Reduction of noise pollution in CNC wood milling through multi-parameter optimization using response surface methodology

Shiva Souri and Farshad Rabiei

PLOS ONE, 2025, vol. 20, issue 12, 1-17

Abstract: Background: CNC (Computer Numerical Control) wood milling machines offer significant productivity advantages but are associated with excessive noise pollution, posing health risks to workers. This study investigates the influence of machining parameters on Noise Pollution Level (NPL) in CNC wood milling and aims to optimize these parameters to minimize noise emissions. Methods: A Response Surface Methodology (RSM) based on Box-Behnken Design (BBD) was employed to model the effects of cutting speed, feed rate, depth of cut, and step over on NPL. A total of 27 experimental runs were conducted. Statistical analysis, including ANOVA and regression modeling, was performed to determine the significance of each parameter. The model was further optimized using a Genetic Algorithm (GA). Results: The NPL observed across experiments ranged from 97.4 dB to 103.8 dB, with all values exceeding the NIOSH recommended limit of 85 dB. ANOVA results revealed that cutting speed, cutting speed squared, feed rate, and depth of cut had a statistically significant effect on NPL (p

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0332222 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 32222&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0332222

DOI: 10.1371/journal.pone.0332222

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().