Control de calidad. Felipe de Mendiburu. Second sample Calibration data in D[trial] New data in D[!trial] First samples UCL. Group summary statistics
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1 Control de calidad con First samples Second sample Calibration data in D[trial] New data in D[!trial] summary statistics Felipe de Mendiburu
![trial] summary statistics 0.0 0.1 0.2 0.3 0.4 0.](/docs-images/57/6906789/images/page_1.jpg "5 Felipe de Mendiburu 1 4 7 11 15 19 23 27 31 39 47")
2 cause.and.effect( cause=list( Materiales=c("Materia prima defectuosa", "Defectos de armado", "Material escalibrado"), Mano.Obra=c("Falta de capacitacion", "Falta de compromiso"),metodos=c("inspeccion deficiente", "Falta de instruccion", "Diseño indadecuado"),maquinas=c("soldador inadecuado", "Patron desequilibrado")), effect="falla el termostado", title= " Diagrama de Causa - Efecto", cex = c(1.5, 0.9, 1.5), font = c(4,1,4)) Diagrama de Causa - Efecto Materiales Mano.Obra Materia prima defectuosa Falta de capacitacion Defectos de armado Falta de compromiso Material descalibrado Falla el termostado Diseño indadecuado Falta de instruccion Patron desequilibrado Inspeccion deficiente Soldador inadecuado Metodos Maquinas
3
4 Argumentos de la funcion qqc()
5 x <- c(33.75, 33.05, 34, 33.8,.) qcc(x, type="xbar.one") xbar.one Chart for x summary statistics Number of groups = 15 Center = StdDev = = = Number beyond limits = 0 Number violating runs = 0
6 Excel: pistones.xls Text: pistones.txt Copy Paste En R: > pistones <- read.table( pistones.txt,header=t)
7
8 > qcc(diameter, type="xbar") xbar Chart for diameter summary statistics Number of groups = 40 Center = StdDev = = = Number beyond limits = 2 Number violating runs = 3
9 > qcc(diameter, type="xbar") Call: qcc(data = diameter, type = "xbar") xbar chart for diameter Summary of group statistics: Min. 1st Qu. Median Mean 3rd Qu. Max sample size: 5 Number of groups: 40 Center of group statistics: Standard deviation: Control limits:
10 Eliminando algunas observaciones para tener muestras con diferentes tamaños: > salen <- c(9, 10, 30, 35, 45, 64, 65, 74, 75, 85, 99, 100)
11 Ordenes para hacer las cartas: > salen <- c(9, 10, 30, 35, 45, 64, 65, 74, 75, 85, 99, 100) > diameter <- qcc.groups(pistones$diameter[-salen], sample[- salen]) > qcc(diameter[1:25,], type="xbar") > qcc(diameter[1:25,], type="r") > qcc(diameter[1:25,], type="s") > qcc(diameter[1:25,], type="xbar", newdata=diameter[26:40,]) > qcc(diameter[1:25,], type="r", newdata=diameter[26:40,]) > qcc(diameter[1:25,], type="s", newdata=diameter[26:40,]) Otras ordenes: > qcc(diameter[1:25,], type="xbar", newdata=diameter[26:40,], nsigmas=2) > qcc(diameter[1:25,], type="xbar", newdata=diameter[26:40,], confidence.level=0.99)
![> qcc(diameter[1:25,], type="xbar", newdata=diameter[26:40,]) > qcc(diameter[1:25,], type="r", newdata=diameter[26:40,]) > qcc(diameter[1:25,], type="s",](/docs-images/57/6906789/images/page_11.jpg "newdata=diameter[26:40,]) Otras ordenes: > qcc(diameter[1:25,], type=\"xbar\", newdata=diameter[26:40,], nsigmas=2) > qcc(diameter[1:25,], type=\"xbar\",")
12 xbar Chart for diameter[1:25, ] summary statistics Number of groups = 25 Center = StdDev = is variable is variable Number beyond limits = 0 Number violating runs = 0
13 R Chart for diameter[1:25, ] summary statistics Number of groups = 25 Center = StdDev = = 0 is variable Number beyond limits = 0 Number violating runs = 2
14 S Chart for diameter[1:25, ] summary statistics Number of groups = 25 Center = StdDev = = 0 is variable Number beyond limits = 0 Number violating runs = 1
15 xbar Chart for diameter[1:25, ] and diameter[26:40, ] Calibration data in diameter[1:25, ] New data in diameter[26:40, ] summary statistics Number of groups = 40 Center = StdDev = is variable is variable Number beyond limits = 3 Number violating runs = 1
16 summary statistics R Chart for diameter[1:25, ] and diameter[26:40, ] Calibration data in diameter[1:25, ] New data in diameter[26:40, ] Number of groups = 40 Center = StdDev = = 0 is variable Number beyond limits = 0 Number violating runs = 2
![diameter[1:25, ] New data in diameter[26:40, ] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29](/docs-images/57/6906789/images/page_16.jpg "31 33 35 37 39 Number of groups = 40 Center = 0.02230088 StdDev = 0.")
