The titanium alloy component CP001 serves as an example of the high-precision components that are the subject of this study’s investigation into the revolutionary effects of ultraprecision machining. The initial requirements were 20 x 20 x 10 mm in size, 0.2 Ra surface polish, and 5 micron tolerance. Experiment ID 101 used a diamond tool, a 0.1 mm tool diameter, a feed rate of 50 mm/min, and a machining speed of 2.0 m/s. Controlled tests were carried out using different ultraprecision machining settings. Significant modifications were seen in CP001 during post-machining examination, with final dimensions of 19.95 x 19.98 x 9.98 mm, a surface polish of 0.18 Ra, and a tolerance of 4.8 microns. The percentage change from the starting dimensions showed -0.25% accuracy, with a 4% decrease in tolerance and a 10% increase in surface polish. These findings highlight the effectiveness of ultraprecision machining and establish it as a game-changing technique for producing high-precision parts with improved surface finishes and regulated dimensional accuracy.

1.
Chu
,
C.H.
,
Zhou
,
Y.
,
Zhang
,
J.H.
,
Tang
,
J.
Computational Approaches for Improving Machining Precision in Five-Axis Flank Milling of Spiral Bevel Gears
.
Comput Ind Eng
2023
,
177
, doi: .
2.
Mu
,
X.
,
Zhou
,
M.
,
Zhang
,
J.
,
Lu
,
N.
Significant Improvements of Machined Surface Qualities by Electrical Multi-Channel Discharging in Precision Manufacturing
.
Procedia CIRP
2022
,
113
,
93
99
, doi: .
3.
Nogueira
,
M.L.
,
Greis
,
N.P.
,
Shah
,
R.
,
Davies
,
M.A.
,
Sizemore
,
N.E.
Machine Learning Classification of Surface Fracture in Ultra-Precision Diamond Turning Using CSI Intensity Map Images
.
J Manuf Syst
2022
, doi: .
4.
Wang
,
Y.
,
Liang
,
Z.
,
Zhao
,
W.
,
Wang
,
X.
,
Wang
,
H.
Anisotropic Cutting Mechanisms on the Surface Quality in Ultra-Precision Machining of R-Plane Sapphire
.
Appl Surf Sci
2023
,
622
, doi: .
5.
Exploring Machining for High-Precision - Search | ScienceDirect.Com Available online: https://www.sciencedirect.com/search?qs=Exploring%20%20Machining%20for%20High-Precision (accessed on 12 November 2023).
6.
Kratz
,
F.S.
,
Möllerherm
,
L.
,
Kierfeld
,
J.
Enhancing Robustness, Precision, and Speed of Traction Force Microscopy with Machine Learning
.
Biophys J
2023
,
122
,
3489
3505
, doi: .
7.
Karabacak
,
M.
,
Margetis
,
K.
Precision Medicine for Traumatic Cervical Spinal Cord Injuries: Accessible and Interpretable Machine Learning Models to Predict Individualized in-Hospital Outcomes
.
Spine Journal
2023
, doi: .
8.
Amsellem
,
W.
,
Yazdani
Sarvestani
, H.,
Pankov
,
V.
,
Martinez-Rubi
,
Y.
,
Gholipour
,
J.
,
Ashrafi
,
B.
Deep Precision Machining of SiC Ceramics by Picosecond Laser Ablation
.
Ceram Int
2023
,
49
,
9592
9606
, doi: .
9.
Gou
,
J.
,
Wang
,
Z.
,
Hu
,
S.
,
Shen
,
J.
,
Liu
,
Z.
,
Yang
,
C.
,
Bai
,
Y.
,
Lu
,
W.F.
Effect of Cold Metal Transfer Mode on the Microstructure and Machinability of Ti-6Al-4V Alloy Fabricated by Wire and Arc Additive Manufacturing in Ultra-Precision Machining
.
Journal of Materials Research and Technology
2022
,
21
,
1581
1594
, doi: .
10.
Sizemore
,
N.E.
,
Nogueira
,
M.L.
,
Greis
,
N.P.
,
Davies
,
M.A.
Application of Machine Learning for Improved Surface Quality Classification in Ultra-Precision Machining of Germanium
.
J Manuf Syst
2022
,
65
,
296
316
, doi: .
11.
Luo
,
K.H.
,
Wu
,
C.H.
,
Yang
,
C.C.
,
Chen
,
T.H.
,
Tu
,
H.P.
,
Yang
,
C.H.
,
Chuang
,
H.Y.
Exploring the Association of Metal Mixture in Blood to the Kidney Function and Tumor Necrosis Factor Alpha Using Machine Learning Methods
.
Ecotoxicol Environ Saf
2023
,
265
, doi: .
12.
McVey
,
C.
,
Hsieh
,
F.
,
Manriquez
,
D.
,
Pinedo
,
P.
,
Horback
,
K.
Invited Review: Applications of Unsupervised Machine Learning in Livestock Behavior: Case Studies in Recovering Unanticipated Behavioral Patterns from Precision Livestock Farming Data Streams1
.
Applied Animal Science
2023
,
39
,
99
116
, doi: .
