The Total Quality Management (TQM) Customer-Focused Principles QFD including g The 7 Tools of TQM Q and Q
Where are You on this scale ? 1
What’s TQM
2
I’ve heard about TQM
3
I’ve read about TQM
4 5
II’ve ve attended some TQM training I’ve used some TQM tools
6
I have lots of experience with TQM
7
I taught Dr. Dr Deming everything he knows about TQM
2
Industrial Paradigm Production : “Mass” 1913
“Lean” 1960
“Flexible” “Reconfigurable” 1980
2000
Objective : “Knowledge Science” Computerization Production Management
“Interchangeable Parts”
Approach: 3
Competition Strategy
Cost
Quality
1800
1960
Delivery
1970
Flexibility/ Responsiveness
1980
1990
Innovation
2000 4
evolusi
TQM Quality Assurance inspection foremen operator
1900
1918
1937
1960
1980 5
QUALITY
Quality Control
Quality Assurance
Total Quality Control
T t l Quality Total Q lit Management M t 6
• Quality of design • Quality of conformance
1 Performance 1. P f 2. Feature 3 Reliability 3. 4. Conformance 5 Durability 5. 6. Serviceability 7. Aesthetic 8. Perceived quality
7
Quality Control
Quality Assurance
PDCA
Quality Circle 8
•
Top Management Commitment
• Customer Focus • Performance measurement • Participative Management • Continuous Contin o s Impro Improvement ement
9
BASIC QUESTIONS IN THE TQM IMPLEMENTATION
• Who are my customer ? • What are the products/services I provide to my customers ? • What are their expectations of my product/service ? • Does D my product/service d t/ i consistently i t tl meett or exceed d their expectations ? • What tells me my product/service is improving ? • How do my work activities add value to the process ? • What actions are needed to improve my process ?
10
Internal Failure Costs
Ê Scrap Ê Rework External Failure Costs
Ê Warranty cost Ê Product liability Appraisal Costs
Ê Inspection costs Prevention Costs Ê Process improvement Ê Product P d t simplification i lifi ti Ê Training costs
Co ontinua al Imprrovem ment
Quality Costs Decline Ê Little or no defective work
Decline Ê No dissatisfied customers
Decline Ê Very little inspection
Increase Ê An ounce of prevention ti is i worth th a pound of cure
11
Cost per good unit of prod C duct
Quality Cost: Traditional View
Internal and external failure costs
Total quality costs
Prevention and appraisal costs
0
Quality level (q)
Minimum t t l costt total
Optimum quality level
100% 12
EIGHT TQM TOOLS 1. CHECK SHEET 2 HISTOGRAM 2. 3. DIAGRAM PARETO 4. DIAGRAM SEBAB AKIBAT 5. DIAGRAM G TEBAR 6. STRATIFIKASI 7. PETA KONTROL 8. QUALITY FUNCTION DEPLOYMENT (QFD) 13
SAMURAI WITH SEVEN PORTABLE WEAPONS + 1 INTENTION 14
Hoyo (Hood)
Kabuto (Helmet)
Gusoku (armor)
Tachi (long sword)
Y i (bow) Yumi (b )
Katana (sword)
Ya (arrow)
AN INTENTION
7+ 15
CHECK SHEET Fungsi Menyajikan data yang berhubungan dgn : • Distribusi proses produksi • Defective item • Defective location • Defective cause • Check up confirmation 16
CHECK SHEET
Date :
Product
:
Plant
:
Usage
:
Dept.
:
Specification :
Inspector :
Inspection number :
Lot No.
Lot Size
:
Supplier
:
:
Measurement unit : Weight (g)
Tally
Frequency
Total 17
HISTOGRAM 1. Guna : menyajikan data secara visual sehingga lebih mudah dilihat oleh pelaksanan 2. Mekanisme : 1.
Kumpulkan data pengamatan (N) ∑ data : minimum Æ • rumus statistik • tentukan 2 2. Pilih harga maksimum & minimum a) Susun data dalam baris & kolom b) Pilih angka max. Tiap baris c)) Pilih angka g min. tiap p baris d) Tentukan max & min dari keseluruhan 3. Hitung range ( R ) = max ↔ min 4. Tentukan jumlah kelas ( K ) K = f(R) = 1 + 3.3 log R Atau K= N atau K = 10 ~ tentukan 18
5.
Tentukan kelas interval ( KI) KI = R/K
6.
Tentukan batas bawah KI terendah BB = min – KI/2
7.
Tentukan BB, batas atas dan setiap nilai kelas KI
K? min
NT
max
8.
