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Advanced machining processes and optimization

Advanced machining processes and optimization is a research topic within Mechanical Engineering. Science Explorer counts 58k research works in it since 1950. 13.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on advanced monitoring and optimization of machining operations, including topics such as surface integrity, tool wear, cutting parameters, chatter vibration, minimum quantity lubrication, and high speed machining. It also covers the machining of composite materials and the control of surface roughness in various machining processes.

  • Machining
  • Surface Integrity
  • Tool Wear
  • Cutting Parameters
  • Metal Cutting
  • Chatter Vibration
  • Minimum Quantity Lubrication
  • Composite Materials
  • High Speed Machining
  • Surface Roughness
Research works
58k
fractional, since 1950
In the world top 10%
7.7k
per year above
Top-10% rate
13.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+29%
the tick is no change

Which countries lead Advanced machining processes and optimization research?

By volume, China and India publish the most (4.6k and 1.7k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 4.6k works
  2. 2 India 1.7k works
  3. 3 Germany 558 works
  4. 4 United States 444 works
  5. 5 Türkiye 376 works
  6. 6 Russia 373 works
  7. 7 Japan 289 works
  8. 8 Poland 222 works
  9. 9 United Kingdom 204 works
  10. 10 Vietnam 179 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 51.4%India: 19.1%Germany: 6.2%United States: 5.0%6 others listed: 18.3%51%largest
China4,606 · 51.4%India1,716 · 19.1%Germany558 · 6.2%United States444 · 5.0%6 others listed1,642 · 18.3%

Shares of the rows listed above, not of the whole node.

Which institutions lead Advanced machining processes and optimization research?

By volume in 2022–2025, Nanjing University of Aeronautics and Astronautics publishes the most Advanced machining processes and optimization research, followed by Dalian University of Technology and Harbin Institute of Technology.

Who are the leading researchers in Advanced machining processes and optimization?

The most-cited researchers publishing on Advanced machining processes and optimization include Kai Wang.

  1. 1 Kai Wang China 3.1k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Advanced machining processes and optimization research done?

The largest centres of Advanced machining processes and optimization research in 2022–2025 are Beijing (China), Shanghai (China), Nanjing (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Thái Nguyên.

Largest cities, 2022–2025

  1. 1 Beijing China 537 works
  2. 2 Shanghai China 273 works
  3. 3 Nanjing China 271 works
  4. 4 Xi'an China 268 works
  5. 5 Harbin China 238 works
  6. 6 Chennai India 204 works
  7. 7 Wuhan China 194 works
  8. 8 Shenyang China 194 works
  9. 9 Dalian China 177 works
  10. 10 Chongqing China 161 works

Where it is the local speciality

  1. Thái NguyênVN · 23.8 works20×
← less than its size predictsmore →

Location quotient: how much more of its research is in Advanced machining processes and optimization than the world average.

See Advanced machining processes and optimization on the map

Where is the best place to study Advanced machining processes and optimization?

Among universities, judged by research, Opole University of Technology, Northeastern University and University of Engineering and Technology Lahore score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 26.73%fractional works in this node (log) →share in the world top 10% →Opole University of Technology: 14, 41.7%Northeastern University: 97, 22.9%University of Engineering and Technology Lahore: 12, 25.2%Dalian University of Technology: 144, 22.7%Indian Institute of Technology Ropar: 14, 25.8%Nanjing University of Aeronautics and Astronautics: 163, 17.3%Düzce Üniversitesi: 14, 37.3%Chongqing University: 106, 23.2%South Ural State University: 14, 18.5%Institute of Infrastructure Technology Research and Management: 10, 32.7%Opole University of …University of Engine…Northeastern Univers…Dalian University of…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Opole University of TechnologyPoland 73.041.7%28.1×14 +108.2%
2 Northeastern UniversityChina 69.322.9%9.5×97 +131.3%
3 University of Engineering and Technology LahorePakistan 69.325.2%10.8×12 +389.7%
4 Dalian University of TechnologyChina 66.122.7%13.1×144 +12.1%
5 Indian Institute of Technology RoparIndia 63.225.8%9.8×14 +367.1%
6 Nanjing University of Aeronautics and AstronauticsChina 61.917.3%15.8×163 -2.5%
7 Düzce ÜniversitesiTürkiye 61.937.3%7.3×14 +157.3%
8 Chongqing UniversityChina 61.023.2%8.4×106 +15.9%
9 South Ural State UniversityRussia 60.218.5%10.4×14 +311.3%
10 Institute of Infrastructure Technology Research and ManagementIndia 59.232.7%41.7×10

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Advanced machining processes and optimization research growing?

Output in 2018–2022 was 29% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Advanced machining processes and optimization.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.