Development of an iterative learning controller for polymer based micro-stereolithography prototyping systems

Abstract

Additive manufacturing systems provide fast and accurate fabrication opportunities for micro-scaled structures. Various methods of processing are used for fabrication of different materials. Stereolithography is an important technique for rapid prototyping of photo-reactive polymer based materials. Similar to the other additive manufacturing methods, DLP based projection micro-stereolithography also includes limitations in terms of dimensions, minimum feature sizes and material properties. For advanced and precise micro-sized structure fabrications, process needs to be defined with a complex control scheme. In order to develop a scheme for increasing the fabrication quality, nature of the complex chemical and physical phenomena behind the resin solidification process is investigated. A complete mathematical model for the pixel based photopolymerization process is developed. According to the parameters included in the solidification model, measurements and observations are made for understanding of the resin, optical system and positioning system. Problems of over-curing and under-curing caused by the attenuation nature of the light inside the liquid resin are observed in the simulations made based on the model which is also supported by the previous fabrication experiences for varying structures. These problems creating structural irregularities are dependent on the process parameter of exposure applied on the fabrication surface. An iterative learning based parameter control algorithm is developed for overcoming these errors decreasing the fabrication quality. Continuous fabrication platform movement instead of step-by-step movement which is one of the main features of the established system is used to define a solution. Main fabrication parameter of platform speed is adjusted for each layer according to the error amount calculated on iterations. Use of an optimized gain for parameter control, decreased the dimensional error calculated by the count of the wrongly cured pixels up to 80% in the simulations and 75% in the real life fabrication trials with the application of algorithm. These improvement ratios and proposed algorithm provide a new perspective for the possible future work about online exposure measurement and in-situ parameter control of the stereolithography process.