Kelompok data setiap kelas = f(data) nyatakan “tally – mark”
9.
g f ( frekwensi ) Hitung X (minus, 0, plus)
10. Hitung rata-rata & tandar deviasi
19
Gambarkan histogram dari data berikut ini : Data
max
min
12
11
12.5
14
13.5
14
11
11
11.5
12
18
19
19
11.5
11
12
12
11.5
13
13
11
14
15
12
11
18
18
11
13
12
14.5
13.5
14.5
14.5
11.5
9
10 5 10.5
95 9.5
10 5 10.5
11
11
9
10
11
12
13
14
14
10
14
13.5
15
16
17
17
13.5
11
12
12
11.5
10
12
10
• R = max ↔ min = 19 ↔ 9 (19 – 9 = 10) • K =
N
= 50/7 ≈ 7,….
Æ8
• KI = R/K = 10/7 = 13/7 ≈ 1.5 • BB = 9 – 1.5/2 = 8.25 • BA A = 99.75
dst untuk setiap i kelas. 20
Batas Kelas
NT
Tallies
8 25 – 9.75 8.25 9 75
9
II
2
9.75 – 11.25
10.5
IIII IIII
10
11.25 – 12.75
12
……
17
12.75 – 14.25
13.5
……
11
14.25 – 15.75
15
……
5
15.75 – 17.25
16,5
……
2
17.25 – 18.75
18
……
2
18.75 – 20.25
19.5
……
1 50
X
f 17 10
11 5
2
2
8.25
2
≈ 10
1 20.25
X
= 12.78 , SD = 2.31 21
DIAGRAM PARETO ~ Petunjuk hierarki kepentingan persoalan cacat produk ~ Mekanisme 1. Buat klasifikasi cacat 2. Tentukan absis~ordinat 3 Buat diagram Æ % jumlah cacat 3. Kumulatif % cacat
a b c d e
~ manfaat • membuat orang mau bekerja sama • dampak perbaikan besar • identifikasi tujuan terpilih 22
Pareto Diagram Catatan produk cacat Date :
Jumlah yang diinspeksi N = 2160
Defective Item
Number of Defectives
Per cent Defective
Per cent of Compodition
Head defective (Hd)
99
4.6 %
47.4 %
Material defectives (Md)
13
06% 0.6
62% 6.2
Bolt defectives (Bd)
52
2.4 %
24.9 %
Corner defectives (Cd)
9
0.4 %
4.3 %
Length defectives (Ld)
36
1.7 %
17.2 %
209
9.7 %
99.9 %
(jumlah) 200
100 (%) 75
100
50 25
0 Hd Bd Ld Md Cd
0 23
C.E. DIAGRAM ~ MANFAAT : • mengarahkan diskusi faktor sebab domonan • petunjuk pengumpulan dan pencatatan data • menunjukkan kemampuan pekerja Menggambarkan hubungan sebab~akibat ~ GUNA • menganalisa kondisi aktual ¾ perbaikan mutu ¾ efisiensi sumber daya ¾ ⇓ biaya • eliminasi kondisi ~ cacat / keluhan konsumen • standarisasi 24
TAHAPAN 1. Kelompok analisa masalah 2. Anak panah 3. “tulang” Æ penyebab sebelah kanan Æ masalah mutu 4. Identifikasi 5. evaluasi
25
Fishbone Chart Airline Customer Service
26
SCATTERED DIAGRAM ~ MANFAAT : • mengarahkan diskusi faktor sebab dominan • petunjuk pengumpulan dan pencatatan data • menunjukkan kemampuan pekerja
Melihat hubungan antar faktor
27
No.
