볼트형 피에조 센서를 활용한 피어싱 펀치의 얼라인먼트 불량 검출에 관한 연구 = A study on the detection of misalignment between piercing punch and die using a bolt-type piezo sensor

다국어 초록 (Multilingual Abstract)

Piercing is the process of shearing a circular hole in sheet metal, whose high shear force makes it difficult tosecure the durability of tools. In addition, uneven clearance between tools due to poor alignment of the piercing punchcauses accelerated die wear and breakage of the tool. This study reviewed the feasibility of in-situ determining alignmentfailure during the piercing process by analyzing the signal deviation of a bolt-type piezo sensor installed inside the toolwhose alignment level was controlled. Finite element analysis was performed to select the optimal sensor location on thepiercing tool for sensitive detection of process signals. A well-aligned piercing process results in uniform deformation inthe circumferential direction, and shearing is completed at a stroke similar to the sheet thickness. Afterward, a sharpdecrease in shear load is observed. The misaligned piecing punch leads to a gradual decrease in the load after themaximum shear load. This gradual decrease is due to the progressive shear deformation that proceeds in thecircumferential direction after the initial crack occurs at the narrow clearance site. Therefore, analyzing the stroke atwhich the maximum shear load occurs and the load reduction rate after that could detect the misalignment of the piercingpunch in real-time.

참고문헌 (Reference)

1 J. Stahlmann, "Understanding and improvement of industrial production how technology paves the way for productivity" 2017 : 109-117, 2017

2 X. Li, "Transient dynamical analysis of strain signals in sheet metal stamping processes" 48 : 576-588, 2008

3 T. Altan, "Sheet metal forming :Rrocess and applications" ASM International 2012

4 S. Y. Kim, "Monitoring of process and tool status in forging process by using bolt type piezo-sensor" 15 : 542-549, 2018

5 Y. D. Chethan, "Machine Vision for Tool Status Monitoring in Turning Inconel 718using Blob Analysis" 2 : 1841-1848, 2015

6 H. Kagermann, "Final report of the Industrie 4. 0 working group" ACATECJ 1-82, 2013

7 H. Chelladurai, "Development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis" 37 : 471-485, 2007

8 W. H. Hsieh, "Application of backpropagation neural network for spindle vibration-based tool wear monitoring in micro-milling" 61 : 53-61, 2012

9 W. Rmili, "An automatic system based on vibratory analysis for cutting tool wear monitoring" 77 : 117-123, 2016

10 H. V. Ravindra, "Acoustic emission for tool condition monitoring in metal cutting" 212 (212): 78-84, 1997