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Gestão & Produção

Print version ISSN 0104-530XOn-line version ISSN 1806-9649

Gest. Prod. vol.23 no.4 São Carlos Oct./Dec. 2016  Epub Sep 01, 2016

http://dx.doi.org/10.1590/0104-530x1649-15 

Articles

A bibliometric analysis of 50 years of worldwide research on statistical process control

Uma análise bibliométrica de 50 anos de pesquisa sobre controle estatístico de processo

Fabiane Letícia Lizarelli1 

Nayara Cristini Bessi1 

Pedro Carlos Oprime1 

Roniberto Morato do Amaral2 

Subhabrata Chakraborti3 

1Departamento de Engenharia de Produção, Universidade Federal de São Carlos – UFSCar, Rod. Washington Luís, Km 235, SP-310, CEP 13565-905, São Carlos, SP, Brazil, e-mail: fabiane@dep.ufscar.br; nayara@nit.ufscar.br; pedro@dep.ufscar.br

2Departamento de Ciência da Informação, Universidade Federal de São Carlos – UFSCar, Rod. Washington Luís, Km 235, SP-310, CEP 13565-905, São Carlos, SP, Brazil, e-mail: roniberto@nit.ufscar.br

3Department of Information Systems, Statistics and Management Science, University of Alabama – UA, P.O. Box 870226, Tuscaloosa, AL, United States, e-mail: schakrab@cba.ua.edu

Abstract

An increasing number of papers on statistical process control (SPC) has emerged in the last fifty years, especially in the last fifteen years. This may be attributed to the increased global competitiveness generated by innovation and the continuous improvement of products and processes. In this sense, SPC has a fundamentally important role in quality and production systems. The research in this paper considers the context of technological improvement and innovation of products and processes to increase corporate competitiveness. There are several other statistical technics and tools for assisting continuous improvement and innovation of products and processes but, despite the limitations in their use in the improvement projects, there is growing concern about the use of SPC. A gap between the SPC technics taught in engineering courses and their practical applications to industrial problems is observed in empirical research; thus, it is important to understand what has been done and identify the trends in SPC research. The bibliometric study in this paper is proposed in this direction and uses the Web of Science (WoS) database. Data analysis indicates that there was a growth rate of more than 90% in the number of publications on SPC after 1990. Our results reveal the countries where these publications have come from, the authors with the highest number of papers and their networks. Main sources of publications are also identified; it is observed that the publications of SPC papers are concentrated in some of the international research journals, not necessarily those with the major high-impact factors. Furthermore, the papers are focused on industrial engineering, operations research and management science fields. The most common term found in the papers was cumulative sum control charts, but new topics have emerged and have been researched in the past ten years, such as multivariate methods for process monitoring and nonparametric methods.

Keywords:  Statistical process monitoring; Statistical process control; Bibliometrics; Cienciometrics

Resumo

Um crescente número de trabalhos sobre controle estatístico do processo (CEP) emergiu nos últimos cinquenta anos e principalmente nos últimos quinze. Isso pode ser atribuído ao aumento da competitividade global gerada pela inovação e pela melhoria contínua de produtos e processos. Nesse sentido, o CEP tem um papel fundamental em sistemas de qualidade e de produção. A investigação deste artigo considera o contexto da melhoria tecnológica e de inovação de produtos e processos como forma de aumentar a competitividade das empresas. Existem várias outras técnicas e ferramentas estatísticas para auxiliar a melhoria contínua e inovação de produtos e processos, mas, apesar das limitações na sua utilização nos projetos de melhoria, há uma crescente preocupação sobre o uso do CEP. A diferença entre as técnicas de CEP ensinadas em cursos de engenharia e suas aplicações práticas para os problemas industriais é observada nas pesquisas empíricas; por esta razão, é importante identificar o que foi pesquisado e as tendências na pesquisa sobre CEP. O estudo bibliométrico é proposto neste sentido e usa para a investigação a base de dados Web of Science (WoS). A análise dos dados indica que houve uma taxa de crescimento de mais de 90% no número de publicações sobre CEP após 1990. Os resultados revelam a origem das principais publicações, os autores com o maior número de artigos e suas redes. As principais fontes de publicações também são identificadas; observa-se que as publicações de artigos sobre CEP estão concentradas em algumas revistas científicas internacionais, não necessariamente aquelas com os maiores fatores de impacto. Além disso, os artigos estão concentrados no campo da engenharia industrial, pesquisa operacional e gestão. O termo mais comum encontrado nos artigos foi carta de controle de soma cumulativa, mas novos temas emergiram e foram pesquisados nos últimos dez anos, como métodos multivariados e não-paramétricos para monitoramento de processos.

