Type of Document	Thesis
Author	Li, Jing
Author's Email Address	jingli@eng.fsu.edu
URN	etd-11172003-220306
Title	Development of Integrated Process Design Environment and Statistical Analysis of RTM Process
Degree	Master of Science
Department	Industrial and Manufacturing Engineering, Department of
Advisory Committee	Advisor Name Title Chuck Zhang Committee Chair Okenwa Okoli Committee Member Zhiyong (Richard) Liang Committee Member
Keywords	Robust Design Flow Simulation
Date of Defense	2003-10-23
Availability	unrestricted
Abstract The resin transfer molding (RTM) process has been used in the composite industry for decades. However, several issues still exist and impede its wide applications. Some design tools for RTM parts have been developed but a more efficient design environment is lacking. Race-tracking is a common phenomenon that makes prediction in actual production difficult and makes current deterministic optimal tooling design unrepeatable. This thesis integrates flow simulation and cost analysis modules together with database management system (DBMS) providing a prototype of the integrated design environment for RTM processes. Preform permeability, especially race-tracking permeability that significantly affects not only simulated but also experimental results, was the factor being investigated. This thesis introduces a statistical approach utilizing statistically distributed variables to explain the race-tracking permeability values. One-dimensional flow experiments were conducted to obtain the permeability values. Three types of distribution (gamma distribution, Weibull distribution and lognormal distribution) were chosen as candidates. Experimental data were fitted for the three distributions. A goodness-of-fit test was performed to find the one that best describes the experimental data. Taking into account the fact that the severe levels of race-tracking can be represented by statistically distributed variables, this thesis proposes an optimization approach to minimize the sensitivity of the mold design to uncertainty of race-tracking permeabilities by choosing the appropriate locations of gates and vents (robust tooling design). A sensitivity that indicates the process robustness was defined as objective and evaluated by RTMSim software both for 2D and 2.5D geometry. With the conclusion that the ratios of race-tracking permeability over average values can be described by Weibull distributed variables, a random number generator was employed to generate the input race-tracking permeability data for obtaining values of the objective. Locations of vents were determined via the assumption that vents should be assigned at the locations where flow ends to avoid dry spot formation. Locations of gate were optimized from most possible locations.
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