The rapidly changing manufacturing landscape requires re-optimisation to ensure efficient and agile operations while adapting to evolving logistical demands. Opturion's latest efforts towards re-optimisation progress for a manufacturing company yield various options, focusing on identifying and utilising cancelled loads available for pickup. We are also examining gaps in crane utilisation, predicting potential time slots for load pickups and anticipating cancellations. Our proactive approach helps our customer optimise their resource allocation and minimise idle times, which enhances operational efficiency.
Before that, we have taken a comprehensive approach to re-optimisation. This includes strategically reassigning jobs from drivers to maximise resource utilisation and assigning each task to the most efficient and available driver. Additionally, we have conducted workshops focused on modelling and what-if scenarios to incorporate new cost models and constraints into our optimisation framework.
Furthermore, we have initiated workshops for functional specification, laying the groundwork for incorporating long-term planning using Linear Programming (LP). This approach provides a holistic view, enabling us to strategise for immediate needs and the medium and long-term, specifically addressing crane movements. We have also conducted workshops on longer-term planning, utilising tools such as Excel to simulate and analyse different scenarios.
Our planning efforts have expanded to include transport between zones, which allows us to run all zones together seamlessly. We have also integrated rail transport into the optimisation strategy, introducing another unloading point to enhance the flexibility and scalability of our logistics network. To ensure precision, we have defined exact requirements for fatigue management, driver swapping, and queuing at sawmills while maintaining the well-being of the customer's workforce and the smooth flow of operations.
These enhancements not only streamline customer's logistics network but also bolster precision, ensuring the optimal utilisation of resources while prioritising the well-being of their workforce and maintaining seamless operational flow. We conducted multiple iterations of what-if planning executed in Excel at the interception of these enhancements. This iterative approach allows us to refine and perfect our optimisation models, making the logistics operations more robust and responsive to the ever-changing dynamics of the manufacturing landscape.