Palavras-chave:  Monitoramento estatístico do processo; Controle estatístico do processo; Bibliometria; Cienciometria

1 Introduction

Monitoring and control plans, such as those in statistical process controls (SPC), are used during the planning and control phases of a process. Such plans can directly impact the efficiency and efficacy of the production; if these plans are poorly delineated, then they can compromise product quality and productivity (Duarte & Saraiva, 2008; Hoerl & Snee, 2010; Montgomery, 2013; Lim et al., 2014).

The SPC has intrinsic relationships with two important research areas: i) the continuous improvement of products and processes, upon which the theoretical bases are derived from quality management models known as Total Quality Management (TQM) and ii) quality engineering, in which propositions originating due to the statistical models used in quality assurance and because of the need to support decisions about processes by using SPC and Design of Experiments (DOE) methods. These two aspects have an impact on business competitiveness, especially in improving the industry productivity and quality of products (Xie & Goh, 1999; Bamford & Greatbanks, 2005; Sadikoglu & Zehir, 2010; Hoerl & Snee, 2010).

There are several books and papers on the use of statistical tools and technics for improving quality and productivity (Box et al., 1978; Chen, 1997; Xie & Goh, 1999; Jones et al., 2001; Montgomery & Runger, 2003; Bamford & Greatbanks, 2005; Ehie & Sheu, 2005; He & Grigoryan, 2005; Chakraborti, 2006; Triefenbach, 2008; Chakraborti et al., 2008; Hoerl & Snee, 2010; Boone & Chakraborti, 2011; Zhang et al., 2011; Oprime & Ganga, 2013; Montgomery, 2013; Bataineh & Al-Dwairi, 2012). Employees have started to join improvement groups, mainly through Kaizen programs, and they have been trained in statistical technics of quality monitoring and control. Such a trend shows the recognition of the importance of statistical tools and technics to solve practical problems. These changes have strongly influenced the dissemination of statistical technics in SPC research and applications.

Traditional SPC methods, which are based on univariate technics, are heavily taught in training programs that have been around since 1980. Following-up on these methods, numerous procedures for multivariate statistical quality control have been developed to simultaneously monitor several quality characteristics in a process. Although somewhat more challenging to implement, the multivariate SPC methods can promote a better understanding and control of the processes being monitored and, thus, seem to be more sensitive to special causes, which are not always easily detected while using univariate control technics (Epprecht et al., 2005; He & Grigoryan, 2005; Costa et al., 2009; Costa & Machado, 2011; Kim et al., 2014; Ferrer, 2014; García-Bustos et al., 2015; Siddiqui et al., 2015). This shows an evolution of the various development and use of SPC technics and their importance in applications.

However, it may be fair to say that the advances made in the academic research world of SPC methods have not yet been fully incorporated in the manufacturing best practices. This may be a result of: i) cultural paradigms; ii) the types of groups used to promote and improve the field of statistical quality control, such as task force and semi-autonomous groups; iii) governance within groups (centralized or decentralized, use of specific methods or routines and monitoring of activities); and iv) understanding and applying new technics and tools in the problem identification stage and solution (Juran & Gryna, 1991; Atkinson, 1994; Chapman & Hyland, 1997; Bond, 1999; Harrison, 2000; Bechet et al., 2000; Jabnoun, 2001; Hyland et al., 2003; Jager et al., 2004; Fryer et al., 2007; Marin-Garcia et al., 2008; Mahanti & Evans, 2012; Rantamäki et al., 2013; Sharma & Kharub; 2014; Lim et al., 2014).

By reviewing the literature, it is evident that many journals have recently presented studies that use SPC technics and focus on process improvement and continuous innovation (Imai, 1994; Prajogo & Sohal, 2001; Murray & Chapman, 2003; Konecny & Thun, 2009; Kim et al., 2012), as well as on organizational learning (Liyanage & Poon, 2002; O’Cass & Weerawardena, 2008; Omerzel & Antončič, 2008; Korakianiti & Rekkas, 2011; Ooi et al., 2012).

