The Most Sophisticated Availability Based Optimization
Availability Based Optimization based on DoD ‘RBS’ Readiness Based Sparing principles and methods determines the lowest-cost stocking strategy that attains targeted system availability.
It can be based upon standard configurations of an asset or unique identifiers like tail numbers. The ABO model can comprehend mission duration, causality such as environmental factors, activity metrics such as hours or cycles, and sources of resupply including cannibalization. The resulting model uses complex algorithmic optimization to set inventory strategy, and the sustainment planning engine makes it a reality.
PTC’s solution supports a virtually unlimited number of items, echelons, and levels of indenture. The logic allows mission profiles, their causal attributes such as environmental conditions, and the sustainment infrastructure and its resupply capabilities to define what material is needed when and where.
The tactical sustainment process coordinates maintenance schedules and a vast array of forecasting models to develop a comprehensive view of all demand sources. Supply is planned based upon a “use what you own” philosophy – looking first to replenish or rebalance from stores; then repair, upgrade or overhaul defective or out-of-revision parts; then cannibalize assets where allowed; and lastly acquire new material.
This holistic model reconciles supply and demand with missions and maintenance, resulting in maximum availability at minimum budget. Configurable dashboards and a Service Knowledge module complement the planning with insight into issues and opportunities.
Plan Material as Effectively as You Plan Your Missions
The missions that drive activity for weapons systems and the system availability targets are also the principle drivers of parts consumption. Increased asset utilization leads to more scheduled maintenance, more unscheduled removals and increased random part failures. Historically, parts planning has been overly reliant on the historical record instead of a view to the future.
Availability Based Optimization (ABO) determines the lowest-cost stocking strategy that will achieve targeted system availability. It can be based upon standard configurations of an asset or unique identifiers like tail numbers. The model can comprehend mission duration, causality such as environmental factors, activity metrics such as hours or cycles, and sources of resupply including cannibalization. The final model uses complex algorithmic optimization to set inventory strategy, and the sustainment planning engine makes it a reality.
Mission Attributes Used to Drive the Material Plan for the Warfighter
PTC's A&D solution portfolio incorporates all scheduled and projected what-if maintenance events. PTC solutions also accept and/or calculate probabilistic bills of material (BOMs) to represent required and conditional parts.
Operational performance dashboards can track overall system availability, non-MICAP due to parts, maintenance delays and any other key metric by job function.
Synchronization of Missions, Maintenance, and Materials
PTC's A&D solution portfolio is a highly focused, technology toolset with the following enablers for optimal weapons system availability:
- Best-in-class ABO parts optimization including causality and variable duration
- Multi-echelon, multi-indenture parts optimization logic tuned to mission profiles
- Incorporation of maintenance schedules and probabilistic bills of material (BOMs)
- Optimized utilization of repairable assets
- Forecasting, optimized stocking levels, and material management by contract
- PBL dashboards displaying operational performance data
PTC Solutions Achieve Weapons System Availability Targets Based on Budget
Defense organizations have struggled to synchronize mission planning with the maintenance and materials required to support steady-state operations through up-tempo and back-to-normal operations. A lack of synchronization either compromises system availability or increases required parts inventories or both.
PTC's Availability Based Optimization creates a single unified demand plan. This capability incorporates the complete roster of scheduled maintenance events, and couples it with sophisticated forecasting for unscheduled removals and random failures. State-of-the-art, availability-based modeling techniques yield an optimized inventory strategy centered on variable mission profiles at the lowest cost – implemented through an exception-based process for maximum depot and logistics productivity.