MP2O helps depot managers improve agility, throughput, and system responsiveness despite ever-changing demands, priorities, and resource constraints. MP2O models bring focus to essential aspects of the MRO system, expanding managements’ understanding of the system and their ability to rigorously test system designs.
The increasing volume and pace of Air Force operations worldwide add to the strain on an already aging fleet and the already taxed sustainment enterprises tasked with keeping that fleet in the air. Air Logistics Centers (ALCs), responsible for aircraft maintenance, repair, and overhaul (MRO), are under pressure to reduce the number of aircraft on station at any given time, speed turnaround, and meet on-time delivery commitments—in other words, to maximize the number of aircraft that are available for duty just when the demand for depot overhaul work is sharply increasing. The only way to achieve this goal is to increase the speed of the MRO process. Given the inherent variability of the MRO process and the variety of resource types that must be managed—parts, manpower, equipment, funding, facilities, etc.—this is a particularly challenging goal.
The Collaborative Analysis and Knowledge Exploration (CAKE) initiative, now in Phase II, is designing a semantic framework that supports information discovery, sense making, and presentation in dynamic, collaborative environments. In Phase II, KBSI is validating the capability to create semantic knowledge from multi-modal text and image data feeds using semantic tagging and collaborative visual approaches.
The ATPD technology is combining new machine learning techniques with advanced rule based methods for automated data utilization pattern discovery. The technology allows users to monitor information use, discover use patterns, and develop ontology models of these relations and patterns.
This capability enables users to monitor information use across systems, discover usage patterns, analyze patterns for potential new (and useful) concepts and relations, and offer intelligent assistance to enterprise knowledge modelers about the integration of newly learned concepts into evolving reference knowledge models.
The FEAST technology uses an innovative methodology for dynamic scenario generation and adaption in simulation-based environments for mission operations training. The technology’s knowledge discovery and automated reasoning methods let you evolve scenario design knowledge over time.
KBSI began by establishing the requirements for a dynamic scenario generation for individual and team learning in simulation-based environments. This requirements building will utilize the Air Force’s Mission Essential Competencies (MECs)-based model as a means for enabling effective transformation from mission based training to competency based training in DMO training environments.
The XFMR solutions concept allows for interactive critical chain re-sequencing, constraint violation identification, and automated critical chain plan option generation. These capabilities are transforming Air Logistics Center (ALC) operations to warrior-centric, highly adaptive, and more efficient sustainment enterprise activities.
The Transformation in Maintenance and Repair (XFMR, or “transformer”) research effort identified the critical method and tool technology voids that must be addressed in transforming Air Logistics Center (ALC) operations to warrior-centric, highly adaptive, and more efficient sustainment enterprise activities. Central to addressing these voids is a set of key technologies that support a critical chain program management (CCPM) approach based on Goldratt’s Theory of Constraints (TOC). The XFMR solution concept includes a set of Critical Chain deconfliction tools that provide critical chain re-sequencing, constraint violation identification, and automated and optimized critical chain plan option generation.
ProPlan™ 21 provides technology for the rapid definition, creation, and editing of constraint based MRO plans, enabling advanced plan analysis and plan execution for depot management decision support across all production echelons.
Key to the responsiveness of Air Logistic Centers (ALC), the hub for maintenance, repair, and overhaul of Air Force aircraft, is planning. Responsiveness is a particularly acute need given the increased pace of Air Force operations worldwide, and ALCs are under pressure to reduce the number of aircraft on station at any given time, to speed maintenance, repair, and overhaul (MRO) turnaround, and to meet on-time delivery commitments despite significant variability in work content, component part reliability, and replacement part acquisition lead-time—all while continuing to maintain consistently high standards of quality.