Significant advances can also be seen in the literature regarding the development of new methods and strategies for SPC, such as models for auto-correlated data and multivariate processes (Costa & Castagliola, 2011; Costa & Machado, 2011; Dokouhaki & Noorossana, 2013; Franco et al., 2014; Leoni et al., 2015), control charts allowing for varying the sampling interval and the sample size (Reynolds et al., 1988; Reynolds, 1996; Reynolds & Arnold, 2001; Lin & Chou, 2005; Castagliola et al., 2006; Wu et al., 2007; Lee, 2011; Yang et al., 2012; Mahadik, 2013), improvement in the performance of control charts by double sampling (Costa & Castagliola, 2011; Teoh et al., 2015; Inghilleri et al., 2015), the design of control charts that minimize operational costs (Michel & Fogliatto, 2002; Celano et al., 2011; Lupo, 2014; Franco et al., 2014), the integration of statistical process control and automatic/engineering process control, avoiding over adjustement of the process (Holmes & Mergen, 2011; Siddiqui et al., 2015); application of the Bernoulli control charts in the field of medicine (Szarka & Woodall, 2011), application of SPC to image data (Megahed et al., 2011; Wells et al., 2013), and strategies for monitoring the variability of small batches (Celano et al., 2012; Castagliola et al., 2013).

Considering the complexity and the importance of SPC, we propose a thorough bibliometric analysis in order to better understand the research evolution over the last fifty years. Bibliometrics is an analysis tool based on empirical laws and principles and, with the passage of time, has become a generic and broad term in carrying out specific measurements in order to quantify the scientific and technological production data through publications of articles and/or patents (Okubo, 1997; Madani, 2015).

This paper has the following objectives that use bibliometrics: i) analyze the growth of the literature on SPC research in the scientific papers; ii) identify the main WoS categories in which publications can be classified and the main terms that are found; iii) recognize the leading authors in the research field and their proximity by publishing sources; iv) discover the main sources of publication; and v) determine networking and collaboration among authors and coutries. It is structured in five parts. The introduction sets out the objectives of the paper and then presents a summary of the research method. In the data analysis section, there are four subsections: i) analysis of the history of SPC publications; ii) most-cited terms and main WoS categories; iii) leading authors in the research field; iv) main souces and v) cooperation networks. A summary of the results found in the data analysis is given in Section 4. Finally, the conclusions are made in Section 5.

2 Method

The paper offers a bibliometric analysis of the international publications about SPC from 1956 to 2013 in the WoS data base. This study used advanced search methods to retrieve the search strings: “Statistical Process Control” or “Control Chart” or “SPC” or “Monitoring” or “Process Control”. After the information extraction, keywords with typos were corrected, the same occurring with authors and countries, which required a significant effort in adjustments in the database; further, there was a standardization of terms. For example, the term CUSUM appeared as CUSUM TEST, CUSUM CHART, CUSUM CHART CONTROL, CONTROL CUMULATIVE CHART, among other citations.

The choice of the database WoS was made due to the fact that it is one of the best-known bibliographic databases in the world, as well as the fact that it contains thousands of journals that can be accessed. The publisher of WoS, Thomson Reuters, is well respected and WoS is one of the most used databases worldwide as a source for the construction of scientific production.

For the data analysis, two types of software were used: Vantage Point (i.e., software for the automatic analysis of bibliographic data, which allowed for the generation of lists, matrices, and networks of cooperation among authors and countries) and Statistica 11.0, which was used in exploratory multivariate analysis that was employed for clustering. The first step was to extract the title of selected publications from the WoS search, and each one was analyzed by reading its abstract to verify that the article contained applications or theoretical developments on the SPC topic.

Bibliometrics that is based on the three main laws was used for analysis (Ravichandra Rao, 1986; Guedes & Borschiver, 2005):

    •. Lokta Law: analyzes the number of publications and their frequency by individual authors within a specific theme. This analysis shows the contribution of authors to scientific or technological progress (scientific authors’ productivity);

    •. Branford Law: analyzes the journals dispersion, focusing on journals that address a specific topic within the scientific research (journals’ productivity);

    •. Zipt Law: establishes a constant relationship between the frequency of a word and the Word position in a ranking; based on the general principle of least effort, the words that require minimal effort appear more frequently in the text (words frequency).

