World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
58
Citations
8971
World Ranking
2576
National Ranking
36

Thong Ngee Goh publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Thong Ngee Goh sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 218 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Thong Ngee Goh D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Thong Ngee Goh sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Normal distribution
  • Artificial intelligence

His primary scientific interests are in Statistics, Control chart, Machine learning, Artificial intelligence and Quality management. His Exponential distribution, Mathematical model, Stochastic process and Autocorrelation study in the realm of Statistics interacts with subjects such as Solar energy conversion. His Control chart research includes elements of Reliability engineering, Equivalence, Statistical process control and Chart.

Thong Ngee Goh interconnects Weibull distribution and Exponentiated Weibull distribution in the investigation of issues within Reliability engineering. His Artificial neural network study in the realm of Machine learning connects with subjects such as Weighting. Thong Ngee Goh studied Quality management and Six Sigma that intersect with Knowledge management and Knowledge economy.

His most cited work include:

  • A modified Weibull extension with bathtub-shaped failure rate function (306 citations)
  • A comparative study of neural network and Box-Jenkins ARIMA modeling in time series prediction (204 citations)
  • A strategic assessment of six sigma (187 citations)

What are the main themes of his work throughout his whole career to date?

Thong Ngee Goh focuses on Control chart, Statistics, Statistical process control, Chart and Reliability engineering. His research investigates the connection between Control chart and topics such as Industrial engineering that intersect with issues in Operations research. His Statistics research integrates issues from np-chart, u-chart and Algorithm.

His Statistical process control study which covers Process that intersects with Quality and Design of experiments. His Chart study integrates concerns from other disciplines, such as CUSUM and Sensitivity. He has researched Weibull distribution in several fields, including Applied mathematics and Failure rate.

He most often published in these fields:

  • Control chart (28.14%)
  • Statistics (23.12%)
  • Statistical process control (19.10%)

What were the highlights of his more recent work (between 2009-2020)?

  • Six Sigma (13.57%)
  • Statistics (23.12%)
  • Quality management (11.56%)

In recent papers he was focusing on the following fields of study:

Thong Ngee Goh spends much of his time researching Six Sigma, Statistics, Quality management, Quality and Control chart. In general Six Sigma, his work in Design for Six Sigma is often linked to Set and Particle physics linking many areas of study. His Statistics study combines topics from a wide range of disciplines, such as Algorithm, Residual and Statistical process control, Average run length.

His Quality study incorporates themes from New product development, Knowledge management and Product. His work deals with themes such as Industrial engineering, Reliability engineering and Chart, which intersect with Control chart. He combines subjects such as Reliability and Weibull distribution with his study of Reliability engineering.

Between 2009 and 2020, his most popular works were:

  • A systematic comparison of metamodeling techniques for simulation optimization in Decision Support Systems (116 citations)
  • Analysis of building environment assessment frameworks and their implications for sustainability indicators (65 citations)
  • Adaptive ridge regression system for software cost estimating on multi-collinear datasets (39 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Normal distribution
  • Artificial intelligence

Design for Six Sigma, Six Sigma, Control chart, Management and Lean Six Sigma are his primary areas of study. His studies deal with areas such as Reliability engineering and Chart as well as Control chart. His biological study spans a wide range of topics, including Economic design, Sample, Industrial engineering and Exponential distribution.

His Chart study combines topics in areas such as Sequential probability ratio test and CUSUM. His Management research incorporates elements of Statistical thinking and Public relations. He has included themes like Statistics, Sample size determination and Statistical process control in his EWMA chart study.

Best Publications

  • A modified Weibull extension with bathtub-shaped failure rate function

    Min Xie;Y. Tang;Thong Ngee Goh

  • A comparative study of neural network and Box-Jenkins ARIMA modeling in time series prediction

    S. L. Ho;M. Xie;T. N. Goh

  • A strategic assessment of six sigma

    T. N. Goh

  • Some effective control chart procedures for reliability monitoring

    Min Xie;Thong Ngee Goh;Priya Ranjan

  • A study of project selection and feature weighting for analogy based software cost estimation

    Y. F. Li;M. Xie;T. N. Goh

  • A systematic comparison of metamodeling techniques for simulation optimization in Decision Support Systems

    Y. F. Li;S. H. Ng;M. Xie;T. N. Goh

  • Cumulative quantity control charts for monitoring production processes

    L. Y. Chan;M. Xie;T.N. Goh

  • Statistical Models and Control Charts for High-Quality Processes

    M. Xie;T. N. Goh;V. Kuralmani

  • Improving on the six sigma paradigm

    T.N. Goh;M. Xie

  • CONTROL CHART FOR MULTIVARIATE ATTRIBUTE PROCESSES

    X S Lu;M Xie;T N Goh;C D Lai

  • A comparative study of the prioritization matrix method and the analytic hierarchy process technique in quality function deployment

    H. Wang;M. Xie;T. N. Goh

  • A control chart for the Gamma distribution as a model of time between events

    C. W Zhang;M Xie;J. Y Liu;T. N Goh

  • Zero-inflated Poisson model in statistical process control

    M. Xie;B. He;T. N. Goh

  • A study of the connectionist models for software reliability prediction

    Siu Lau Ho;M. Xie;T. N. Goh

  • The role of statistical design of experiments in Six Sigma: Perspectives of a practitioner

    T. N. Goh

  • FORTIFICATION OF SIX SIGMA: EXPANDING THE DMAIC TOOLSET

    Loon Ching Tang;Thong Ngee Goh;Shao Wei Lam;Cai Wen Zhang

  • A study of mutual information based feature selection for case based reasoning in software cost estimation

    Y. F. Li;M. Xie;T. N. Goh

  • Analysis of building environment assessment frameworks and their implications for sustainability indicators

    Yuya Kajikawa;Toshihiro Inoue;Thong Ngee Goh

  • Analysis of step-stress accelerated-life-test data: a new approach

    L.C. Tang;Y.S. Sun;T.N. Goh;H.L. Ong

  • Stochastic modeling and forecasting of solar radiation data

    T.N. Goh;K.J. Tan

Frequent Co-Authors

Min Xie
Min Xie City University of Hong Kong
Loon Ching Tang
Loon Ching Tang National University of Singapore
Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Jiang Liu
Jiang Liu Southern University of Science and Technology
B.W. Ang
B.W. Ang National University of Singapore
S. L. Ho
S. L. Ho Hong Kong Polytechnic University
Yan-Fu Li
Yan-Fu Li Tsinghua University
Dennis K. J. Lin
Dennis K. J. Lin Purdue University West Lafayette
Yuya Kajikawa
Yuya Kajikawa University of Tokyo
Johan Liu
Johan Liu Chalmers University of Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Best Scientists Citing Thong Ngee Goh

Trending Scientists

Recently Published Articles