Computational and empirical modeling of additive manufacturing processes

The interest in Additive Manufacturing (AM) processes is constantly increasing due to the many advantages they offer. There is a wide range of AM applications in terms of material, process mechanism and machine type. One important aspect that is common in all the AM processes is the movement of the...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Φωτεινόπουλος, Παναγής
Άλλοι συγγραφείς: Foteinopoulos, Panagis
Γλώσσα:English
Έκδοση: 2021
Θέματα:
Διαθέσιμο Online:http://hdl.handle.net/10889/15518
Περιγραφή
Περίληψη:The interest in Additive Manufacturing (AM) processes is constantly increasing due to the many advantages they offer. There is a wide range of AM applications in terms of material, process mechanism and machine type. One important aspect that is common in all the AM processes is the movement of the scanner head. It is defined by the path sequence followed for the scanning of a layer (scanning strategy) and by the speed of the scanner head over time. Therefore, the movement of the scanner head is of high importance, since it directly affects part quality and build time. The knowledge of the entire progression of the phenomenon is key for the optimization of the path and speed of the scanner head, as well as for other important process parameters. However, the majority of studies simulate either very short portions of the manufacturing time or very small/simple parts, and they are not capable to present a holistic overview of its effects on part quality. In this dissertation, process modeling has been used for the investigation of the effect of the movement of the scanner head (path and speed) on part quality. The principles of model based system engineering (MBSE) were taken into account for the development of the presented framework and models. The existing AM process groups have been classified based on three parameters-axes: temperature of the process, part size and process complexity. This classification points out the impact of each of the two components of the scanner head movement (path and speed) on part quality for the different AM process groups. Viewing the entirety of the AM processes as a whole, a different AM process has been selected for the investigation of each of the scanner head components: the investigation of the effect of scanning strategy on quality has been performed by modeling metal-based AM, while for the effect of scanner speed on quality cement-based AM has been modelled. For the investigation of the scanner path a numerical 3D thermal simulation tool has been developed for the metal-based AM process group (Powder Bed Fusion process). It allows for the extraction of conclusions concerning process parameters and scanning strategy (path) selections by simulating the thermal field, which is much faster in its calculation than the thermal induced thermal stresses and deformations. This is enabled by the Stress Formation Tendency Index (SFTI) that has been developed. The SFTI encapsulates the intensity of the non-uniformity of the thermal field, which is the reason for the development of thermal stresses and deformations. Therefore, ease of use and practicality is ensured for the simulation of the whole manufacturing procedure, even for complex parts, maintaining low computational cost and time making possible the evaluation of alternatives in terms of the scanning strategy selection and of other important process parameters. An empirical modeling approach has been followed for the investigation of the effect of scanner head speed on part quality. In the context of this, a cement-based AM experimental apparatus was designed and developed and two types of two types of extrusion experiments have taken place, linear and rotational. An alternative process-control strategy has been followed, according to which the width of the extruded path is controlled by the ratio of the extrusion speed over the scanner head speed. The advantage of this approach is its higher precision and productivity. The effect of important process parameters on part quality has been investigated; namely the extrusion speed, the ratio of the extruder/scanner head speed and the radius under which the extrusion takes place. The research contribution of this dissertation focuses on the following points: 1. Investigation of the main challenges of AM. 2. Review and categorization of the existing simulation models for AM processes. 3. Process models have been created, under a specific framework, for the investigation of the effect of the movement of the scanner head (path and speed) leading to increased part quality. 4. Development of a modeling framework towards the increase of the effectiveness and of the practicality of simulations for AM processes. 5. Development of a 2D model for metal AM processes capable of real-time simulations (use in machine control). 6. Scanner path investigation: Development of a 3D model of metal-based AM processes towards improving part quality through the evaluation of alternatives in terms of the scanning strategy selection and of other important process parameters. 7. The developed models take into account the exact path of the heat source throughout the process, maintaining the required computing resources at low levels. 8. Development of the SFTI index, which is based on the uniformity of the thermal field and reflects the thermal stresses and deformations that develop during the production of a part. SFTI makes it practically possible, in terms of computational costs, to use modeling to evaluate scanning strategy alternatives towards the minimization of thermal stresses and deformations. 9. Scanner speed investigation: Empirical modeling of cement-based AM process. Design and manufacture of an experimental apparatus for the conduction of experiments towards the investigation of the effect of scanner head speed on part quality. 10. Investigation of an alternative process-control strategy, according to which the width of the extruded path is controlled by the ratio of the extrusion speed over the scanner head speed, offering higher precision and productivity. 11. The theoretical results have been benchmarked using experimental data and commercial simulation packages. 12. Extraction of conclusions concerning the rest of the AM group towards more practical simulations.