Large airlines tie up millions of dollars each year holding inventory of excess parts in order to support the unplanned replacing of parts. They spend millions of dollars each year moving those parts from one maintenance location to another in order to ensure that they have the parts on hand when they have to perform maintenance on their planes.
The stocking levels for the spare parts were often determined based on actual usage requirements and limited forecasts. Not having the needed part on hand in the right maintenance location caused out of stock conditions which grounds aircraft that cost the airlines money, negative impacts consumer experiences, and negatively impacts the reliability numbers that the airlines are measured against. In order to limit this, airlines hold excess inventory which costs them millions of dollars a year. Without analytical tools, there was no ability to see trends in part usage aside from raw historical use. The airline was also not able to determine if maintenance should be done earlier than scheduled when the part and the plan were in the same location.
How We Solved It
Trillium was brought in to manage the requirements gathering, data mining, design and implementation of new Supply Chain Software and predictive analytics solutions and then coordinate the activities of 6 best of breed consulting companies to implement these new tools. Trillium also designed and developed tools to simplify the integration of these new tools into the airlines legacy environment. In addition, Trillium designed and developed key reporting components to support the clients decision making process.
- Management of over 450,000 bin locations is no longer a manually intensive and reactive activity.
- Procurement of parts is now done objectively using forecasts with measurable error rates allowing departments to make decisions based on rel
- Annual carrying cost for parts was reduced by over $100 million
- Shipping costs were reduced by over $50 million a year transferring parts between maintenance facilities.
- Tight integration with the existing legacy system reduces the risk of unnecessary overstocking and stock-outs.