Title :Modeling and Analysis of Dimensional Variation in Multi-Station Multi-Stream Manufacturing Processes

Sponsor : NIST-ATP

Collaborators: R. Kumar, J. Kong, Y. Zhou, S. Gogoneni (Dimensional Control Systems)

SOVA state space model has been developed for modeling analysis, prediction and synthesis on product design at early design stage. Current SOVA model considers multi-station process configured as a single stream, i.e. a single assembly line. However, to adapt rapid market changes, most of current manufactures already use multi-station and multi-stream assembly system configuration to reduce the lead-time to market of a product. That means several parts are concurrently manufactured along different subassembly streams. We call this manufacturing method as multi-stream manufacturing. In this research, we will introduce a methodology of modeling and analysis dimensional variation for multi-station and multi-stream assembly system configurations. The objective is to integrate the configuration of assembly process and current SOVA model together such that we can analyze, predict, and synthesis dimensional variations with considering interactions between assembly streams. The methodology of building this model includes (1) constructing the information of assembly configuration to represent an assembly process by using incidence matrix and (2) modeling variation propagation in multi-station and multi-stream manufacturing process by integrating current SOVA model with information of assembly configuration (incidence matrix). By using this methodology, we can model the dimensional variation of a product with considering the relationship between overall configuration of assembly process and variation sources at each assembly stream. The model is validated through a case study of Warren truck by using 3DCS Analyst simulation software. This case study helps us having a better understanding of why and how using multi-stream SOVA model and allows us to have successful implementations of similar problems in practice.