In response, KBSI, leveraging their expertise in knowledge representation methods and technologies, focused on developing technologies for capturing and applying the domain knowledge of pricing, costs, and benefits specific to Tinker's production environment. These knowledge representation systems served as the baseline for a number of technologies developed by KBSI to aid the Air Force in automating decision support for equipment purchases, centralizing data concerning equipment life-cycle parameters, and traceability of the cost calculations performed in determining the need for equipment acquisition.

KBSI applied these methods and technologies at the U.S. Army's Corpus Christi Army Depot (CCAD), where depot maintenance managers were experiencing difficulties in identifying the direct and indirect costs associated with activities on the shop floor. CCAD was keen to determine the cost of jobs, based on selected shop activities, in order to anticipate the costs associated with working job batches in CCAD's blade and shot peening shops.

KBSI began by developing, in coordination with shop floor workers and managers, a series of activity and cost models that represented current activities on the shop floor. The models, developed using KBSI's AIØ WIN®, PROSIM®, and SmartCost® tools, included detailed decompositions of the individual shop activities, showing a more granular view of activities and their constraints, cost models, cost rules, and cost analysis spread sheets. Once the shop floor activities and costs were mapped out, KBSI next developed a software interface front-end tool, SmartStat®, that allowed for stochastic simulation of the AIØ WIN® cost model, allowing users to track, for example, the statistical behavior of cost driving attributes like labor over a set of simulation iterations and to evaluate the cost frequencies and ranges. SmartStat® results are presented in a simple to use Excel spreadsheet for closer analysis.

These technologies helped CCAD to drastically improve blade and shot peening shop efficiency, reduce work in progress (WIP), and determine the optimum induction rate of jobs in the shops. The results? In addition to demonstrating the feasibility of integrating these methods and technologies with CCAD's existing systems, this project directly reduced WIP inventory valued at up to $40M from the shop floor, reduced cycle time by 25%, and increased the available capacity of the workforce by 35%.