17 S Chart for diameter[1:25, ] and diameter[26:40, ] Calibration data in diameter[1:25, ] New data in diameter[26:40, ] summary statistics Number of groups = 40 Center = StdDev = = 0 is variable Number beyond limits = 0 Number violating runs = 1
18 ATRIBUTOS
19
20 p Chart for D[trial] summary statistics Number of groups = 30 Center = StdDev = = = Number beyond limits = 2 Number violating runs = 0
21
22 p Chart for D[inc] summary statistics Number of groups = 28 Center = StdDev = = = Number beyond limits = 1 Number violating runs = 1
23 summary statistics Calibration data in D[inc] p Chart for D[inc] and D[!trial] New data in D[!trial] Number of groups = 52 Center = StdDev = = = Number beyond limits = 2 Number violating runs = 2
24 > q1 <- qcc(d[inc], sizes=size[inc], type="c") > c Chart for D[inc] summary statistics Number of groups = 28 Center = StdDev = = 0 = Number beyond limits = 0 Number violating runs = 0
25 Carta U Datos de clase
26 > attach(datos) > qcc(defectos,unidades, type="u") u Chart for Defectos summary statistics Number of groups = 30 Center = StdDev = is variable is variable Number beyond limits = 1 Number violating runs = 1
27 OC curves for xbar chart Prob. type II error n = 5 n = 1 n = 10 n = 15 n = Process shift (std.dev)
28 contact num. price code supplier code part num. schedule date Pareto Chart for defect Error frequency % 25% 50% 75% 100% Cumulative Percentage
29 q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=false) process.capability(q, spec.limits=c(73.95,74.05)) Process Capability Analysis for diameter[1:25, ] LSL Target USL Number of obs = 125Target = 74 Center = LSL = StdDev = USL = Cp = 1.42 Cp_l = 1.51 Cp_u = 1.34 Cp_k = 1.34 Cpm = 1.38 Exp<LSL 0% Exp>USL 0% Obs<LSL 0% Obs>USL 0%
30 > q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=false) > process.capability.sixpack(q, spec.limits=c(73.95,74.05)) summary statistics xbar Chart for diameter[1:25, ] Process Capability Analysis for diameter[1:25, ] LSL Target USL summary statistics R Chart for diameter[1:25, ] Sample Quantiles Normal Q-Q Plot Theoretical Quantiles diameter[1:25, ] Run chart Capability plot Center = StdDev = Target = 74 Process tolerance Cp = 1.46 Cp_k = 1.38 Specification limits Cpm =
31 > q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=false) > cusum(q) Cusum Chart for diameter[1:25, ] Cumulative Sum Below Target Above Target UDB LDB Number of groups = 25 Target = StdDev = Decision boundaries (std. err.) = 5 Shift detection (std. err.) = 1 No. of points beyond boundaries = 0
32 > q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=false) > process.capability.sixpack(q, spec.limits=c(73.95,74.05)) summary statistics xbar Chart for diameter[1:25, ] Process Capability Analysis for diameter[1:25, ] LSL Target USL summary statistics R Chart for diameter[1:25, ] Sample Quantiles Normal Q-Q Plot Theoretical Quantiles diameter[1:25, ] Run chart Capability plot Center = StdDev = Target = 74 Process tolerance Cp = 1.46 Cp_k = 1.38 Specification limits Cpm =
33 > q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=false) > ewma(q, lambda=0.2) EWMA Chart for diameter[1:25, ] Summary Statistics Number of groups = 25 Target = StdDev = Smoothing parameter = 0.2 Control limits at 3*sigma
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