Statistical Engineering
Submission Deadline: Dec. 20, 2014
Lead Guest Editor
Ana Paula B. R. de Freitas
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Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
Published Papers
Authors: Thiago De Camargo Leite Labastie , Carlos Alberto Chaves , Antonio Faria Neto , Wendell De Queiroz Lamas , Luiz Fernando Fiorio , Helena Barros Fiorio
Pages: 47-57 Published Online: Feb. 8, 2015
DOI: 10.11648/j.ajtas.s.2014030601.16
Views 3663 Downloads 156
Authors: Carla Cristina Almeida Loures, Gisella Rossana Lamas Samanamud, Ana Paula Barbosa Rodrigues de Freitas, Ivy S. Oliveira, Leandro Valim de Freitas, Carlos Roberto de Oliveira Almeida
Pages: 42-46 Published Online: Jan. 10, 2015
DOI: 10.11648/j.ajtas.s.2014030601.15
Views 2970 Downloads 151
Authors: Ana Paula Barbosa Rodrigues de Freitas, Leandro Valim de Freitas, Carla Cristina Almeida Loures, Lúcio Gualiato Gonçalves, Messias Borges Silva
Pages: 35-41 Published Online: Dec. 31, 2014
DOI: 10.11648/j.ajtas.s.2014030601.14
Views 3174 Downloads 172
Authors: Robisom Damasceno Calado, Messias Borges Silva, Angela Alice Silva Boa Sorte Oliveira, Gabriela Salim Spagnol, Alice Sarantopoulos, Li Min Li
Pages: 23-34 Published Online: Dec. 27, 2014
DOI: 10.11648/j.ajtas.s.2014030601.13
Views 3469 Downloads 187
Authors: Ana Paula Barbosa Rodrigues de Freitas, Leandro Valim de Freitas, Carla Cristina Almeida Loures, Aneirson Francisco da Silva, Lúcio Gualiato Gonçalves, Messias Borges Silva
Pages: 19-22 Published Online: Dec. 27, 2014
DOI: 10.11648/j.ajtas.s.2014030601.12
Views 3298 Downloads 155
Authors: Fernanda de Oliveira Simon, Estéfano Vizconde Veraszto, José Tarcísio Franco de Camargo, Dirceu da Silva, Leandro Valim de Freitas, Nonato Assis de Miranda
Pages: 1-18 Published Online: Dec. 27, 2014
DOI: 10.11648/j.ajtas.s.2014030601.11
Views 3744 Downloads 156
Recently, statistical knowledge has become an important requirement and occupies a prominent position in the performance of various professions. Every day, professionals use statistical techniques increasingly sophisticated to aid in decision making.

The Statistical Engineering is a highly interdisciplinary area of knowledge focused on the design, analysis and optimization of experiments to solving real and complex multivariate problems with minimal costs involved in the trial. Moreover, it has been widely used in various fields like Engineering, Management, Logistics, Marketing, Tourism, Chemistry, Physics, Biology, among others.

The aim of this book is to bring together research papers, literature review and case studies with a multidisciplinary focus and organize them in a comprehensive way for the community interested in the field.

The advantage is that this Special Issue will cover a wide range of applications in diverse areas of knowledge for decision making based on sophisticated statistical tools that consider several variables at once. So, this Issue will not focus on just one area of application, for example, only in Chemistry or Economics as it happens traditionally. Thus, the representation of reality through statistical models become more realistic contributing to process improvement by reducing the variability, reprocessing, environmental impact. Thus, the processes are better monitored and controlled with greater profits.

Topics covered, but not limited to:

Design of Experiments

    Full Factorial Design
    Fractional Factorial Design
    Plackett-Burman Design
    Taguchi Methods
    Central Composite
    Mixture Design
    Optimization Methods (Response Surface Method, Desirability, among others)

Multivariate Analysis and Data Mining

    Classification Methods
    Factorial Analysis
    Principal Component Analysis (PCA)
    Principal Component Regression (PCR)
    Partial Least Squares Regression (PLS)
    Support Vector Machine Regression (SVMR)
    Artificial Neural Networks (ANN)

Statistical Process Control (SPC)

    Control Charts
    Measurement System Analysis (MSA)
    Multivariate Processes

Applications, but not limited to:

    Chemistry (Advanced Oxidation Process-AOP, among others)
    Industrial Engineering
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