D-SIMSPAIR is a suite of advanced domain-specific decision-support modules for spare parts demand forecasting and inventory network optimisation in the aviation industry, combining mathematical modelling, simulation techniques and optimisation algorithms with domain expertise, and addresses common pain points in aviation spare parts management:
- The difficulty of assessing risks and prioritizing pre-emptive measures against technical delays and Aircraft-On-Ground (AOG) situations caused by non-availability of spare parts.
- Field behaviour often not being in agreement with relevant planning parameters such as Mean Time Between Unscheduled Removals (MTBUR) and Repair Turnaround Time, leading to investments that are not necessary on the one hand and shortages resulting in flight cancellations on the other hand.
- Challenges associated with designing and delivering competitive component support services that can justify higher cost and price, in an environment where MRO organisations are facing enormous cost pressure from airlines.
D-SIMSPAIR suite combines mathematical modelling, simulation techniques, optimisation algorithms with domain expertise to accomplish all processes involved in aviation spare parts management.
D-SIMSPAIR has been designed for use either stand-alone or on top of an Enterprise Resource Planning (ERP) system. The various D-SIMSPAIR modules can be hosted either by D-SIMLAB or within the customer’s domain.
D-SIMSPAIR suite contains products to provide the user ease with carrying specific tasks in the aviation spare parts management decision process. These products include Dashboard, Component Demand Forecaster, Field Parameter Analyser, Inventory Optimiser and Expendables Settings Analyser.
Business Use Cases
D-SIMSPAIR products can enable a number of business use cases in the aviation spare parts management decision process. These use cases can be stored as pre-set scenarios and can be picked by a user and executed for different data sets on a regular basis. Each of the use cases has predefined reports. The user is also provided with the capability to download raw output data and perform offline analysis before connecting to the underlying ERP and executing the decisions in reality.