World's Best Scientists 2026 revealed!
Reliability Engineering and System Safety
H-index 79

Reliability Engineering and System Safety

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Engineering and Technology 27 235 840 70

Additional Metrics

Number of Best Scientists*: 514
Documents by Best Scientists*: 1282
Top 100 Ranked Scientists*: 21
SCIMAGO H-index: 196
SCIMAGO SJR: 2.647
Impact Factor: 11

Overview

Top Research Topics at Reliability Engineering & System Safety?

The main research concerns discussed in Reliability Engineering & System Safety are Reliability engineering, Reliability (statistics), Operations research, Mathematical optimization and Risk analysis (engineering). In Reliability Engineering & System Safety, Probabilistic logic, Reliability (computer networking) and Component (UML) are investigated in conjunction with one another to address concerns in Reliability engineering research. The journal focuses on Reliability (statistics) but the discussions also offer insight into other areas such as Algorithm and Monte Carlo method.

The research on Risk analysis (engineering) featured in it combines topics in other fields like Risk management, Process (engineering) and Risk assessment.

  • Reliability engineering (29.03%)
  • Reliability (statistics) (20.22%)
  • Operations research (10.80%)

What are the most cited papers published in the journal?

  • Multi-objective optimization using genetic algorithms: A tutorial (2268 citations)
  • Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (1494 citations)
  • Global sensitivity analysis using polynomial chaos expansions (1357 citations)

Research areas of the most cited articles at Reliability Engineering & System Safety:

The most cited articles generally zeroe in on subjects such as Reliability engineering, Reliability (statistics), Operations research, Mathematical optimization and Risk analysis (engineering). The works on Reliability engineering tackled in the most cited papers bring together disciplines like Probabilistic logic, Process (engineering), Reliability (computer networking) and Component (UML). Issues in Reliability (statistics) were discussed in the published articles, taking into consideration concepts from other disciplines like Data mining and Failure rate.

What topics the last edition of the journal is best known for?

  • Statistics
  • Artificial intelligence
  • Law

The previous edition focused in particular on these issues:

The journal focuses on Reliability (statistics), Reliability engineering, Mathematical optimization, Component (UML) and Risk analysis (engineering). The journal explores issues in Reliability (statistics) which can be linked to other research areas like Identification (information), Complex system, Artificial intelligence, Sequence and Algorithm. Preventive maintenance research are fields of study within Reliability engineering but they also intertwine with concepts in Degradation process.

Mathematical optimization research featured in it incorporates concerns from various other topics such as Distribution networks, Reliability (computer networking), Value (mathematics), Computation and Robustness (computer science). The journal facilitates discussions on Component (UML) that incorporate concepts from other fields like Reliability model, Dual (category theory), Expression (mathematics), Imperfect and Redundancy (engineering). The studies in Risk analysis (engineering) featured incorporate elements of Potable water, Resilience (network), Water infrastructure, Prognostics and Hierarchy.

The most cited articles from the last journal are:

  • Guided simulation for dynamic probabilistic risk assessment of complex systems: Concept, method, and application (3 citations)
  • Evaluation of urban bus service reliability on variable time horizons using a hybrid deep learning method (1 citations)
  • Mathematical modeling of interdependent infrastructure: An object-oriented approach for generalized network-system analysis (1 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Reliability Engineering & System Safety (based on the number of publications) are:

  • Enrico Zio (166 papers) published 4 papers at the last edition, 6 less than at the previous edition,
  • Gregory Levitin (146 papers) absent at the last edition,
  • Terje Aven (106 papers) published 1 paper at the last edition, 2 less than at the previous edition,
  • Liudong Xing (70 papers) absent at the last edition,
  • Jon C. Helton (69 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Reliability Engineering & System Safety (based on the number of publications) are:

  • University of Stavanger (159 papers) published 1 paper at the last edition, 7 less than at the previous edition,
  • Polytechnic University of Milan (149 papers) published 3 papers at the last edition, 8 less than at the previous edition,
  • Delft University of Technology (148 papers) absent at the last edition,
  • Israel Electric Corporation (134 papers) absent at the last edition,
  • University of Electronic Science and Technology of China (132 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2022 edition, 22.06% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 22.64% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.66% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.64% of all publications and 49.06% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice

    Enrico Zio;Enrico Zio

    (2022)
    584 Citations
  • Machine learning for reliability engineering and safety applications: Review of current status and future opportunities

    Zhaoyi Xu;Joseph Homer Saleh

    (2021)
    451 Citations
  • Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges

    Unknown

    (2022)
    344 Citations
  • Fusing physics-based and deep learning models for prognostics

    Manuel Arias Chao;Chetan S. Kulkarni;Kai Goebel;Olga Fink

    (2022)
    343 Citations
  • Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning

    Min Xia;Haidong Shao;Darren Williams;Siliang Lu

    (2021)
    335 Citations
  • A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings

    Yudong Cao;Yifei Ding;Minping Jia;Rushuai Tian

    (2021)
    316 Citations
  • Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network

    Shiqi Fan;Shiqi Fan;Eduardo Blanco-Davis;Zaili Yang;Jinfen Zhang

    (2020)
    297 Citations
  • Multi-scale deep intra-class transfer learning for bearing fault diagnosis

    Xu Wang;Changqing Shen;Min Xia;Dong Wang

    (2020)
    289 Citations
  • Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks

    Omar Kammouh;Paolo Gardoni;Gian Paolo Cimellaro

    (2020)
    281 Citations
  • Failure mode and effect analysis improvement: A systematic literature review and future research agenda

    Jia Huang;Jian-Xin You;Hu-Chen Liu;Ming-Shun Song

    (2020)
    248 Citations

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