13.
Khalil
,
A.K.
,
Yip
,
W.S.
,
Rehan
,
M.
,
To
,
S.
A Novel Magnetic Field Assisted Diamond Turning of Ti-6Al-4 V Alloy for Sustainable Ultra-Precision Machining
.
Mater Today Commun
2023
,
35
, doi: .
14.
Du
,
P.
,
Chen
,
W.
,
Deng
,
J.
,
Zhang
,
S.
,
Zhang
,
J.
,
Liu
,
Y.
A Critical Review of Piezoelectric Ultrasonic Transducers for Ultrasonic-Assisted Precision Machining
.
Ultrasonics
2023
,
135
, doi: .
15.
Xing
,
T.
,
Zhao
,
X.
,
Song
,
L.
,
Cui
,
Z.
,
Zou
,
X.
,
Sun
,
T.
On-Machine Measurement Method and Geometrical Error Analysis in a Multi-Step Processing System of an Ultra-Precision Complex Spherical Surface
.
J Manuf Process
2022
,
80
,
161
177
, doi: .
16.
Li
,
M.
,
Ma
,
C.
,
Liu
,
J.
,
Gui
,
H.
,
Zeng
,
S.
,
Luo
,
F.
Thermal Error Prediction of Precision Boring Machine Tools Based on Extreme Gradient Boosting Algorithm-Improved Sailed Fish Optimizer-Bi-Directional Ordered Neurons-Long Short-Term Memory Neural Network Model and Physical-Edge-Cloud System
.
Eng Appl Artif Intell
2024
,
127
, doi: .
17.
Mallinger
,
K.
,
Corpaci
,
L.
,
Neubauer
,
T.
,
Tikász
,
I.E.
,
Banhazi
,
T.
Unsupervised and Supervised Machine Learning Approach to Assess User Readiness Levels for Precision Livestock Farming Technology Adoption in the Pig and Poultry Industries
.
Comput Electron Agric
2023
,
213
, doi: .
18.
Zhuang
,
Z.
,
Du
,
H.
,
Sze
Yip
, W.,
Yin
,
T.
,
Zhao
,
Z.
,
Zhu
,
Z.
,
To
,
S.
Development of a High-Performance Cutting Device Based on Hybrid Actuation for Ultra-Precision Machining
.
Mater Des
2023
,
225
, doi: .
19.
Han
,
S.
,
Mannan
,
N.
,
Stein
,
D.C.
,
Pattipati
,
K.R.
,
Bollas
,
G.M.
Classification and Regression Models of Audio and Vibration Signals for Machine State Monitoring in Precision Machining Systems
.
J Manuf Syst
2021
,
61
,
45
53
, doi: .
20.
Latif
,
S.D.
,
Alyaa Binti
Hazrin
, N.,
Hoon
Koo
, C.,
Lin
Ng
, J.,
Chaplot
,
B.
,
Feng
Huang
, Y.,
El-Shafie
,
A.
,
Najah
Ahmed
, A.
Assessing Rainfall Prediction Models: Exploring the Advantages of Machine Learning and Remote Sensing Approaches
.
Alexandria Engineering Journal
2023
,
82
,
16
25
, doi: .
21.
Khalil
,
A.K.
,
Yip
,
W.S.
,
To
,
S.
Theoretical and Experimental Investigations of Magnetic Field Assisted Ultra- Precision Machining of Titanium Alloys
.
J Mater Process Technol
2022
,
300
, doi: .
22.
Kim
,
Y.
,
Yoon
,
H.S.
A Model for Predicting the Friction of Micro Patterns Fabricated by Precision Machining
.
Tribol Int
2022
,
175
, doi: .
23.
Wang
,
S.
,
Zhao
,
Q.
,
Guo
,
B.
Wear Characteristics of Electroplated Diamond Dressing Wheels Used for On- Machine Precision Truing of Arc-Shaped Diamond Wheels
.
Diam Relat Mater
2022
,
129
, doi: .
24.
Chen
,
Z.S.
,
Kulkarni
,
P.
(Param),
Galatzer-Levy
,
I.R.
,
Bigio
,
B.
,
Nasca
,
C.
,
Zhang
,
Y.
Modern Views of Machine Learning for Precision Psychiatry
.
Patterns
2022
,
3
, doi: .
25.
Amati
,
M.
,
Tiede
,
J.
,
Sun
,
Q.
(Chayn),
Deilami
,
K.
,
Hurley
,
J.
,
Fox
,
A.
,
Dickson
,
J.
Using Machine Learning to Identify Urban Forest Crown Bounding Boxes (CBB): Exploring a New Method to Develop Urban Forest Policy
.
Urban For Urban Green
2023
,
85
, doi: .
26.
Zhang
,
B.
,
Shi
,
S.
,
Wang
,
X.
,
Wang
,
X.
Machinability and Mechanism of Abrasive Flow Machining Ultra- Precision Surface with Orientated Grinding Marks
.
Journal of Materials Research and Technology
2023
, doi: .
27.
Haq
,
Md.Z. ul
;
Sood
,
H.
,
Kumar
,
R.
