Analysis of tool vibration and surface roughness with tool wear progression in hard turning: An experimental and statistical approach

Ambhore, Nitin; Kamble, Dinesh; Chinchanikar, Satish

doi:10.15282/jmes.14.1.2020.21.0506

Cited by 2 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The turning process is widely applied in industry for machining the metal components in the final step of manufactures [1]. In this step, both high accuracy and perfect surface finish of the final product are required.…”

Section: Introductionmentioning

confidence: 99%

Chatter identification in turning process based on vibration analysis using Hilbert-Huang transform

Susanto¹,

Yamada²,

Tanaka³

et al. 2020

JMES

View full text Add to dashboard Cite

In machining process, the increasing cutting depth is aimed to accelerate machining operations in a short time. However, the increasing cutting depth can cause chatter vibration at any time. Chatter can accelerate tool wear and lead to poor machined surface. This paper studied the application of Hilbert-Huang transform (HHT) to analyse chatter caused by the increasing cutting depth during operation. Chatter vibration is typical of non-stationary and non-linear vibration signals, therefore it should be analysed by appropriate signal processing; HHT. In this research, initially “hammering tests” were conducted to observe dynamic modal parameters of cutting system; modal mass, damping ratio, and stiffness. Then stability lobe chart was generated based on those dynamic modal parameters to determine cutting parameters. Second, turning tests were conducted and then vibrations obtained in turning tests were analysed using HHT for chatter detection. The results were then compared by conventional signal processing; short-time Fourier (STFT) transforms. The results show that the empirical mode decomposition (EMD) of HHT process separated complex vibrations into simple components and isolated chatter from the others. The chatter was isolated in the first IMF. Therefore, chatter can be identified by EMD process. In the spectrum analysis, HHT spectra showed its superiority over STFT spectra. HHT spectra provided high time resolution and high frequency resolution both rather than STFT spectra that provided blurry and blocked spectra. The implication is that HHT can be applied to monitor the machining process.

show abstract

Section: Introductionmentioning

confidence: 99%

Chatter identification in turning process based on vibration analysis using Hilbert-Huang transform

Susanto¹,

Yamada²,

Tanaka³

et al. 2020

JMES

View full text Add to dashboard Cite

show abstract

“…Therefore, geopolymer materials can be analyzed and profiled by adopting a relatively new statistical approach called 2-level fractional factorial design (2-FrFD). To date, statistical analysis has been used in various field of studies [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Factorial design approach to investigate the significance of factors on the fire resistant, compression and adhesion properties of geopolymer binder

Salahuddin

Mazlan

Mustapha

et al. 2020

JMES

View full text Add to dashboard Cite

Despite numerous studies on the factors which influenced the properties of the geopolymer binder have been conducted, the effect of different factors on the properties of geopolymer binder was not well determined. In this research, geopolymer materials were analyzed and profiled using a statistical approach called 2-level fractional factorial design (2-FrFD). The objective is to screen and identify important factors affecting the behaviour of geopolymer binder. MINITAB, a statistical software, was used to design the experiment, analyze data obtained and present the significance value of the factors via chart and plots. The result showed that the curing temperature (V3) did not have a significant effect on the fire resistant properties of the geopolymer binder with the p-value of 0.526. Other factors and interaction were significant with RHA/AA ratio (V2) was the most significant factor with the coefficient value of 135. For the compression strength properties, all factor and interactions were significant (p-value between 0.000 and 0.009) with the RHA/AA ratio (V2) recorded the highly significant factor with the coefficient value of 8.838. For adhesion strength properties, NaOH concentration (V4) and curing time (V5) were found to be insignificant with the p-value of 0.223 and 0.133, respectively. Other factors and interaction were significant curing temperature (V3) was the most significant factor with the coefficient value of 0.287. This result may hugely benefit future researchers, towards producing halal and sustainable polymer, in determining the suitable factors which have a significant effect of the properties (outcome) of the geopolymer binder.

show abstract

Analysis of tool vibration and surface roughness with tool wear progression in hard turning: An experimental and statistical approach

Cited by 2 publications

References 22 publications

Chatter identification in turning process based on vibration analysis using Hilbert-Huang transform

Chatter identification in turning process based on vibration analysis using Hilbert-Huang transform

Factorial design approach to investigate the significance of factors on the fire resistant, compression and adhesion properties of geopolymer binder

Contact Info

Product

Resources

About