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Quality Control with R

Part of the Use R! Book Series

DOI: 10.1007/978-3-319-24046-6

ISBN: 978-3-319-24044-2

Publisher: Springer International Publishing - Springer Journals

Nov 21, 2015

1 - 10 of 10 Chapters

LitStream

An Intuitive Introduction to Quality Control with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 3 –28

[This chapter introduces Quality Control by means of an intuitive example. Furthermore, that example is used to illustrate how to use the R statistical software and programming language for Quality Control. A description of R outlining its advantages is also included in this chapter, all in all...
LitStream

An Introduction to R for Quality Control

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 29 –92

[This chapter introduces R as statistical software and programming language for quality control. The chapter is organized as a kind of tutorial with lots of examples ready to be run by the reader. Moreover, the code is available at the book’s companion website. Even though the RStudio interface...
LitStream

The Seven Quality Control Tools in a Nutshell: R and ISO Approaches

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 93 –118

[The aim of this chapter is to smoothly introduce the reader to Quality Control techniques from the so-called Seven Basic Quality Control tools: Cause-and-effect-diagram, check sheet, control chart, histogram, Pareto chart, scatter diagram, and stratification. These are basic but powerful tools...
LitStream

R and the ISO Standards for Quality Control

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 119 –142

[This chapter details the way ISO international standards for quality control are developed. Quality Control starts with Quality, and standardization is crucial to deliver products and services where quality satisfies final users, whatever they are customers, organizations, or public bodies. The...
LitStream

Modelling Quality with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 145 –186

[This chapter provides the necessary background to understand the fundamental ideas of descriptive and inferential statistics. In particular, the basic ideas and tools used in the description both graphical and numerical, of the inherent variability always present in real world are described....
LitStream

Data Sampling for Quality Control with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 187 –199

[Statistical Quality Control tries to predict the behavior of a given process through the collection of a subset of data coming from the performance of the process. This chapter showcases the importance of sampling and describes the most important techniques used to draw representative samples....
LitStream

Acceptance Sampling with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 203 –220

[Undoubtedly, an effective but expensive way of providing conforming items to a customer is making a complete inspection of all items before shipping. In an ideal situation, a process designed to assure zero defects would not need inspection at all. In practice, a compromise between these two...
LitStream

Quality Specifications and Process Capability Analysis with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 221 –236

[In order to assess quality, specification limits are to be established. In this chapter a method to set specification limits taking into account customers’ and producer’s loss is presented. Furthermore, the specification limits are the voice of the customer, and quality can be assessed by...
LitStream

Control Charts with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 239 –270

[Control charts constitute a basic tool in statistical process control. This chapter develops the fundamentals of the most commonly applied control charts. Although the general basic ideas of control charts are common, two main different classes are to be considered: control charts for variables,...
LitStream

Nonlinear Profiles with R

Cano, Emilio L.; Moguerza, Javier M.; Corcoba, Mariano Prieto

Pages: 271 –284

[In many situations, processes are often represented by a function that involves a response variable and a number of predictive variables. In this chapter, we show how to treat data whose relation between the predictive and response variables is nonlinear and, as a consequence, cannot be...

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