SBIR-STTR Award

The vision is to provide decision-makers with effective, fast, and inexpensive analysis tools to answer "What-If" and "What-Should" questions about manufacturing systems. Value Stream Mapping (VSM) is a modeling methodology with widespread contemporary use in manufacturing, and our strategy is to start with VSM as a deployment beachhead for the eventual deployment of a more generic manufacturing system modeling and analysis tool. In Phase 1, we propose to add modeling rigor and computational analysis to VSM; our goal is to demonstrate the feasibility of using Value Stream Maps to answer routine value stream questions about throughput, capacity, cycle time, and inventory using automated generation of discrete-event simulation models. A Phase 1 demonstration will start from the VSM tool environments of Microsoft Visio and Excel, and automatically generate discrete-event simulation models in a COTS language and tool.

The vision is to create enterprise-grade software tools supporting the design and improvement of manufacturing systems, tools that can provide answers to fundamental business questions about product selection, resource planning, scheduling, and logistical control – quickly, accurately, and with adequate consideration of risk. Objectives accomplished in Phase I included adding formality and rigor to a widely-adopted manufacturing system modeling language, delineating scope and boundary limitations for language extensions, and demonstrating automated formulation of computational analysis to answer routine questions about expected cycle time, throughput, capacity, and inventory levels. Phase II objectives include maturing behavioral and control definitions in reference models, integrating SysML-language reference models with software implementations, formalizing system – analysis integration, and extending the manufacturing system modeling language to express components of resource planning and scheduling problems. At the conclusion of the work we will have a software tool that we can demonstrate to potential customers and test within their production environments.