Citation: Jegorowa, A.; Kurek, J.; Kruk, M.; Górski, J. The Use of Multilayer Perceptron (MLP) to Reduce Delamination during Drilling into Melamine Faced Chipboard. Forests 2022, 13, 933. https:// doi.org/10.3390/f13060933 Academic Editor: Milan Gaff Received: 17 May 2022 Accepted: 13 June 2022 Published: 15 June 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Article The Use of Multilayer Perceptron (MLP) to Reduce Delamination during Drilling into Melamine Faced Chipboard Albina Jegorowa 1 , Jaroslaw Kurek 2 , Michal Kruk 2 and Jaroslaw Górski 1, * 1 Institute of Wood Science and Furniture, Warsaw University of Life Sciences, Nowoursynowska 159, 02-787 Warsaw, Poland; albina_jegorowa@sggw.edu.pl 2 Institute of Information Technology, Warsaw University of Life Sciences, Nowoursynowska 159, 02-776 Warsaw, Poland; jaroslaw_kurek@sggw.edu.pl (J.K.); michal_kruk@sggw.edu.pl (M.K.) * Correspondence: jaroslaw_gorski@sggw.edu.pl Abstract: Drilling into melamine-faced-wood-based panels is one of the most common processes in modern furniture manufacturing. Delamination is usually the main and the most troublesome quality defect in this case. A lot of scientific studies draw the conclusion that the progress of tool wearing during the cutting of wood-based materials is the key problem. Therefore, tool condition monitoring and the replacement of worn tools at the right time is the most useful and common (in the industrial practice) way to reduce delamination. However, the automation of this process is still a problem due to various issues. There is yet no commercial (even prototypical) offer for the furniture industry in this regard. For this reason, it is considered advisable to try to use the multilayer perceptron (MLP) algorithm to automatically identify a drill’s condition during drilling in a laminated chipboard. It has been established that, for practical purposes, it is important to distinguish between the three different classes of tool conditions, which can be conventionally described as “Green” (keep working), “Red” (implicitly stop and replace) and “Yellow” (warning signal—stop and replace if you want to avoid deterioration in cutting quality). To register the signals generated in the cutting zone and those constituting the basis for the identification of the tool condition in the “on-line” mode, the following elements were used: contact sensor of acoustic emission, accelerometer for vibration, two-component force gauge and a microphone. The classification effects (with an overall accuracy above 70%) were ultimately fairly decent but slightly worse than those of the classification algorithms tested earlier (i.e., “nearest neighbors” or “support vector machine” algorithms). The most troublesome, however, is the fact that serious errors (mistakes between “Green” and “Red” classes) were occasionally noted (for about 1% of the analyzed cases). Keywords: MLP classifier; tool condition monitoring; drilling; laminated chipboard 1. Introduction It is hard to imagine modern furniture manufacturing without drilling into melamine- faced-wood-based panels. It is a well-known fact that the machining of any composite material generates quality problems (defects), mainly delamination. Problems of this kind also arise during the machining of laminated panels commonly used for furniture or interior fitting manufacturing [1–4]. A lot of scientific studies of delamination have concluded that the progress of tool wearing during the cutting of wood-based materials is a key problem in this case. For example, Szwajka and Trzepieci´ nski [2,3] as well as ´ Smieta ´ nska et al. [4] observed a clear relationship between the progress of tool wearing and delamination during the machining of melamine faced panels. Therefore, tool condition monitoring and the replacement of worn tools at the right time is the most useful and common (in industrial practice) way to reduce delamination. However, automation is currently the most stably developing trend in modern furniture manufacturing, which causes a lot of issues in this particular field. For this reason, the automation of tool wearing diagnostics in woodworking has been a subject of various research studies. Forests 2022, 13, 933. https://doi.org/10.3390/f13060933 https://www.mdpi.com/journal/forests