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Reliability and Maintenance Optimization

Reliability and Maintenance Optimization is a research topic within Safety, Risk, Reliability and Quality. Science Explorer counts 24k research works in it since 1950. 23.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on reliability engineering and maintenance optimization, covering topics such as degradation modeling, condition-based maintenance, multi-state systems, prognostic models, accelerated degradation tests, risk-based maintenance, stochastic modeling, and system reliability. The papers explore various methods and strategies for optimizing maintenance policies and improving the reliability of deteriorating systems.

  • Reliability Engineering
  • Maintenance Optimization
  • Degradation Modeling
  • Condition-Based Maintenance
  • Multi-State Systems
  • Prognostic Models
  • Accelerated Degradation Tests
  • Risk-Based Maintenance
  • Stochastic Modeling
  • System Reliability
Research works
24k
fractional, since 1950
In the world top 10%
5.7k
per year above
Top-10% rate
23.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+20%
the tick is no change

Which countries lead Reliability and Maintenance Optimization research?

By volume, China and the United States publish the most (1.6k and 371 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.6k works
  2. 2 United States 371 works
  3. 3 India 357 works
  4. 4 France 124 works
  5. 5 United Kingdom 112 works
  6. 6 Iran 110 works
  7. 7 Germany 106 works
  8. 8 Indonesia 101 works
  9. 9 Canada 94 works
  10. 10 South Korea 75 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: 52.7%United States: 12.1%India: 11.7%France: 4.0%6 others listed: 19.5%53%largest
China1,616 · 52.7%United States371 · 12.1%India357 · 11.7%France124 · 4.0%6 others listed598 · 19.5%

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

Which institutions lead Reliability and Maintenance Optimization research?

By volume in 2022–2025, Beihang University publishes the most Reliability and Maintenance Optimization research, followed by Beijing Institute of Technology and Northwestern Polytechnical University.

By volume, 2022–2025

  1. 1 Beihang University China 106 works
  2. 2 Beijing Institute of Technology China 42 works
  3. 3 Northwestern Polytechnical University China 40 works
  4. 4 Nanjing University of Aeronautics and Astronautics China 37 works
  5. 5 Shanghai Jiao Tong University China 34 works
  6. 6 University of Electronic Science and Technology of China China 28 works
  7. 7 Chongqing University China 25 works
  8. 8 Xi'an Jiaotong University China 25 works
  9. 9 Tsinghua University China 24 works
  10. 10 National University of Defense Technology China 24 works

Who are the leading researchers in Reliability and Maintenance Optimization?

The most-cited researchers publishing on Reliability and Maintenance Optimization include Gilles Deleuze.

  1. 1 Gilles Deleuze 4.6k citations

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

Where is Reliability and Maintenance Optimization research done?

The largest centres of Reliability and Maintenance Optimization research in 2022–2025 are Beijing (China), Xi'an (China), Shanghai (China) and Nanjing (China).

Largest cities, 2022–2025

  1. 1 Beijing China 384 works
  2. 2 Xi'an China 128 works
  3. 3 Shanghai China 123 works
  4. 4 Nanjing China 95 works
  5. 5 Chengdu China 67 works
  6. 6 Wuhan China 51 works
  7. 7 Chongqing China 48 works
  8. 8 Changsha China 46 works
  9. 9 Guangzhou China 45 works
  10. 10 Tianjin China 45 works
See Reliability and Maintenance Optimization on the map

Where is the best place to study Reliability and Maintenance Optimization?

Among universities, judged by research, Beijing Institute of Technology, Toronto Metropolitan University and Beihang University 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%60%mean 37.58%fractional works in this node (log) →share in the world top 10% →Beijing Institute of Technology: 42, 41.6%Toronto Metropolitan University: 10, 48.5%Beihang University: 106, 26.4%University of Massachusetts Dartmouth: 9, 44.2%Nanjing University of Aeronautics and Astronautics: 37, 29.3%Graphic Era University: 16, 22.8%Northwestern Polytechnical University: 40, 35.6%Xi'an Jiaotong University: 25, 54.0%University of Strathclyde: 14, 26.4%Delft University of Technology: 14, 47.0%Toronto Metropolitan…University of Massac…Beijing Institute of…Beihang University
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
1Beijing Institute of Technology China 72.341.6%8.4×42 +234.7%
2Toronto Metropolitan University Canada 66.248.5%11.0×10 +103.5%
3Beihang University China 66.126.4%22.6×106 +59.0%
4University of Massachusetts Dartmouth United States 60.344.2%46.6×9 +67.4%
5Nanjing University of Aeronautics and Astronautics China 59.629.3%9.7×37 +74.3%
6Graphic Era University India 58.522.8%10.8×16 +200.3%
7Northwestern Polytechnical University China 57.035.6%8.3×40 +10.6%
8Xi'an Jiaotong University China 56.454.0%3.6×25 +93.8%
9University of Strathclyde United Kingdom 54.326.4%12.1×14 +64.1%
10Delft University of Technology Netherlands 54.147.0%4.9×14 +86.4%

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 Reliability and Maintenance Optimization research growing?

Output in 2018–2022 was 20% higher than in 2013–2017, peaking in 2023. The fastest-growing topics are Reliability and Maintenance 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.