Abstract
AbstractThe main goal of this paper was to examine whether image processing can be an effective tool in automatic quality control systems for furniture manufacturing, at least in cases where delamination is a key problem. Image processing turned out to be a very effective way of delamination factor monitoring. Moreover, the research analyzed the quality effect of up or down milling of melamine-faced MDF. The delamination factor increased significantly with increasing tool wear. However, the increase was not very regular. The experimental data showed that up milling had a significant advantage over down milling.
Publisher
Springer Science and Business Media LLC
Subject
General Materials Science,Forestry
Reference6 articles.
1. Darmawan W, Azhari M, Rahayu IS, Nandika D, Dumasari L, Malela I, Nishio S (2018) The chips generated during up-milling and down-milling of pine wood by helical router bits. J Indian Acad Wood Sci 15(2):172–180. https://doi.org/10.1007/s13196-018-0223-4
2. Davim P (2013) Wood machining. John Wiley and Sons, New York
3. Kurek J, Świderski B, Jegorowa A, Kruk M, Osowski S (2017) Deep learning in assessment of drill condition on the basis of images of drilled holes. In: Eighth International Conference on Graphic and Image Processing (ICGIP 016), Tokyo, Japan, pp 1–7.
4. Laszewicz K, Górski J, Wilkowski J (2013) Long-term accuracy of MDF milling process-development of adaptive control system corresponding to progression of tool wear. Eur J Wood Prod 71(3):383–385. https://doi.org/10.1007/s00107-013-0679-2
5. Lemaster RL, Lu L, Jackson S (2000) The use of process monitoring techniques on a CNC wood router. Part 2. Use of vibration accelerometer to monitor tool wear and workpiece quality. For Prod J 50(9):59–64
Cited by
11 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献