabling targeted improvements and increased overall efficiency
G-nous role
G-nous Tech applied its technical expertise in data science, analytics and land industrial logistics to achieve output which improved the storage allocation of the interoperable buffer.