Other concepts used by bibliometrics include the number of citations, the impact factor and the h-index. The number of citations may indicate the influence of a particular work on other researchers, demonstrate intellectual connections, and show that a small group of authors and publications has more influence in a subject (Guedes & Borschiver, 2005). Citation numbers establish the impact factor by measuring the importance and reputation of journals and authors (Garfield, 2006). The h-index can be calculated by the number of citations received by articles from a particular journal or a particular author in the last two years divided by the total number of articles published in the same period (Garfield, 2006; Jones, 2003; Guedes & Borschiver, 2005). Another possibility, the h-index proposed by Hirsch (2005), is defined as the number of papers with the citation number ≥ h.

3 Results and discussion

3.1 SPC historical analysis

The search in the WoS database about SPC found 3,683 articles published from 1956 to 2013. Figure 1 shows the growth in the number of publications in the SPC literature. The highest number of publications was in 2013, with 343 records; 62.3% were published in the last ten years (2004 to 2013). From 1991 to 2013, 3,542 articles were published (96% of the records). The countries with the highest number of publications are the United States and the Republic of China (Figure 2), with 1,185 publications from the United States and 345 from China, together that is about 43% of the total number of publications.

Figure 1 Total number of publications related to SPC. 

Figure 2 Number of publications related to SPC of the Republic of China and the United States. 

Looking more closely, Figure 2 shows the strong growth of publications by Chinese researchers over the past decade, peaking in 2012 with 55 publications out of a total of 306, representing 17.97% of the publications for the year. The United States had 76 publications, 24.8% of the world records in the same year (2012). In 2013 the publications by United States researchers reached it’s a peak with 100 articles published, clearly showing current interest in the topic.

Figure 3 shows the number of publications per country since 1956, as well as the 20 countries with the highest number of publications.

Figure 3 Number of SPC publications per country since 1956. 

It is interesting to note in Figure 3 that 3 (Taiwan, Singapore and South Korea) among the 10 countries with the highest number of publications in the area are countries that had a high growth rate and industrialization between 1960 and 1990, showing the importance of SPC to assist in the implementation of good manufacturing and control practices.

Six (China, Iran, India, Brazil, Turkey and Malaysia) of the 20 countries with the highest number of publications are considered to be developing countries, emphasizing the importance of SPC for industrial practice.

3.2 Most cited terms and main WoS categories

The topics that were surveyed about SPC are classified in the following WoS categories or fields, in order (Figure 4) are: Engineering, Mathematical; Operations Research & Management Science; Computer Science; Automation & Control Systems and Business & Economics. Engineering, Mathematical and Operations Research & Management Science have, in this period, 68.5% of the total number of papers. The articles are mainly classified in the Engineering categoy (42.03%), showing that the papers present or deal with practical applications of SPC.

Figure 4 Main categories of SPC publications. 

The main terms that occurred among the keywords of the SPC papers were identified and displayed in Figure 5. The terms are important because they indicate areas of research emphasis. Among these, the following keywords appear frequently: cumulative sum control charts (CUSUM), multivariate statistical process control, fault detection, exponentially weighted moving average (EWMA) and quality control. In addition, there are other areas that can be considered to be evolving and signify current areas of interest, such as low cost control charts, SPC applications in metrology, process capability analysis, and nonparametric methods.

Figure 5 Principal terms found in the keywords. 

3.3 Leading authors in the research field

Figure 6 shows the most productive authors in SPC from 1956 to 2013. Our results identify that the four most productive authors (i.e., Wu, Woodall, Reynolds and Runger) have 19.2% of the total publications of the 100 most productive authors. The leading authors have concentrated their publications in some particular journals; for example, Woodall, Reynolds and Runger have over than 37% of their publications in the Journal of Quality Technology.

Figure 6 The most productive authors in SPC. 

Aiming to identify the proximity of the authors considering the source of the paper, the existence of four clusters is observed in Figure 7. It consists of the group of the 40 most productive authors, from 1956 to 2013. The analysis in Figure 7 was based on the main authors and the journals in which they published, and was then cross-checked for publication by different authors in the same journal. For the analysis, cases were the 40 most productive authors and the variables were the number of papers in the journals in which they publish. It was performed Ward's method of euclidean distance for analyzing the formed clusters, other methods were also tested, opting for the Ward's. The closer the authors are in the cluster analysis, the greater the tendency of publishing in the same journals.

