On the Optimization of the Fiber Reinforced Composites Manufacturing Process with Two Pressure Steps

Dementyev, Vyacheslav B.; Kostritskiy, S.; Petuhov, M.; Torkunov, A. M.

doi:10.1007/978-94-011-2874-2_3

Cited by 2 publications

(1 citation statement)

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“…G2EXP2. J/mol pre-exponential factor A 5.5 X 1022 5.0 X 1022 min-1 tooling thermal diffusivity at 3.71 X 10-7 5.05X10-7 m2/s value (an event which can be represented as a change in an appropriate trend of the viscosity profile), a heuristic rule obtained from previous knowledge of the problem (Dementyev et al, 1992;Loos and Springer, 1983; Kardos et al, 1986).…”

Section: Introductionmentioning

confidence: 99%

Implementation of Model-Based Optimal Temperature Profiles for Autoclave Curing of Composites Using a Knowledge-Based System

Pillai¹,

Beris²,

Dhurjati³

1994

Ind. Eng. Chem. Res.

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The manufacture of composite parts using the autoclave curing process requires the specification of the autoclave temperature as a function of time. It is desired to obtain a part meeting given specifications in the minimum amount of time. A recently developed methodology was used to optimize the process using a mathematical simulation of the cure process. The optimal profile so obtained was implemented on a full-sized autoclave which is interfaced to a proprietary control system running on a Hewlett-Packard computer, using a knowledge-based system (KBS) as a supervisor. In order to account for discrepancies between the simulation and the actual process, we have followed a strategy that uses process trend analysis of the simulation output as the basis for control. The whole process is split up into episodes based on an analysis of the variable profiles. This information is used in conjunction with other knowledge about the system embedded in the KBS to adjust the set point of the autoclave temperature so that the process follows the same "trends" as dictated by the model-based optimization. Using this system, it was possible to guide the cure robustly along an "optimal" path, consistently yielding superior quality parts despite the variability of the raw materials. This procedure allows us to optimize a process independently using even an inexact simulation and apply the optimal profiles obtained therefrom.

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Section: Introductionmentioning

confidence: 99%