Forecast/ABC: A Predictive Activity-Based Cost Modeling and Analysis Agent Network

Period of Performance: 05/01/1998 - 02/01/1999

$100K

Phase 1 SBIR

Recipient Firm

Intelligent Systems Technology, Inc.
1212 Victoria Ave
Los Angeles, CA 90066
Principal Investigator

Research Topics

Abstract

The Phase I SBIR effort is concerned with development an Activity-Based Cost (ABC) modeling and analysis tool based on autonomous agent technology to improve cost forecasting for complex manufacturing systems. Historically, ABC has been employed as a descriptive mechanism for understanding the sources of costs based on activities that generate the costs, and not on the traditional material-labor-overhead (MLO) categories. However, with recent advances in modeling, simulation and autonomous with recent advances in modeling, simulation and autonomous agent technologies, the ability to model and simulate complex systems using a collection of simple, autonomous software agents that can be deployed concurrently has become entirely feasible. The Phase I effort is directed to creating a system concept , implementation architecture, and Phase II implementation plan for an autonomous agent-based ABC forecasting tool. The payoffs of such a tool are dramatic reduction in manufacturing costs and cycle time through: (a) early detection of non-value-added activities and waste; and (b) various ABC streamlining optimization strategies. Above all, given the diagnostic and predictive nature of the tool, managers and executives will be able to: (a) gain better control of their processes through increased visibility into the sources of cost; and (b) maintain such control because of the diagnostic predictions made possible by the tool.