Reaction Temperature
Yield Y (%)
1
72.5
91.1
2
73.8
90.8
3
73.2
90.8
4
72.1
91.3
5
73 0 73.0
91 0 91.0
6
73.0
90.6
7
74.3
90.6
8
71.5
91.6
9
72.9
91.2
10
73.6
90.8
11
74.2
90.8
12
74.9 9
90.3 90 3
13
73.7
91.0
14
72.1
91.5
15
74.3
90.5
16
74.5
90.7
17
72.8
91.4
18
73.7
90.5
19
72.8
90.9
20
72.0
91.3
21
73.1
91.4
22
73.5
91.2
28
X X
X
X
X X X Reaction Temperature 29
STRATIFIKASI ~ MANFAAT : • mencari penyebab utama faktor kualitas • memisahkan data (kategorisasi) sesuai dengan kelompok datanya • memudahkan d hk pengambilan bil kkeputusan t Æ peta t kontrol k t l • mempelajari secara menyeluruh masalah yang dihadapi
30
kategorisasi
Stratifikasi
Mencari faktor penyebab utama
Grade A
Il strasi : Ilustrasi
Grade B Grade C
Grade D
31
Q alit Control Approaches Quality
Statistical process control (SPC) –Monitors the production process to prevent –poor quality
Acceptance sampling –Inspects a random sample of the product – to determine if a lot is acceptable 32
Statistical Process Control
Take periodic samples from a process
Plot the sample points on a control chart
Determine if the process is within limits
Correct the process before defects occur
33
T pes Of Data Types
Attribute data • Product characteristic evaluated with a discrete choice –
Good/bad, yes/no
V i bl d Variable data t • Product characteristic that can be measured –
Length size, Length, size weight weight, height height, time, time velocity
34
SPC Applied To Ser Services ices
Nature of defect is different in services
Service defect is a failure to meet customer requirements
Monitor times, customer satisfaction 35
Ser ice Quality Service Q alit Examples E amples
Hospitals –timeliness, responsiveness, accuracy
Grocery Stores –Check-out time, stocking, cleanliness
Airlines –luggage handling, waiting times, courtesy
Fast food restaurants –waiting times, food quality, cleanliness 36
PETA KONTROL ~ MANFAAT : • mengendalikan proses • kecenderungan k d proses • identifikasi kebutuhan konsumen
pH • • •
• • • • • t
37
Process Control Chart Upper control limit
Process average g
Lower control limit 1
2
3
4
5
6
Sample number
7
8
9
10 38
Patterns to Look for in Control Charts
39
Flow Diagram: g Statistical Process Control Steps Start
Produce Good Provide Service Take Sample
No Assign. A i Causes? Yes
Inspect Sample
Stop Process
Create Control Chart
Find Out Why
40
Constr cting a Control Chart Constructing
Decide what to measure or count Collect the sample data Plot the samples on a control chart Calculate and plot the control limits on the control c a chart Determine if the data is in-control If non-random variation is present present, discard the data (fix the problem) and recalculate the control limits 41
A Process Is In Control If
No sample points are outside control limits
M t points Most i t are near the th process average
About an equal q #p points are above & below the centerline
Points appear randomly distributed
42
The Normal Distrib Distribution tion
95 % 99.74 % -3σ
-2σ
-1σ
μ = 0 1σ 2σ 3σ
Area under the curve = 1.0 43
Control Chart Z Val Values es
Smaller Z values make more sensitive charts
Z = 3.00 3 00 is standard
Compromise between sensitivity and errors 44
Control Charts and the Normal Di ib i Distribution UCL
+3σ Mean
-3σ LCL
45
T pes Of Data Types
Attribute data (p-charts, c-charts) Product characteristics evaluated with a discrete choice (Good/bad, yes/no, count)
Variable data (X (X-bar bar and R charts) Product characteristics that can be measured (Length size, (Length, size weight weight, height height, time, time velocity)
46
Control Charts For Attrib Attributes tes
p Charts –Calculate C l l t percentt d defectives f ti iin a sample; l –an item is either good or bad
c Charts –Count number of defects in an item
47
p - Charts Based on the binomial distribution – p = number defective / sample size, n – p=
total no. of defectives p observations total no. of sample UCLp = p + 3 p(1-p)/n LCLp = p - 3 p( p(1-p)/n p)
pp-Chart Chart Calculations Proportion Sample Defect Defective 1 6 .06 2 0 .00 3 4 .04
..
20
..
18 200
UCL = p + 3 p( p(1-p) p) /n
..
.18 1.00
100 jeans in each sample
p = =
ttotal t ld defectives f ti total sample observations
200 = 0.10 0 10 20 (100)
= 0.10 + 3 0.10 (1-0.10) /100 = 0.190 LCL = p - 3 p(1-p) /n = 0.10 + 3 0.10 (1-0.10) /100 = 0.010
0.2
0.14 0.12 0.1 0 1 0.08 0.06 0.04
20
18
16
14
12
..