Figure 7 Most productive authors grouped by publication source. 

Woodall, Runger and Reynolds are among the authors who published more articles in the area (Figure 6). Figure 7 indicates that all three are in the same cluster, indicating similarities among these authors in relation to the sources of publication. This is seen to be the most productive and the most-cited authors in recent years and have all published in similar publcations (journals). The same is not true for Wu, who, despite publishing a large number of articles, is distant from the other three authors based on the source of publication. The other 16 authors who publish more in the area are divided into clusters one and four, showing the trend of publishing in similar journals.

3.4 Main sources of publication

This analysis verifies the main sources of publication and can be seen in Figure 8 of the top 30 journals with publications on the topic of SPC, 1019 sources on the subject were found and these 30 journals are the sources of 44,3% of articles published on the topic. It should be noted that some publication sources, i.e. journals, such as the Journal of Quality Technology, Quality and Realiability Engineering International, International Journal of Production Research, IIE Transactions and Communications in Statistics-Simulation and Computation, are the top five sources of publications on the topic. Further, 20.1% of articles from 1956 to 2013 were published in these 5 major journals.

Figure 8 Top 30 journals with publications in SPC. 

The WoS impact factor of the source of publications, which are measured by the number of citations, are shown in Table 1, the same table shows the h-index. Not all the information was available for all journals. The journals with the highest impact factor (Annals of Statistics, Aiche Journal and Chenometrics and Intelligent Laboratory Systems) appear in the twenty-third, twenty-second, and the eleventh position in relation to the number of published articles. Despite the high impact factor, these are not the journals with the highest number of publications in SPC.

Table 1 Classification of main journals. 

Number # Records Source H-index Impact Factor
1 216 JOURNAL OF QUALITY TECHNOLOGY 74 1.271
2 192 QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 29 0.994
3 135 INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 86 1.323
4 102 IIE TRANSACTIONS 68 1.064
5 95 COMMUNICATIONS IN STATISTICS SIMULATION AND COMPUTATION 33 0.288
6 87 TECHNOMETRICS 126 1.79
7 84 INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 48 1.779
8 69 COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 49 0.284
9 66 JOURNAL OF APPLIED STATISTICS 36 0.453
10 62 COMPUTERS & INDUSTRIAL ENGINEERING 62 1.69
11 48 CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 94 2.381
12 41 INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH - 2.235
13 35 JOURNAL OF PROCESS CONTROL 56 2.179
14 34 JOURNAL OF STATISTICAL PLANNING AND INFERENCE 52 0.598
15 32 INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 75 2.081
16 30 EXPERT SYSTEMS WITH APPLICATIONS 69 1.965
17 28 COMPUTATIONAL STATISTICS & DATA ANALYSIS 58 1.151
18 27 JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 31 2.037
19 27 STATISTICS IN MEDICINE 146 0.713
20 25 IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 50 0.977
21 24 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH - 1.843
22 22 AICHE JOURNAL - 2.581
23 22 ANNALS OF STATISTICS 162 2.442
24 21 STATISTICS & PROBABILITY LETTERS 45 0.531
25 20 ISA TRANSACTIONS 29 2.256
26 20 JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION - 2.114
27 19 TAPPI JOURNAL 54 0.752
28 18 STATISTICAL PAPERS 18 0.82
29 16 QUALITY ENGINEERING 7 1.226
30 16 STATISTICA SINICA 55 0.355

Among the 10 journals with the highest number of articles published in the field, it may be noted that Techmometrics, International Journal of Advanced Manufacturing Technology, Computers & Industrial Engineering and International Journal of Production Research are the ones with a large number of published articles (sixth, seventh, tenth and third) and with higher impact factors (twelfth, thirteenth, fourteenth and fifteenth), and h-index values.

The journals with the highest impact factors among the 30 analyzed are: Aiche Journal, Annals of Statistics, Chemometrics and Intelligent Laboratory Systems, ISA Transactions and Industrial & Engineering Chemistry Research.

