In order to improve the processing efficiency and production quality of Taiwan's manufac-turing products, and assist Taiwan's manufacturing industry to strengthen its process optimiza-tion capabilities, the National Science and Technology Council (NSTC) actively promotes the re-search and development of smart manufacturing innovation technologies. The teams from Pro-fessor Lo, Yu-Lung, Department of Mechanical Engineering at National Cheng Kung University, have developed the "Optimization System for Smart Laser Machining Process", which can help the manufacturing industry greatly reduce the time and material costs spent on repeated test-ing before mass production and processing.

Laser processing technology is widely used in 3D metal printing in the defense/aerospace industry, laser welding of heterogeneous alloys in the automotive industry, and Through Silicon Via (TSV) process of wafers in the semiconductor industry. Professor Lo's team cooperated with many professors from National Cheng Kung University, Kaohsiung University of Science and Technology, and Southern Taiwan University of Science and Technology to develop a set of "op-timization system for smart laser machining process". To achieve process optimization and im-prove product yield with application value, we develop simulation models to optimize process parameters, a monitoring system in manufacturing process, and a feed-back control system to adjust laser power according to monitoring results. It can be linked to domestic machinery re-lated companies such as: DIGITAL-CAN TECH, SMART LONG TECHNOLOGY CO., ANJI TECHNOL-OGY CO., SYNTEC CO., JUMBO CO., YULON MOTOR CO., RATC TECHNOLOGY CO., TONGTAI CO., and CONTREL CO., etc.

The application benefits of its optimization system are as follows:
1. During 3D printing, by precisely controlling the laser power and scanning mode, the sys-tem can optimize the structural strength of the workpiece while performing a higher scanning speed, thereby improving production efficiency and application prospects.
2. During laser welding of heterogeneous alloys, by optimizing laser welding parameters, the system can achieve high-strength welding joints and reduce material deformation and welding defects; bringing more efficient laser welding applications to the automo-bile manufacturing industry.
3. By optimizing the laser machining parameters with the green dry etching process, the system can achieve more accurate silicon wafer deep drilling processing, while reducing production costs and improving production efficiency for green manufacturing in the semiconductor industry, in order to achieve the concept of sustainable management.

In the production process, the optimization process system combined with laser processing technology, parameter optimization analysis model, monitoring and feedback control system can help determine the optimization range of energy saving and carbon reduction, and achieve low energy consumption and low carbon emission under the quality conditions so as to achieve green manufacturing.

On the whole, the optimization system of smart laser machining process can add value to the domestic 3D metal printing system, assist domestic automotive battery suppliers to upgrade their technology, and deepen semiconductor perforation laser processing technology, which can bring benefits to the manufacturing industry. A more efficient and precise green manufacturing method will open up a new blue ocean market. It is of great significance to optimize product quality, shorten delivery cycle, save cost resources and improve production efficiency, and is crucial to improving the economic competitiveness of Taiwan's industrial circles. Professor Lo's team expects this system to be widely used in the manufacturing industry. Its key technology can lead the green technology elements of next-generation mechanical processing, advance towards the goal of green manufacturing and carbon reduction, promote eco-friendliness and realize the goal of sustainable manufacturing.

References:
3D Metal Printing:
[1] T.N. Le, Y.L. Lo, “Effects of sulfur concentration and Marangoni convection on melt-pool for-mation in transition mode of selective laser melting process,” Materials and Design, 2019.
[2] H.C. Tran, Y.L. Lo, “Heat transfer simulations of selective laser melting process based on vol-umetric heat source with powder size consideration,” Journal of Materials Processing Technolo-gy, 2018.
[3] H.C. Tran, Y.L. Lo, “Systematic approach for determining optimal processing parameters to produce parts with high density in selective laser melting process,” The International Journal of Advanced Manufacturing, 2019.
[4] H.C. Tran, Y.L. Lo, H.C. Yang, H.Z. Xiao, F.T. Cheng, T.H. Kuo, “Intelligent Additive Manufactur-ing Architecture for Enhancing Uniformity of Surface Roughness and Mechanical Properties of Laser Powder Bed Fusion Components,” IEEE Transactions on Automation Science and Engineer-ing, 2022.
 

Laser Dissimilar Welding:
[1] N.T. Tien, Y.L. Lo, M.M. Raza, C.Y. Chen, C.P. Chiu, “Optimization of processing parameters for pulsed laser welding of dissimilar metal interconnects,” Optics & Laser Technology, 2023. 
 

Laser TSV:
[1] K. Dileep, Y.L. Lo, C.H. Yang, “Simulation study and parameter optimization of laser TSV us-ing artificial neural networks,” minor revisions to Journal of Materials Research and Technology, March 2023.

Media Contact：
Tien Shun Kuo
Program Manager
Department of Engineering and Technologies
National Science and Technology Council
Phone：(02) 2737285
e-mail：tskuo@nstc.gov.tw