10
8
6
4
2
0.02 0 0
Prroportion d defective
0.18 0.16
Sample number 50
c - Charts
Count the number of defects in an item
Based on the Poisson distribution –c = number of defects in an item – c = total number of defects – number of samples –
UCLc = c + 3 c LCLc = c - 3 c
c - Chart Calculations Count # of defects per roll in 15 rolls of denim fabric Sample Defects 1 12 2 8 3 16 . . . . 15 15 190
12 67 c = 190/15 = 12.67 UCL = c + z c = 12.67 + 3 12.67 = 23.35 LCL = c - z c = 12.67 - 3 12.67 = 1.99
52
E ample c - Chart Example 24
18 15 12 9 6 3 14
12
10
8
6
4
2
0 0
Numb ber of defeccts
21
Sample number 53
Control Charts For Variables
Mean chart (X-Bar Chart) –Measures central tendencyy of a sample p
Range chart (R-Chart) –Measures M amountt off dispersion di i iin a sample l
Each chart measures the process differently differently. Both the process average and process variability must be in control for the p process to be in control. 54
Example: Control Charts for Variable Data Sample 1 2 3 4 5 6 7 8 9 10
Slip Ring Diameter (cm) 1 2 3 4 5 5.02 02 5.01 01 4.94 9 4.99 99 4.96 96 5.01 5.03 5.07 4.95 4.96 4 99 5.00 4.99 5 00 4.93 4 93 4.92 4 92 4.99 4 99 5.03 4.91 5.01 4.98 4.89 4.95 4.92 5.03 5.05 5.01 4.97 5.06 5.06 4.96 5.03 5.05 5.01 5.10 4.96 4.99 5 09 5.10 5.09 5 10 5.00 5 00 4.99 4 99 5.08 5 08 5.14 5.10 4.99 5.08 5.09 5.01 4.98 5.08 5.07 4.99
X 4.98 98 5.00 4 97 4.97 4.96 4.99 5.01 5.02 5 05 5.05 5.08 5.03 50.09
R 0 08 0.08 0.12 0 08 0.08 0.14 0.13 0.10 0.14 0 11 0.11 0.15 0.10 1.15
Constr cting an Range Chart Constructing UCLR = D4 R = (2.11) (.115) = 2.43 LCLR = D3 R = (0) ((.115) 115) = 0 where h R = Σ R / k = 1.15 1 15 / 10 = .115 115 k = number of samples = 10 R = range = (largest - smallest)
56
3 Control Chart Factors 3σ Sample size n 2 3 4 5 6 7 8
X-chart A2 1.88 1.02 0.73 0.58 0 48 0.48 0.42 0 37 0.37
R-chart D3 0 0 0 0 0 0.08 0 14 0.14
D4 3.27 2.57 2.28 2.11 2 00 2.00 1.92 1 86 1.86 57
E ample R-Chart Example R Chart UCL
0,3 0,25
R Range
0,2
R
0,15 0,1 0,05 0 1
2
3
4
5
6
7
8
9
10
LCL
Sample number
58
Constructing A Mean Chart UCLX = X + A2 R = 5 5.01 01 + (0 (0.58) 58) ((.115) 115) = 5 5.08 08 LCLX = X - A2 R = 5.01 - (0.58) (.115) = 4.94 where X = average of sample means = Σ X / n = 50.09 / 10 = 5.01 R = average range = Σ R / k = 1.15 / 10 = .115
59
E ample X-bar Example X bar Chart 5,10
UCL
5,08 Sam mple average
5,06 5,04 5,02
X
5,00 4 98 4,98 4,96 4,94
LCL
4 92 4,92 1
2
3
4
5
6
7
8
9
10
Sample number
60
Penyebaran y Fungsi g Kualitas
Needs
1. Produsen mengharapkan konsumen mengubah keinginan menjadi permintaan yang dapat dimengerti
2. Konsumen menyatakan dengan baik keinginan mereka tetapi produsen tidak memuaskan k keinginan k mereka k
Requirements
Needs Requirements
Build to Requirements
User Specification Developer 62
Alat utama QFD
CUSTOMER INFORMATION TECHNICAL INFORMATION
Rumah Kualitas
• Suatu proses perencanaan • Input: keinginan dan kebutuhan konsumen • Penggunaan matriks untuk mencatat informasi penting • Memungkinkan analisa dan penentuan isu-isu utama • O Outt putt : iisu-isu i tindakan ti d k kunci k i untuk t k memperbaiaki b i ki kepuasan k konsumen berdasarkan input konsumen
63
Identifikasi keinginan pelanggan Mempelajari ketentuan teknis dalam menghasilkan barang ba ang atau ata jasa Hubungan antara keinginan dan ketentuan teknis Perbandingan kinerja dengan pesaing Evaluasi Pelanggan Trade off
64
Trade off
