5.-peta-kendali-atribut
TRANSCRIPT
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Peta Kendali ATRIBUT
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Outline• Overview• Peta P• Peta C
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ControlCharts
RChart
VariablesCharts
AttributesCharts
XChart
PChart
CChart
Continuous Numerical Data
Categorical or Discrete Numerical Data
Control Chart Types
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Konsep• Atribut : karakteristik kualitas yg
sesuai spesifikasi atau tidak
• Atribut dipakai jk ada pengukuran yg tidak mungkin dilakukan ( tidak dibuat) spt : goresan,apel yg busuk, kesalahan warna, ada bagian yg hilang
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Kelebihan• Dapat diterapkan di semua tgkt
organisasi , departemen, pusat kerja dan mesin operasional (tgk tertinggi – terendah)
• Membantu identifikasi permasalahan ( umum dan detil)
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Kelemahan• Tdk dapat diketahui sbrp jauh
ketidaktepatan dg spesifikasi tsb
• Ukuran sampel yg besar akan bermasalah jk pengukurannya mahal dan destruktif
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Tipe Peta Kendali ATRIBUT
1. Berdasar Distribusi BINOMIAL– Kelompok pengendali unit
ketidaksesuaian– Dinyatakan dalam proporsi (%)
– Menunjukkan proporsi
ketidaksesuaian dalam sampel / sub kelompok
p Chart
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2. Berdasar Distribusi POISSON– bagian ketidaksesuaian dalam unit
inspeksi– Berkaitan dg kombinasi ketidaksesuaian
berdasar BOBOT yg dipengaruhi banyak sedikitnya ketidaksesuaianc- Chart
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Tahapan….• Menentukan sasaran menentukan
karakteristik kualitasnya (ketidaksesuaian dalam proporsi atau unit)
• Memilih tipe peta kendali atribut• Banyaknya sampel dan observasi• Pengumpulan data• Penentuan BATAS KENDALI ( CL,UCL dan
LCL)• Interpretasi hasil (pola in/out of control)• Revisi jika perlu
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p/c Chart Structure
UCL
LCL
Process MeanWhen in Control
Center Line
Time
p/np/c Upper Control Limit
Lower Control Limit
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Outline• Overview• Peta P• Peta C
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Peta P
1. Jumlah sampel sama
•Proporsi diketahui•Proporsi tidak diketahui2.
Jumlah sampel berbeda
•Dihitung secara rata-rata•Dihitung secara individuPeta P
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1. Jumlah Sampel SAMA• Proporsi
diketahui• Garis Tengah =
p¯
pp
pp
pLCL
pUCL
3
3
pp pn
( )1
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Contoh : Ukuran sampel per grup = 50 ( p-
chart)No Banyak produk
cacatNo Banyak produk cacat
12345678910
4253213254
11121314151617181920
3552324
1043
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No Banyak produk cacat
Proporsi No Banyak produk cacat
Proporsi
12345678910
4253213254
0,08...........................
11121314151617181920
35523241043
0,06...........................
Total Proporsi ... Total Proporsi ...
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• p¯ = total proporsi / grup sampel = .072
• p = √ (0,072)(0,928)/50 = .037• BKA = 0,072 + 3(0,037) = 0,183• BKB = 0,072 - 3(0,037) = -
0,039 = 0
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1. Jumlah Sampel SAMA• Proporsi TIDAK diketahui
m = banyak grup sampel n = ukuran sampel (banyak sampel dalam grup) D = bagian tidak sesuai
p¯ = ∑Di/(mn) Garis Tengah = p¯
UCL p
LCL pp p
p p
3
3
p
p pn
( )1
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Example
Twenty samples, each consisting of
250 checks, The number of defective
checks found in the 20 samples are
listed below.(proporsi tidak diketahui)4 1 5 3 2 7 4 5 2 32 8 5 3 6 4 2 5 3 6
$115006529 25447581 1445
2655
Simon SaysAugusta, ME 01227
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• n = 250 sampel• m = 20 grup• D = total defect (semua defect dijumlah)• p¯ = ∑Di/(mn)
Estimated p = 80/((20)(250)) = 80/5000 = .016
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LCL = 3 .016 3(.007936) -.007808 0pp
(1 ) .016(1 .016) .015744 .007936250 250pp p
n
UCL = 3 .016 3(.007936) .039808pp
Note that thecomputed
LCLis negative.
$
115006529 25447581 1445
2655
Simon SaysAugusta, ME 01227
Control Limits For a p Chart
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Tdk sesuai
Proporsi Tdk sesuai
Proporsi
4153274523
(4/250) = 0,016
(1/250) =0,004
2853642536
(2/250) = 0,008
(8/250) = 0,032
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p Chart for Norwest Bank
0.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
0.040
0.045
0 5 10 15 20Sample Number
Sam
ple
Prop
ortio
n p UCL
LCL
Control Limits For a p Chart$
115006529 25447581 1445
2655
Simon SaysAugusta, ME 01227
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2. Sampel BEDA …
a. Metode RATA_RATA Ukuran sampel RATA -RATA dg perbedaan tidak terlalu besar -> ( n¯ = ∑n/observasi)
b. Metode INDIVIDU Batas Kendali tergantung ukuran sample tertentu shg UCL/LCL tidak berupa garis LURUS
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Ukuran sampel beda (p chart)
no sampel Produk cacat no sampel
Produk cacat
12345678910
200180200120300250400180210380
1410178201825203015
11121314151617181920
190380200210390120190380200180
15261014241518191112
Jml sampel 4860 Jml Cacat 341
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Metode Rata-rata• Sampel rata-rata n¯ = total sampel /observasi = 4860/20 = 243 p¯ = D/(n¯m) = 341 / (243.20) = 0,07 (CL) p = √ (0,07(0,93))/243 = 0,0164 BPAp = 0,07 + 3 (0,0164) = 0,119 BPBp = 0,07 - 3 (0,0164) = 0,021
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Metode Individu• Sampel rata-rata n¯ = total sampel /observasi = 4860/20 = 243 p ¯ = D/(n¯m) = 341 / (243.20) = 0,07 (CL) semua
titik sama• Control Limit (obs-1) (tergantung jml
sampel per grup) p = √ (0,07(0,93))/200 = 0,018 UCL = 0,07 + 3 (0,018) = 0,124 LCL = 0,07 - 3 (0,018) =
0,016……………….dst
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Tabel Proporsi untuk Grafik
No observasi sampel cacat proporsi1234567891011121314151617181920
200180200120300250400180210380190380200210390120190380200180
141017820182520301515261014241518191112
0,0700,0550,0850,067………………………………0,0950,0500,0550,067
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Outline• Overview• Peta P• Peta C
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C-chart
• Mengetahui banyaknya kesalahan unit produk sbg sampel
• Jumlah kesalahan per sample• Aplikasi : bercak pd tembok,
gelembung udara pd gelas, kesalahan pemasangan sekrup pd mobil
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C - chart
Number of defects per unit: c¯ = ∑ Ci / n
UCL cc c 3
LCL cc c 3
c c
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Example…c-chart
no Byknya kesalahan
no Byknya kesalahan
12345678910
547685651610
11121314151617181920
978119576108
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• c¯ = ∑c/n = 152/20 = 7,6• BPA c = (7, 6) + 3 (√7,6) = 15,87• BPB c = (7, 6) - 3 (√7,6) = -0,67 =
0
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TERIMA KASIH