# Nelson Rules for Control Charts

Implementation of Nelson rules for control charts in 'R'. The 'Rspc' implements some Statistical Process Control methods, namely Levey-Jennings type of I (individuals) chart, Shewhart C (count) chart and Nelson rules (as described in Montgomery, D. C. (2013) Introduction to statistical quality control. Hoboken, NJ: Wiley.). Typical workflow is taking the time series, specify the control limits, and list of Nelson rules you want to evaluate. There are several options how to modify the rules (one sided limits, numerical parameters of rules, etc.). Package is also capable of calculating the control limits from the data (so far only for i-chart and c-chart are implemented).

## Overview

Rspc is an implementation of nelson rules for control charts in R. The RSPC package implements some Statistical Process Control methods, namely Levey-Jennings type of I (individuals) chart, Shewhart C (count) chart and Nelson rules. Typical workflow is taking the time series, specify the control limits, and list of Nelson rules you want to evaluate. There are several options how to modify the rules (one sided limits, numerical parameters of rules, etc.). Package is also capable of calculating the control limits from the data (so far only for i-chart and c-chart are implemented).

• `EvaluateRules()` This function evaluates the Nelson rules (1 through 8) selected by the user. It uses output from the CalculateLimits function.

• `SetParameters()` Provides flexibility to change some default settings in the Rules 1-8 functions, such as the number of data points matching a non-random pattern for identification of run rules violations, or whether to use ‘jmp’ or ‘minitab’ convention for rules 3 and 4.

• `CalculateLimits()` If no predefined limits are entered, this function calculates k sigma limits from the center line, where k can take the values 2 or 3 (3 by default) as defined by user, the sigma is calculated as the standard deviation of the numeric data values, and the center line is calculated as the average of the numeric data values. Providing a center line as input overrides calculation of the mean from the input data. Providing any of the limits as input overrides calculation of the standard deviation from the input data.

• `CalculateZoneBorders()` This function determines the values at ±1 sigma, ±2 sigma and ±3 sigma that define the zones required for the evaluation of some Nelson Rules. It requires the input from the CalculateLimits function.

• `NelsonRules()` Wrapper function to evaluate the Rule 1-Rule 8 functions

• `Rule1() - Rule8()` These functions detect and flag violation of Nelson rules test 1 through 8 on numeric data values, relative to the center line and limits as passed by the CalculateLimits function, and delimited zones as passed by the CalculateZoneBorders function. For definition of the Nelson Rules, see Appendix 1. These functions are all called within the NelsonRules function.

# Rspc 1.2.0

• Added a `NEWS.md` file to track changes to the package.
• Only Rules 1-4 relevant for c-chart.
• Check for non negative data for c-chart.
• For controlLimitDistance less than or equal to 2 disable rule 5.
• For controlLimitDistance less than or equal to 1 disable rule 5,6,8.

# Rspc 1.2.1

• bug fix when input data has some NA values

# Rspc 1.2.2

• To main function EvaluateRules was added parameter returnAllSelectedRules

# Reference manual

install.packages("Rspc")

1.2.2 by Stanislav Matousek (MSD), 2 years ago

Report a bug at https://github.com/Merck/SPC_Package/issues

Browse source code at https://github.com/cran/Rspc

Authors: Martin Vagenknecht (MSD) [aut] , Jindrich Soukup (MSD) [aut] , Stanislav Matousek (MSD) [aut, cre] , Janet Alvarado (MSD) [ctb, rev] , Merck Sharp & Dohme Corp. a subsidiary of Merck & Co. , Inc. , Kenilworth , NJ , USA [cph]

Documentation:   PDF Manual