An efficient scanning algorithm for improving accuracy based on minimising part warping in selected laser sintering process

ABSTRACT

In the selective laser sintering (SLS) method, layers of powder are scanned by a laser beam and sintered. The thermal gradients created by laser heating and the subsequent cooling of the sintered sections results in thermal stresses and part warping in the final part. Thermal gradients are dependent on the scanning algorithm, in particular, the scan vector length. In this work, an efficient scanning algorithm for the SLS process is presented with the aim to minimise the part warping in the final part due to thermally induced residual stresses, while maintaining the production time at a minimum. The proposed algorithm is implemented in a finite element simulation and scanning parameters including the number of offsets and scanning length are optimised at constant laser parameters and chamber conditions. The FE model is verified by testing a few samples on SLS machine and comparing the parts made by the proposed algorithm with those made using conventional scan algorithm is the same as parallel-line scan algorithm. It is shown that part warping in the parts made by the proposed algorithm is reduced by up to 35% while the production time, part accuracy and surface properties are improved.

KEYWORDS:

• Additive manufacturing
• selective laser sintering
• scanning algorithm
• hatching pattern
• part warping
• finite element modeling

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Ahmad Manshori Yeganeh received the M.Sc. degree in Mechanical Engineering from Sharif University of Technology, Tehran, Iran (2016). He is currently a research assistant in the Precision Manufacturing Lab at Sharif of University of Technology. His main research interests are Additive Manufacturing processes and Finite Element Simulations of manufacturing processes.

Mohammad Reza Movahhedy received the Ph.D. degree in Mechanical engineering from the University of British Columbia, Vancouver, Canada (2000). He is presently working as a Professor in Department of Mechanical Engineering at Sharif University of Technology, Tehran, Iran. His major research interests are Hybrid machining Processes; Ultrasonic and Laser-assisted Machining Laser Processing; Additive Manufacturing, Laser Cladding Mechanics of Machining Processes Machine Tools Dynamics FEM Simulation of Metal Cutting/Forming Processes Experimental Modal Analysis Computer Aided Tolerancing.

Saeed Khodaygan received the Ph.D. degree in Mechanical engineering from Sharif University of Technology in Iran (2011). He is currently working as an Assistant Professor in the Department of Mechanical Engineering at Sharif University of Technology, Tehran, Iran. His major research interests are Optimal Multidisciplinary Design, Computer-aided Tolerance Design, Design for Additive Manufacturing, Measurement Systems and Instrumentation, Mechanical System Identification, Applications of Artificial Intelligence to Engineering.