Regarding the h-index, the five journals with the highest rates are: Annals of Statistics, Journal of Statistical Computation and Simulation, Technometrics, Chemometrics and Intelligent Laboratory Systems and International Journal of Production Research. Two journals (Annals Statistics and Chenometrics and Inteligent Laboratory Systems) have both, one of the best impact factor and h-index of the sample analyzed; they are important sources of information on the subject for researches. Other sources have high levels of h-index and a large number of publications on SPC (for exemple, International Journal of Production Research and Technometrics)

This analysis allows researchers to identify the main sources of publications with a high impact factor, h-index and the number of publications for authors researching the topic or those who intend to publish on the subject.

A cluster analysis was also performed to verify the proximity of sources of publications to consider the authors who ‘publish in the same journals’ (see Figure 9). Was analyzed the number of articles published in each source by the fifty authors with the highest number of publications on SPC. The cases are the journals and variables are the number of publications of the fifty SPC main authors in these sources. The proximity of the sources shows that the same authors in the field of SPC publish in these sources.

Figure 9 The most important sources grouped by authors’ similarity. 

It can be seen from Figure 9 that there are two main groups. The first group is formed by for of the six major journals in relation to the number of publications (the exception was Communication in Statistics-Simulation and Computation and International Journal of Production Research), authors who publish in one usually publish in the other. The other large group is formed by twenty-six other journals. The same thirty companies were used for cluster analysis. The analysis shows the publications trend in the field—that the main authors publish in a specific set of journals—typically in the first group, according to the cluster analysis. These are the primary sources of publications in the area.

In Figure 10 we show the growth in the number of publications in each journal over the last 50 years. The journal Quality and Reliability Engineering International should be highlighted for the growing number of published articles on SPC and for being one of the leading journals in relation to the number of articles published on the topic.

Figure 10 Annual publication by sources. 

It is possible to see an upward trend in the number of publication in all of the five main journals from 1990 to 2009, thus showing the importance of the topic. It´s not possible to confirm if this trend continues in the 2010s, since the analysis was performed only for four years (2010-2013), but it is already possible to notice that the Quality and Reliability Engineering International journal has almost the same number of articles in four years that the previous decade (2000-2009).

Considering the fact that the 10 journals with the largest number of published papers on SPC contain 30.1% of all publications in the area, Table 2 shows what categories from WoS or research field articles are classified in each. For example, the Journal of Quality Technology classifies its publication in three different categories: Engineering, Industrial; Operations Research & Management Science and Statistics & Probability; because of this, the number of articles is repeated in each category. The same occurs for the journal Quality and Reliability Engineering International, that classifies its publication in three different categories: Engineering, Industrial; Operations Research & Management Science and Engineering, Multidisciplinary.

Table 2 Classification of journals in the main categories of WoS. 

Journal Web of Science Categories
Engineering, Industrial Operations Research & Management Science Statistics & Probability Engineering, Manufacturing Engineering, Multidisciplinary Automation & Control Systems Computer Science, Interdisciplinary Applications
JOURNAL OF QUALITY TECHNOLOGY 216 216 216
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 192 192 192
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 135 135 135
IIE TRANSACTIONS 102 102
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 95
TECHNOMETRICS 87
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 84 84
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 69
JOURNAL OF APPLIED STATISTICS 66
COMPUTERS & INDUSTRIAL ENGINEERING 62 62
Total 707 645 533 219 192 84 62

In absolute numbers, there is a greater occurrence of articles of SPC classified as Engineering, Industrial and Operations Research & Management Science because of the journals in which they are published. A graph of the number of publications in the five main categories is shown in Figure 11. It is seen that the statistics and probability category has seen its ups and downs whereas the other categories all show an increasing trend. It appears that research and publications in SPC is trending more towards Engineering and Operations journals which focus more on practical and applied research.

Figure 11 Evolution of numbers of publications by WoS categories. 

3.5 Cooperation structure

The analysis of the co-authorship data by authors from different countries helps to identify and illustrate the knowledge network and the intellectual leverage generated by some authors with great international connections.

The network analysis was performed to identify the cooperation structure between 50 authors who produce the largest number of publications in SPC, considering the connections between countries and North American states. Figure 12 summarizes this analysis, identifying seven networks of cooperation, especially the cooperation between the Chinese and American authors, and others (e.g., USA-Germany, USA-South Korea, USA-India, France-Italy, France-Malaysia and Netherlands-Belgium). This analysis is important because it shows the network of cooperation between countries and the dissemination of knowledge, and researchers from some countries have not yet established significant international partnerships, such as Greece, Portugal and even Brazil.

