World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
10447
World Ranking
3833
National Ranking
58

Toshio Nakagawa 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 Toshio Nakagawa sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 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: 117 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: 59 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: 380 publications — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Toshio Nakagawa 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 Toshio Nakagawa sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 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: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 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: 94 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: 24 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: 51 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Toshio Nakagawa is affiliated with the Aichi Institute of Technology in Japan. Their research spans multiple fields, primarily within engineering, computer science, and decision sciences.

The main fields of study for Toshio Nakagawa include:

  • Engineering
  • Computer Science
  • Decision Sciences

Within these broader fields, the scientist has contributed notably to subfields such as:

  • Safety, Risk, Reliability and Quality
  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Computer Networks and Communications

The core research topics addressed include:

  • Reliability and Maintenance Optimization
  • Software Reliability and Analysis Research
  • Statistical Distribution Estimation and Applications
  • Probabilistic and Robust Engineering Design
  • Risk and Safety Analysis
  • Probability and Risk Models
  • Advanced Statistical Process Monitoring

Toshio Nakagawa has published a number of papers in various academic venues. Selected recent publications are:

  • Preventive replacement policies with time of operations, mission durations, minimal repairs and maintenance triggering approaches (2020), Journal of Manufacturing Systems
  • A Revisit of Age-Based Replacement Models With Exponential Failure Distributions (2021), IEEE Transactions on Reliability
  • Periodic replacement policies with shortage and excess costs (2020), Annals of Operations Research
  • Age and periodic replacement policies with two failure modes in general replacement models (2021), Reliability Engineering & System Safety
  • Preventive replacement policies for parallel systems with deviation costs between replacement and failure (2020), Annals of Operations Research

The frequent co-authors collaborating with Toshio Nakagawa are:

  • Satoshi Mizutani
  • Xufeng Zhao
  • Kodo Ito
  • Kenichiro Naruse
  • Mingchih Chen

Common publication venues include:

  • International Journal of Reliability Quality and Safety Engineering
  • Annals of Operations Research
  • Communication in Statistics- Theory and Methods
  • Reliability Engineering & System Safety
  • 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM)

In addition to journal articles and conference papers, Toshio Nakagawa has contributed to book publications within the Springer series in reliability engineering. Notable titles include:

  • Optimal Inspection Models with Their Applications (2023)
  • Which-Is-Better (WIB): Problems in Reliability Theory (2023)

Best Publications

  • Maintenance Theory of Reliability

    Toshio Nakagawa

  • The Discrete Weibull Distribution

    Toshio Nakagawa;Shunji Osaki

  • Sequential imperfect preventive maintenance policies

    T. Nakagawa

  • Shock and Damage Models in Reliability Theory

    Toshio Nakagawa

  • Periodic and sequential preventive maintenance policies

    Toshio Nakagawa

  • Optimum Policies When Preventive Maintenance is Imperfect

    Toshio Nakagawa

  • Advanced Reliability Models and Maintenance Policies

    Toshio Nakagawa

  • A summary of maintenance policies for a finite interval

    Toshio Nakagawa;Satoshi Mizutani

  • Analysis of a system with minimal repair and its application to replacement policy

    Toshio Nakagawa;Masashi Kowada

  • Bibliography for Reliability and Availability of Stochastic Systems

    Shunji Osaki;Toshio Nakagawa

  • Extended optimal replacement model with random minimal repair costs

    Shey-Huei Sheu;William S. Griffith;Toshio Nakagawa

  • New thermal neutron capture therapy for malignant melanoma: melanogenesis-seeking 10B molecule-melanoma cell interaction from in vitro to first clinical trial.

    Yutaka Mishima;Masamitsu Ichihashi;Susumu Hatta;Chihiro Honda

  • Optimization problems of replacement first or last in reliability theory

    Xufeng Zhao;Toshio Nakagawa

  • A SUMMARY OF PERIODIC REPLACEMENT WITH MINIMAL REPAIR AT FAILURE

    Toshio Nakagawa

  • A summary of imperfect preventive maintenance policies with minimal repair

    T. Nakagawa

  • Imperfect Preventive-Maintenance

    Toshio Nakagawa

  • Preparation of micron-size monodisperse polymer particles having highly crosslinked structures and vinyl groups by seeded polymerization of divinylbenzene using the dynamic swelling method

    M. Okubo;T. Nakagawa

  • Age replacement models: A summary with new perspectives and methods

    Xufeng Zhao;Khalifa N. Al-Khalifa;Abdel Magid S. Hamouda;Toshio Nakagawa

  • On a Replacement Problem of a Cumulative Damage Model

    Toshio Nakagawa

  • Stochastic Processes: with Applications to Reliability Theory

    Toshio Nakagawa

  • Optimum Policies for a System with Imperfect Maintenance

    Toshio Nakagawa;Kazumi Yasui

Frequent Co-Authors

Shunji Osaki
Shunji Osaki Nanzan University
Satoshi Fukumoto
Satoshi Fukumoto Tohoku University
Abdel Magid Hamouda
Abdel Magid Hamouda Qatar University
Tadashi Dohi
Tadashi Dohi Hiroshima University
Shey-Huei Sheu
Shey-Huei Sheu Asian University
David J. Edwards
David J. Edwards Birmingham City University
Gary David Holt
Gary David Holt University of Central Lancashire
Ming J. Zuo
Ming J. Zuo University of Alberta
Hu-Chen Liu
Hu-Chen Liu Tongji University
Balbir S. Dhillon
Balbir S. Dhillon University of Ottawa

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