Master Thesis: Surface topographical analysis Of Cutting inserts

2023-05-01Master students in Mechanical Engineering

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Final PresentationShobin

Masters in Mechanical

Introduction

Variants and region of interest Aim of the study Theoretical framework of reference Parameter Selection methods Results of work package 1 & 2 OBSERVATION for WP1 OBSERVATION for WP2 Future work

Variants and region of interest

Region of Interest

Edge Rounding +Pre treatment Post treatmentCoating

3 variants in WP”1” & Five varaints in WP2

1. MSG 1572. MSG1583. MS160G

1. MSG 1862. MSG1873. MSG1894. MSG190 5. MSG191

Aim of the study The Aim of the study is to investigate the Surface topography of the putting

inserts (CNMG120408-MM) In Work Package one WP1 :

Which parameter s are important when comparing different variants Interpretation of the surface roughness of the variants in connection to the

manufacturing process. If there are a predominant direction of the topograph

In Work Package one WP1 : Which parameters are important to look at when comparing the different

variants to each other? How the coating effect the surface topography Different measurement approaches to measure the surface roughness on

variants in WP1 and WP2

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Theoretical framework of reference

Surface integrity Loop Function

Manufacturing Characterization

Function : effective cutting insert, properties and alloy elements

Manufacturing: grit blasting , polishing and Chemical vapour deposition

Characterization: a) region of interest b)surface texture measurement by using

interferometer and SEM, C)Software used after the reading mountainsmap 7,

Microsoft excel, SPSS. d)3D surface texture parameter ISO 25718.

Mountainsmap7template

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1. The significance factor Si; is computed on the basis of the intervals and the mean

2.

Check threshold & disjunct function Select parameter have ´+´ve (disjunct) significant factor Reject Parameters Have ´-´ Si factor

2. Error bar :Average and Standard deviation method Check the condition choosing the parameters:

Error bar overlapping : Neglect All error bar not overlapping: Accept,

means that experimental data falling far Outside of Standard deviation are considered as significant

1. Average and Standard deviation method

Sa Smc (p = 10%)

Sxp (p = 50%,

q = 97.5%)

Vv (p = 10%)

Vmc (p = 10%,

q = 80%)

Vvc (p = 10%,

q = 80%)

0.00

0.20

0.40

0.60

0.80

1.00

Mea

n

3.Spearman's correlation Strength of a monotonic

relationship between paired data Find the spearmen correlation denoted by rs (0≤rs ≤1.00).• 0-0,3 Weak • 0,3-0,5Moderate • 0,5-0,9 strong• 0.9- 1, 0 very strong

Parameter Selection methods with Results

Selected parameters correlations

 Smc

 Sq

 Vm

 Vv

 Vmc

 Sdq

Sxp 0,97          Sa   0,96        

Vmp     0,1      Vmc       0,96    Vvc       0,99 0,99  Sdr           0,99

Error Bar followed by ANOVA and t-test

Analysis of Variance Table for WP2

Flow chart showing the Analysis of variance (ANOVA)

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MSG157

MSG158

MSG160

Result of WP1 & 2

Numerical being weighted by ”visual estimation

OBSERVATION for WP1

• Selected parameters are arithmetic mean height(Sa), extreme peak height(Smc), void volume(Vv), Core material volume(Vmc), Core void volume(Vvc) and Area height difference(Sxp).

• MSG158 Shows more texture, MSG160 shows smoother Surface and MSG157 surface characteristics in between MSG158 & MSG160.

• MSG158 shows isotropic texture with low directionality & MSG157 shows anisotropic texture. MSG160 shows high distance over the surface such that new location minimal correlation with original.

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MSG157MSG158MSG160

OBSERVATION for WP2 Parameters Sa, Smc, Vv, Vmc & Vvc are selected by using the Error bar

followed by ANOVA & t-test. MSG189 & MSG187 shows higher texture properties out of five variants. MSG190 & MSG191 are shows same surface property(which is not comparable

according to Error bar followed by ANOVA & t-test: all values are FALSE) The comparison between the MSG186&MSG189, MSG189&MSG190 &

MSG189&MSG191 are the highly significant comparison.

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Future Work Machining test followed by analysis of variants by regression

method(SPSS soft ware). Investigate the same texture properties propagated from WP1

to WP2