Control of Thermal Distribution in Additive Manufacturing

Additive Manufacturing is a rapidly growing industry. However, the defects generally occurring in parts built through Additive Manufacturing have hindered its way towards a reliable technology for mass production. Most of these defects generally occur through residual stresses building up in the parts during the process. Complex machinery is available which ensures defect free parts but it comes with a trade-off for cost. The aim of this study is to provide a potential cost-effective solution to address the defects and issues arising due to uneven thermal distribution in the AM built parts. A detailed study about the basic understanding of the consolidation mechanism of the Powder Bed based Additive Manufacturing processes and Induction is discussed. The use of induction to selectively control the thermal distribution in these manufacturing process is proposed. Preliminary stage simulations and experiments are carried out to validate the proposal and its scope of application is discussedMaster of Science in EngineeringAutomotive Systems Engineering, College of Engineering & Computer ScienceUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/145492/1/Master's Thesis Copy Formatted (2).pdfDescription of Master's Thesis Copy Formatted (2).pdf : Thesi

Microstructure Control and Property Prediction in Inductively Coupled Selective Laser Melting

Metal Additive Manufacturing has earned significant industrial and research inclination in the recent years given faster production times and less wastage of material as compared to subtractive or traditional manufacturing. However, issues and concerns regarding quality, and process control, repeatability and consistency with Additive Manufacturing is still under works. With more demand for tailored manufacturing suitable for specific end-applications, controlling physical properties by modifying process parameters or by inclusion of complimentary processes to Additive Manufacturing has been well known. This proposed study aims at delivering an effective way of addressing the thermal distribution control in a Powder Bed Fusion process for Selective Laser Melting of 316 Stainless Steel. Selective heating of the powder bed through a co-axially integrated induction system with a conventional laser setup is proposed based on literature survey, simulation data and baseline experiments. A system suitable for the proposed concept is designed, fabricated, and assembled. Extensive experimental trials are conducted to study the effect of the auxiliary heating source on the microstructure and the variation in physical properties of the built deposits. Effect of controlling the cooling rate of the melt pool on the resulting mechanical properties is reviewed and discussed. Machine Learning to help predict physical properties and control the process flow given the complex nature, is proposed through a Digital Twin. Analytical data generated through the depositions is used to model the training and testing of the Digital Twin and a framework for a more comprehensive study of the same is laid. A proof of concept demonstrating the use of induction in controlling the microstructure is achieved as well as initial efforts towards the Digital Twin are also successfully achieved.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/171953/1/Aniket C Jadhav Final Dissertation.pdfDescription of Aniket C Jadhav Final Dissertation.pdf : Dissertatio