Figure 12 General structure for cooperation. 

Figure 13 shows the network among the authors, i.e, the relations between the co-authors of the papers, the focus being on the connection among the individual researchers. Figure 13 displays the network of cooperation between the 50 leading authors, thus showing that, as a form of cooperation between countries, some authors have a network of more contacts, thus influencing other authors who work together. The authors who publish more in the field (Wu, Woodall, Reynolds, Runger and Tsung), have a high level of contact with others, thus strengthening the network of publications.

Figure 13 Network among authors. 

4 Discussion

The United States and China are the two countries that stood out with the highest number of published articles on SPC over the last decade; Chinese production has increased substantially since 2000. The five countries with the highest number of publications since 1956, in order, are the United States, China, the United Kingdom, Taiwan and Canada. Several countries among the twenty with the highest number of publications on SPC had a high rate of industrialization between 1960-1990 or are developing countries, showing the connection and importance of the topic for researchers and industrial applications.

The analysis of the number of publications on the subject during the time investigated showed that there is an increasing trend in the number of published articles, thus showing the growth of SPC research and that SPC is an important and current topic.

The scientific production in the area of SPC has grown by 65.5% in the last ten years. It is concentrated in the fields of Engineering, Mathematics and Operations Research & Management Science. The most commonly used terms found in the database in the period surveyed were: CUSUM, Multivariate Statistical Process Control, Average Runs Length (ARL) and Quality Control. Other topics with lower absolute numbers of records, but equally important, were Economic Design, Process Capability, Pattern Recognition and Non-Parametric Analysis. The analysis of the key terms can identify search trends, as some of them have already been heavily exploited and others seem to be indicating trends for future research.

The bibliometric analysis also allowed the identification of the main authors of the area (Wu, Woodall, Reynolds, Runger and Tsung) and the proximity between them regarding the sources of publication. It should be noted that the Journal of Quality Technology, Quality and Realiability Engineering International, International Journal os Production Research, IIE Transactions and Communications in Statistics-Simulation and Computation are the top five sources of number of publications on the SPC topic. We also observed the journals with the highest impact factor and h-index.

The top journals that publish SPC research focus on Engineering, Industrial; Operations Research & Management Science, Statistics & Probability, but there was a decrease in the number of publications in the last category over the years. The concentration of publications in the Engineering and Operations Research categories shows the applied nature of SPC research. The use of cluster analysis made it possible to identify the closeness among the journals because of publication by the same authors in these different sources.

The final analysis involved the creation of cooperation networks between the countries and between the authors, thus enabling the identification of the knowledge network and important links between and among these networks.

5 Conclusion

SPC continues to be an important area of research for the Engineering, Operations Research and Management Science sectors. For this reason, the number of published articles on SPC has grown in recent years. However, some research topics, such as ARL, were already well explored, opening space for topics such as multivariate statistical control. Incentives for research on emerging topics on SPC, such as non-parametric methods, can be achieved by encouraging other researchers to work on the subject and thus form productive networks.

There are leading countries in this type of publication, such as the United States. More recently, China have increased their academic outputs, but the production remains still small compared to that of United States.

The most productive authors publish in the same sources (journals) and have a strong research network. The most productive authors also have strong affinities and are distinguished from other clusters of researchers who publish in different journals. The collaboration network is also strong for countries with the highest number of publications, therefore showing the importance of forming collaborative networks and knowledge dissemination pathways.

This paper chronicles identifies the growth of publications in the various areas of SPC research and the main sources of English language publications. It also surveys major terms, countries that have the highest number of publications on the subject and cooperation networks between the leading authors and between countries. A bibliometric analysis of SPC is important because it provides an overview of the research arena, main sources and authors to indentify current research and future trends for SPC.

Financial support: The visit of Professor Subha Chakraborti to the Department of Production Engineering from the Federal University of São Carlos, DEP-UFSCar, had financial assistance from FAPESP, through the “Research Assistance Program”, Process 2014/00550-3.

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Received: August 06, 2015; Accepted: December 17, 2015

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