Karakteristik proses
H A R A P A N
EVALUASI PELANGGAN
Lakukan analisa
MATRIKS HUBUNGAN
PERBANDINGAN KINERJA PERUSAHAAN TINGKAT KEPENTINGAN NILAI RELATIF
65
Mendengarkan M d k S Suara K Konsumen (V i (Voice off Customer) C t ) untuk t k menentukan harapan pelanggan Caranya: Penentuan konsumen ahli Wawancara dengan g konsumen ahli
Judgement Sampling Hasil wawancara : Atribut kualitas
Pembobotan dengan de ga metode etode perbandingan berpasangan
Cara perhitungan pembobotan: Membuat skala perbandingan yang disebt skala fundamental yang diturunkan berdasarkan riset psikologis atas kemampuan individu dalam membuat suatu perbandingan secara berpasangan terhadap beberapa elemen yang di b di k diperbandingkan. Sk l perbandingan Skala b di t b t adalah tersbut d l h ;1: 1 sama penting, ti 2 sedikit 2: dikit lebih penting, 5: lebih penting, 7: jauh lebih penting, 9: sangat lebih penting, 66 angka 2, 4,6,8 adalah nilai atara
Cara Penentuan Hubungan Keterkaitan dan Trade Roof
Brainstorming dengan manager ahli yang mengetahui secara mendalam mengenai proses produksi 1. Hubungan Keterkaitan Hubungan antara harapan pelanggan dan karakteristik proses dapat dinyatakan dengan menggunakan lambang-lambang tertentu untuk menyatakan hubungan. Lambang dan nilai yang umum digunakan adalah sebagai berikut. = 10 = Hubungan Kuat = 5 = Hubungan sedang = 1 = Hubungan g lemah Penentuan kuat, sedang dan lemah dikerjakan dengan membuat pertanyaan apakah dengan mengerjakan karakteristik proses ini maka dapat memuasakan harapan pelanggan. Harus diterapkan setiap kolom antara satu karakteristik proses dengan harapan 67 pelanggan
+
: kuat (10) : sedang (5) : lemah (1)
+ +
+ +
+ +
+
I
Harapan pelanggan
+ +
II
+
+ +
+ +
+ +
+ +
+ +
+ +
+
III
IV
+ + +
+ +
+ +
+ +
V
VI
+ +
+ +
+ +
+
+ +
VII
VIII
PT SM; PT A; PTB
Targe; Rasio
Kesegaran
6
5; 4; 5
5,1
Kebersihan
5
5; 4; 5
5,1
Keamanan pangan
5
3; 3; 3
4,1
Warna
4
4; 3; 4
4,1
Daya tahanproduk
3
4; 4; 4
4,1
Ukuran seragam
2
4; 3; 4
4,1
Bentuk standar
1
4 3; 4; 3 4
41 4,1
PT SM
5
4
4
5
5
5
5
PT A
5
4
4
4
4
5
4
PT B
5
4
4
5
5
5
5
NILAI (Ti (Tingkat k tk kepentingan) ti )
12 0
230
55
150
205
230
125
Nilai Relatif
0.108
0.206
0.049
0.135
0.184
0.206
0.112
Keterangan : I.
BOBOT KONVERSI
IV. PENERIMAAN
VII. PENYIMPANAN
II PENGADAAN BAHAN BAKU II.
V SORTASI V.
VIII DISTRIBUSI VIII.
III. PENANGANAN BAHAN BAKU
VI. PENGEMASAN
Gambar Rumah Kualitas Sayuran Segar PT. SM
68
+
Rumah Kualitas Ban PT. G.Y
+ + + + +
Harapan pelanggan
+
+ +
+
: kuat (10) : sedang (5) : lemah (1)
+ + + + +
+ + +
Proses Produksi
PT X;A;B;C ; ; ;
Target ; Rasio
Atribut Pelanggan
I
Keselamatan
5
4; 4; 4; 4
4; 1
Kekuatan
4
2; 5; 4; 5
5;; 2,5 ,
Kenyamanan
3
3; 5; 4; 4
5; 1,66
Desain
2
4; 4; 3; 3
4; 1
Harga
2
4; 4; 4; 3
4; 1
II
III
IV
V
VI
VII
PT .X
3
4
4
4
3
PT. A PT.B
4
5
5
4
4
5
4
5
5
3
4
4
PT.C
4
5
4
2
4
4
140
120 18,8
NILAI (Tingkat kepentingan) Nilai Relatif
97 15,2
95 14,9
105 80 16,5 12,6
21,9
4
Keterangan : I Bobot B b Konversi II Pencampuran III Pelapisan IV Penggabungan V Penyemprotan VI Pemasakan69 VII Pengujian
•Marimin, 2004, Teknik dan Aplikasi Pengambilan Keputusan Kriteria Majemuk, Grassindo.
70
• Pilih kasus industri yang anda paling kuasai • Susun salah satu alur proses produksi atau sistem pengelolaannya • Rancang QFD-nya QFD nya • Diskusikan matrik QFD yang telah anda rancang tersebut. b •Kendalikan respon teknik dominan/kritis dengan Statistical process control. 71
