Analysis of tool wear, surface roughness and cutting power in the turning process of compact graphite irons with different titanium content

Rosa, Sílvia do Nascimento; Diniz, Anselmo Eduardo; Andrade, Cássio Luiz Francisco de; Guesser, Wilson Luiz

doi:10.1590/s1678-58782010000300006

Cited by 21 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…GCI contains graphite particles dispersed in the form of matrix of pearlite and limited quantity of ferrite. The literatures reveal that the pearlite matrix has well wear resistance [2]. To enhance its mechanical strength, some alloy elements, such as C, Si, Sn, Cr etc.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Reaming Process Parameters for Alloy Grey Cast Iron HT250 Using Grey Relational Analysis

Shi

Chen

et al. 2020

KEM

View full text Add to dashboard Cite

Reaming is one of the finishing processes that has been widely applied in automotive industry. Reaming parameters were evaluated and optimized based on multiple performance characteristics including tool wear and hole quality. Taguchi’s L16, 4-level, 2-factor orthogonal array (OA) was conducted for this test. It was shown that crater wear and flank wear were seen on the tool surface. Furthermore, the crater wear was also of major significance. Hole quality was discovered to be mostly dependent upon cutting speed and feed rate. TiAlN coated carbide reamer shows the best performance with respect to the tool wear as well as hole quality. Grey relational analysis used as a multiple-response optimization technique found that feed rate was the more influential parameter than cutting speed. The goal of the experimental results was to obtain both minimum diametral error and the value of surface roughness by adopting the optimal combination of the reaming parameters.

show abstract

Section: Introductionmentioning

confidence: 99%

Optimization of Reaming Process Parameters for Alloy Grey Cast Iron HT250 Using Grey Relational Analysis

Shi

Chen

et al. 2020

KEM

View full text Add to dashboard Cite

show abstract

“…Machining of CGI has been studied in all traditional machining methods, such as turning, milling, and drilling [4][5][6][7][8][9]. Rose et al [8] studied the effect of the content of Ti on tool wear and surface roughness in CGI turning. The results indicated that the increasing content of Ti in CGI could dramatically decrease the tool life.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Drilling Machinability of Compacted Graphite Iron under Dry and Minimum Quantity Lubrication (MQL)

Kuzu³

et al. 2019

Metals

View full text Add to dashboard Cite

Compacted graphite iron (CGI), which is used as a potential material in the auto industry, is a hard-to-machine material for the different minor elements and for the geometry of graphite with grey cast iron. The machinability of CGI in the drilling process was investigated with a 4-mm diameter fine-grain carbide twist drill under four lubrication conditions, dry (no compressed air), dry (with compressed air), MQL 5 ml/h, and MQL 20 mL/h in this paper. The maximum flank wear, types of wear, and cutting loads were studied for identifying the wear mechanism in drilling of CGI. The tool life in the four experiments of CGI drilling is 639 holes, 2969 holes, 2948 holes, and 2685 holes, respectively. The results showed that the main wear mechanism in drilling of CGI is adhesion and abrasion. Carbon, which originates from the graphite of CGI, can improve the lubrication in the drilling process by comparing with MnS in drilling grey cast iron. The thrust force and torque are more than 1000 N and 150 N*cm after 2700 holes in CGI drilling. Drilling of CGI under dry conditions (with compressed air) and MQL 5 ml/h is feasible.

show abstract

“…Commonly, poor surface quality is directly linked to vibration in machine tools or due to run out or great overhang of the tooling. However, the response issued by vibration sensors appears just when occurring high levels of tool wear due to the abrupt variations in the process [3,4].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of microturning process using acoustic emission signals

Filho

Oliveira

Lauro

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

The great challenge of modern industry is to carry out an online prediction in the shop floor during the machining to define the exact tool breakage instant and simultaneously improve the quality of manufactured products. Acoustic emission sensors have been used to monitoring traditional and non-traditional machining processes. This work shows a study of the online monitoring in the microturning process using an acoustic emission sensor. A factorial design was performed to examine the effect of the feed rate, depth of cut, cooling system, and the type of tool on the response acoustic emission signal. Moreover, the acoustic emission signal was correlated with surface roughness and microhardness. The results showed that the acoustic emission signals are sensitive with the progressive increase in surface roughness and the microhardness.

show abstract

Analysis of tool wear, surface roughness and cutting power in the turning process of compact graphite irons with different titanium content

Cited by 21 publications

References 4 publications

Optimization of Reaming Process Parameters for Alloy Grey Cast Iron HT250 Using Grey Relational Analysis

Optimization of Reaming Process Parameters for Alloy Grey Cast Iron HT250 Using Grey Relational Analysis

Investigation of Drilling Machinability of Compacted Graphite Iron under Dry and Minimum Quantity Lubrication (MQL)

Monitoring of microturning process using acoustic emission signals

Contact Info

Product

Resources

About