Effect of Using Plastic Waste on Mechanical Properties of Fly Ash Based Geopolymer Concrete
.
Mater Today Proc
2022
.
28.
Rana
,
V.S.
,
ul Haq
,
M.Z.
,
Mathur
,
N.
,
Khera
,
G.S.
,
Dixit
,
S.
,
Singh
,
S.
,
Prakash
,
A.
,
Viktorovna
,
G.V.
,
Soloveva
,
O. V.
,
Solovev
,
S.A.
Assortment of Latent Heat Storage Materials Using Multi Criterion Decision Making Techniques in Scheffler Solar Reflector
.
International Journal on Interactive Design and Manufacturing (IJIDeM)
2023
,
1
15
.
29.
Sood
,
H.
,
Kumar
,
R.
,
Jena
,
P.C.
,
Joshi
,
S.K.
Optimizing the Strength of Geopolymer Concrete Incorporating Waste Plastic
.
Mater Today Proc
2023
.
30.
Sood
,
H.
,
Kumar
,
R.
,
Jena
,
P.C.
,
Joshi
,
S.K.
Eco-Friendly Approach to Construction: Incorporating Waste Plastic in Geopolymer Concrete
.
Mater Today Proc
2023
.
31.
Kumar
,
K.
,
Dixit
,
S.
,
Prakash
,
A.
,
Vatin
,
N.I.
,
ul Haq
,
M.Z.
,
Tummala
,
S.K.
,
Bobba
,
P.B.
,
Sobti
,
R.
,
Kalpana
,
K.
Understanding Composites and Intermetallic: Microstructure, Properties, and Applications
. In
Proceedings of the E3S Web of Conferences; EDP Sciences
,
2023
; Vol.
430
, p.
01196
.
32.
Kumar
,
K.
,
Dixit
,
S.
,
ul Haq
,
M.Z.
,
Maksudovna
,
V.K.
,
Tummala
,
S.K.
,
Bobba
,
P.B.
,
Chhabra
,
S.
,
Khatua
,
D.
Breaking Barriers: Innovative Fabrication Processes for Nanostructured Materials and Nano Devices
. In
Proceedings of the E3S Web of Conferences; EDP Sciences
,
2023
; Vol.
430
, p.
01197
.
33.
Dixit
,
S.
,
Stefańska
,
A.
Bio-Logic, a Review on the Biomimetic Application in Architectural and Structural Design
.
Ain Shams Engineering Journal
2022
, doi: .
34.
Kumar
,
M.
,
Mohan
,
C.
,
Kumar
,
S.
,
Epifantsev
,
K.
,
Singh
,
V.
,
Dixit
,
S.
,
Singh
,
R.
Coordination Behavior of Schiff Base Copper Complexes and Structural Characterization
.
MRS Adv
2022
,
7
,
939
943
, doi: .
35.
Nguyen
,
H.D.
,
Pramanik
,
A.
,
Basak
,
A.K.
,
Dong
,
Y.
,
Prakash
,
C.
,
Debnath
,
S.
,
Shankar
,
S.
,
Jawahir
,
I.S.
,
Dixit
,
S.
,
Buddhi
,
D.
A Critical Review on Additive Manufacturing of Ti-6Al-4V Alloy: Microstructure and Mechanical Properties
.
Journal of Materials Research and Technology
2022
,
18
,
4641
4661
, doi: .
36.
Aghimien
,
D.
,
Ngcobo
,
N.
,
Aigbavboa
,
C.
,
Dixit
,
S.
,
Vatin
,
N.I.
,
Kampani
,
S.
,
Khera
,
G.S.
Barriers to Digital Technology Deployment in Value Management Practice
.
Buildings
2022
,
12
, doi: .
37.
Saini
,
A.
,
Singh
,
G.
,
Mehta
,
S.
,
Singh
,
H.
,
Dixit
,
S.
A Review on Mechanical Behaviour of Electrodeposited Ni-Composite Coatings
.
International Journal on Interactive Design and Manufacturing
2022
, doi: .
38.
Arora
,
M.
,
Prakash
,
A.
,
Dixit
,
S.
,
Mittal
,
A.
,
Singh
,
S.
A Critical Review of HR Analytics: Visualization and Bibliometric Analysis Approach
.
Inf Discov Deliv
2023
,
51
,
267
282
, doi: .
39.
Shanmugavel
,
R.
,
Chinthakndi
,
N.
,
Selvam
,
M.
,
Madasamy
,
N.
,
Shanmugakani
,
S.K.
,
Nair
,
A.
,
Prakash
,
C.
,
Buddhi
,
D.
,
Dixit
,
S.
Al-Mg-MoS2 Reinforced Metal Matrix Composites: Machinability Characteristics
.
Materials
2022
,
15
, doi: .
40.
Nguyen
,
D.N.
,
Dang
,
M.P.
,
Dixit
,
S.
,
Dao
,
T.P.
A Design Approach of Bonding Head Guiding Platform for Die to Wafer Hybrid Bonding Application Using Compliant Mechanism
.
International Journal on Interactive Design and Manufacturing
2022
, doi: .
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