The Business need
Safran Landing Systems is the world leader in aircraft landing and braking systems. Their medium machine manufacturing process specialises in a diverse array of product families requiring a range of unique and bespoke machines. These factors alongside static data, complex routings and a priority list planning approach bring a level of scheduling complexity to the operations.
Currently, scheduling is a predominantly manual process with support from a bespoke manufacturing execution system (MES) focused more on paperless execution rather than intelligent scheduling and execution. This setup can lead to delays, increased inventory issues and inefficiencies and a resource-heavy shop floor unable to react quickly to priorities.
Safran is interested in developing a dynamic scheduling system that can provide an intelligent rules-based system capable of reacting to changing customer demand. The solution needs to be scalable and ultimately assist the workforce in reducing the complexity around planning whilst understanding impact and consequences. An agile and adaptable solution to increase scheduling efficiency.
The Solution provided
Our scalable TotalControlPro solution ultimately assisted the workforce in reducing the complexity around planning whilst understanding impact and consequences. Overall, from the data and evidence collated, Planning and Scheduling will be a significant contributor to improving industrial productivity by more than 30% by 2030. Evidence points to recouping more than 30 minutes of lost production capacity per shop floor operator per day (representing the recovery of over 10,000 lost production hours per year for a typical SME), a 10% improvement in productivity, and a 15% reduction in downtime.
The Impact and Results
Built & deployed a cloud-based Adaptive Planning engine that optimises the resources and output of the Safran Prismatic parts.
Demonstrated the value of real-time data and MACHINE LEARNING technology in optimising the planning and execution of workload through a series of complex processes.
Independently supported Return on Investment business case, notably;
- 10% improvement in OLE & OEE
- improve on-time-delivery, and significantly reduce inventory costs
- Opportunity to generate a 10x ROI, & a project payback within 2 full production months