Applications in teaching Statistical Quality Control with different R interfaces

Continual improvement in the quality of products, processes, and services has been facilitated by applying statistical methods. The statistical process control technique (SPC) provides enhanced results, as it utilizes statistical methods throughout all the developmental stages of a project and/or production. One of these techniques is control charts, which are powerful tools for viewing and understanding different types of process variations. Therefore, it is essential for professionals linked to engineering and technological fields to be familiar with these techniques and software programs, in order to facilitate the development process for creating control charts. The majority of these software programs designed for easy utilization and friendly interface for SPC applications are sold at high prices and thereby make access impossible to this computational resource for freelance professionals, small businesses, and especially students. The GNU R interface is open source and provides free access as one of the alternatives. So, for this purpose, this paper presents the description and application of control charts in three different R interfaces, as its objective is to use them for the teaching and learning process.

[1]  G. Geoffrey Vining.  Technical Advice: Phase I and Phase II Control Charts , 2009 .

[2]  B. Becker.  A Look at the Literature (and Other Resources) on Teaching Statistics , 1996 .

[3]  Robert G. Gould,et al.  Statistics and the Modern Student , 2010 .

[4]  Gilberte Schuyten,et al.  Statistical Thinking in Computer‐Based Learning Environments , 2007 .

[5]  Edson Pacheco Paladini,et al.  Artificial intelligence approach to support statistical quality control teaching , 2006, Comput. Educ..

[6]  A.F.S Leao.  Controle estatistico de qualidade de eficiencia escolar na DHN , 1983 .

[7]  L. Scrucca,et al.  qcc: An R package for quality control charting and statistical process control , 2004 .

[8]  Erich Neuwirth,et al.  Excel : : COM : : R , 2007, Comput. Stat..

[9]  S. W. Roberts,et al.  Control Chart Tests Based on Geometric Moving Averages , 2000, Technometrics.

[10]  Jeffrey S. Racine,et al.  RStudio: A Platform-Independent IDE for R and Sweave , 2012 .

[11]  John Verzani.  Using R in Introductory Statistics Courses With the pmg Graphical User Interface , 2008 .

[12]  Francisco Louzada,et al.  Controle Estatístico de Processo via Linguagem Livre , 2012 .

[13]  Custodio da Cunha Alves,et al.  A utilização de gráficos de controle de soma acumulada (cusum) para monitoramento de um processo de usinagem , 2009 .

[14]  Erich Neuwirth,et al.  Excel :: COM :: $$\mathsf{R}$$ , 2007 .

[15]  John Maltby,et al.  Learning statistics by computer software is cheating , 2001, J. Comput. Assist. Learn..

[16]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[17]  Jaydeep Balakrishnan,et al.  An Interactive VBA Tool for Teaching Statistical Process Control SPC and Process Management Issues , 2005 .

[18]  E. S. Page.  CONTINUOUS INSPECTION SCHEMES , 1954 .

[19]  Eric R. Ziegel,et al.  Probability and Statistics for Engineering and the Sciences , 2004, Technometrics.

[20]  John Fox,et al.  GETTING STARTED WITH THE R COMMANDER: A BASIC-STATISTICS GRAPHICAL USER INTERFACE TO R , 2005 .

[21]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[22]  Michael Sherman.  Probability and Statistics for Engineering and the Sciences (6th ed.) , 2006 .