This chapter analyzes fuzzy reliability theory using bibliometric analysis. Different aspects of fuzzy have already been analyzed using bibliometric analysis, and a series of bibliometric tools have also been used. VOSviewer software was used to identify maps showing the most relevant trends. The analysis includes scientific articles, citations, journals, authors, universities, keywords, and countries. Results show that countries belonging mainly to Asia are at the avant-garde in terms of research in the field, China and India being the most productive countries in terms of the number of articles published, citations, and universities invested in the topic. Other countries in North America, such as Canada and the United States, and in Europe, the UK, Poland, Italy, and France, also show a great interest in this area of science. Research on the topic is relatively recent. The first articles were published in 1991; therefore, it presents excellent opportunities that will quite possibly attract researchers and universities from different regions of the world.
TopIntroduction
The origins of fuzzy reliability theory come from the consideration of reliability aspects of computer systems, in which system states could not be simply classified as failed or functioning (Huang & He, 2008; Zadeh, 1965). Various forms of fuzzy reliability theory can be identified, including profust reliability theory (Cai, Wen, & Zhang, 1993) posbist reliability theory (Cai, Wen & Zhang, 1991; Cappelle & Kerre, 1993), and posfust reliability theory (Kerre, Onisawa, Cappelle & Gazdik, 1998).
The works on the fuzzy reliability theory can be traced to the 1990s (Kacprzyk & Onisawa 1995), being the most relevant works those of Cai (1996) in the United States and Rotshtein & Shtovba (1997) in Ukraine. Theories were also developed by Capelle & Kerre, (1993) and Nikolaidis, Chen, Cudney, Haftka, & Rosca (2004). The applications of fuzzy ideas in reliability theory dealing with lacking inaccuracy or fluctuation data can be seen in many areas (Bamrungsetthapong & Pongpullponsak, 2014). For this study, fuzzy reliability theory was differentiated from the conventional reliability theory (Cai et al., 1991), which has been used in different contexts and settings (Chaube & Singh, 2016; Xiaoning, 2008).
Bibliometrics has been named the "Science of evaluation and analysis of Sciences" (Martínez, Díaz, Lima, Herrera & Herrera-Viedma, 2014). It applies mathematical processes and statistical methods (Garfield, 1979) to various sources, mainly publications in journals, to analyze and evaluate the quality of the scientific activity carried out by individual researchers, by research groups, by universities, and by countries (Martínez et al., 2014). Bibliometric analysis can be carried out through studies of performance, based on quantitative indicators such as the number of publications and/or impact indicators (Garfield, 1972; Martínez et al., 2014); and studies of content, based on science maps constructed through co-occurrences of terms that allow identifying the underlying conceptual structure of a scientific discipline (Cobo, López-Herrera, Herrera-Viedma & Herrera, 2011; Martínez et al., 2014).
This methodology helps evaluate the impact and performance of scientific publications through bibliometric indicators such as articles, citations, authors, journals, institutions, languages, h-index, and countries, among others; as well as various content indicators such as co-occurrences, bibliographic coupling, co-citations, etc., within a specific line of research.
Research using this methodology has increased, particularly due to the development and growth of information and communication technology tools (Pinto-López, Montaudon-Tomas & Yañez-Moneda, 2020), which has allowed access for researchers, universities, governments, and countries around the world to various scientific databases such as the Web of Science, Scopus, Google Scholar, Ebsco, Scielo, ScienceDirect, Springer, and JStor. Similarly, software tools such as VOSviewer have been developed to analyze content indicators (Van & Waltman, 2010).
Bibliometric analysis is a distinctive approach to providing a complementary perspective of research in a field closely related to scientometrics, informetrics, and webometrics. The field has substantially benefited from computerized data treatment from the last few years, and more analytical methods have become available, including mapping tools. It helps to recognize research trends by measuring scientific progress in specific disciplines.
This analysis will create an introductory perspective to the field of fuzzy reliability theory and a general overview of the state of the field, explaining the moment in which research started to be produced and its evolution. It also analyses document type, the language of publication, publication output, authorship, publication patterns, distribution of subject category, distribution of author keywords, country of publication, most-frequently cited article, document distribution, and connections between different variables. As a result, understanding of the potential and interest in the field, and the topics most frequently associated with fuzzy reliability theory will be obtained. It will also provide new insights on the topic, identifying the most influential works, the evolution of publications over time, and identifying areas of current research interest and potential directions in the future (Fahimnia, Sarkis, & Davarzani, 2015).