كتاب World Class Quality
منتدى هندسة الإنتاج والتصميم الميكانيكى
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منتدى هندسة الإنتاج والتصميم الميكانيكى
بسم الله الرحمن الرحيم

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وتسعدونا بالأراء والمساهمات
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وشرح لطريقة التنزيل من المنتدى بالفيديو:
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الرئيسيةالبوابةالتسجيلدخولحملة فيد واستفيدجروب المنتدى

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 كتاب World Class Quality

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كاتب الموضوعرسالة
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تاريخ التسجيل : 01/07/2009
الدولة : مصر
العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى

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مُساهمةموضوع: كتاب World Class Quality    كتاب World Class Quality  Emptyالجمعة 24 سبتمبر 2021, 9:58 pm

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World Class Quality
SECOND EDITION
Using Design of Experiments to Make It Happen
Keki R. Bhote, Adi K. Bhote

كتاب World Class Quality  W_c_q_10
و المحتوى كما يلي :


Contents
List of Figures ix
List of Tables xiii
Foreword by Bob Galvin xvii
Preface to the Second Edition xix
Acknowledgments xxiii
Part I Introduction
1. The Need for and Objectives and Benefits of
Design of Experiments 3
2. Fads, Potions, Nostrums of the Quality
Movement in the Last 50 Years 10
3. A Powerful Tool Kit for the 21st Century 19
Part II Preamble to the Design of Experiments
4. The Measurement of Process Capability 51
5. Variation: An Industrial Epidemic 65
6. The Three Approaches to DOE: Classical,
Taguchi, and Shainin 73
7. A Synopsis of the 10 Powerful DOE Tools 86
Part III ‘‘Talking to the Parts’’—A Set of Clue-Generating
Tools
8. The Multi-Vari Analysis: Homing In on the
Red X 107
vvi Contents
9. The Concentration Chart: Pinpointing
Locations of Repetitive Problems 147
10. Components Search: Simple, Smooth
Swapping 157
11. Paired Comparisons: An Elegant, Versatile
Tool 194
12. Product/Process Search: Pinpointing Process
Variables 217
Part IV Formal Design of Experiments Techniques to
Characterize a Product/Process
13. Variables Search: The Rolls Royce in the Search
for the Red X 233
14. The Full Factorial: Purest Technique for
Separating and Quantifying Each Interaction
Effect 282
15. B versus C: An Excellent Validation Technique 309
Part V DOE Optimization
16. Scatter Plots to Achieve Realistic Specifications
and Tolerances 335
17. Response Surface Methodology (RSM): To
Optimize Interactions 355
Part VI The Transition From DOE to SPC: Vital
Disciplines
18. Positrol: Freezing Process Gains 369
19. Process Certification: Eliminating Peripheral
Causes of Poor Quality 378
Part VII Statistical Process Control: For Monitoring
Quality
20. Control Charts: A Technique Whose Time Has
Gone 393
21. Pre-Control: A Technique Whose Time Has
Come 399Contents vii
Part VIII Linkage of DOE to Reliability
22. Multiple Environment Over Stress Tests: As
Effective for Reliability as DOE Is for Quality 421
Part IX A Logical Sequence in the Use of DOE Tools
23. Case Studies in Sequential DOE Tools to Solve
Chronic Problems 445
Part X From Classroom Instruction to True Learning on
the Job
24. Learning by Doing 467
References 479
Index 4
Contents
List of Figures ix
List of Tables xiii
Foreword by Bob Galvin xvii
Preface to the Second Edition xix
Acknowledgments xxiii
Part I Introduction
1. The Need for and Objectives and Benefits of
Design of Experiments 3
2. Fads, Potions, Nostrums of the Quality
Movement in the Last 50 Years 10
3. A Powerful Tool Kit for the 21st Century 19
Part II Preamble to the Design of Experiments
4. The Measurement of Process Capability 51
5. Variation: An Industrial Epidemic 65
6. The Three Approaches to DOE: Classical,
Taguchi, and Shainin 73
7. A Synopsis of the 10 Powerful DOE Tools 86
Part III ‘‘Talking to the Parts’’—A Set of Clue-Generating
Tools
8. The Multi-Vari Analysis: Homing In on the
Red X 107
vvi Contents
9. The Concentration Chart: Pinpointing
Locations of Repetitive Problems 147
10. Components Search: Simple, Smooth
Swapping 157
11. Paired Comparisons: An Elegant, Versatile
Tool 194
12. Product/Process Search: Pinpointing Process
Variables 217
Part IV Formal Design of Experiments Techniques to
Characterize a Product/Process
13. Variables Search: The Rolls Royce in the Search
for the Red X 233
14. The Full Factorial: Purest Technique for
Separating and Quantifying Each Interaction
Effect 282
15. B versus C: An Excellent Validation Technique 309
Part V DOE Optimization
16. Scatter Plots to Achieve Realistic Specifications
and Tolerances 335
17. Response Surface Methodology (RSM): To
Optimize Interactions 355
Part VI The Transition From DOE to SPC: Vital
Disciplines
18. Positrol: Freezing Process Gains 369
19. Process Certification: Eliminating Peripheral
Causes of Poor Quality 378
Part VII Statistical Process Control: For Monitoring
Quality
20. Control Charts: A Technique Whose Time Has
Gone 393
21. Pre-Control: A Technique Whose Time Has
Come 399Contents vii
Part VIII Linkage of DOE to Reliability
22. Multiple Environment Over Stress Tests: As
Effective for Reliability as DOE Is for Quality 421
Part IX A Logical Sequence in the Use of DOE Tools
23. Case Studies in Sequential DOE Tools to Solve
Chronic Problems 445
Part X From Classroom Instruction to True Learning on
the Job
24. Learning by Doing 467
References 479
Index
acceptable quality level (AQL), 10
accuracy, of measurement, 97–102
affinity diagram, 26
alpha () risk, 313, 315, 404
analysis of variance (ANOVA), 83
arrow diagram, 27
attributes, conversion from, 102
B versus C: 309–22; alpha () risk, 313,
315; applications in administrative
services, 329; beta () risk, 313–17;
confidence, risk, and end-count,
317; importance of validation, 309;
increasing sample sizes to reduce
B and C separation, 320; more than
two alternatives, 323; opinion surveys, 330; overlap and no overlap
rules, 316; stress test to failure, 327;
when C is worse than B, 323
baby sigma practices, 17
balance, in experimentation, 283
ball park stage, 161
benchmarking, 34–36
beta () risk, 313, 315, 317, 406
Bhote, Keki, 14, 477, 478
Big Q (Bhote) Quality System, 14
brainstorming, 4, 16, 22
business excellence, 17
business process engineering, 40
capability, process, 51–64, 401
case studies: appliance servicer, 278;
automotive styling, 330; bubbles in
glass, 223; bushing, 394; car com-
481
pany’s ice cream fiasco, 178–82;
contact lens, 266; cracked epoxy,
260, 317; customer loyalty/satisfaction/profit, 351; customer services at hotel, 141; dairy farm
bacteria levels, 211; Dendermonde,
Belgium, 475–76; die casting, 376;
disc brake, 309; dome tweeter sensitivity, 457–64; edge defects in
contact lenses, 336; electric razor,
103; foam leaks in refrigerator
door, 148; Ford versus Mazda, 52;
four megabit dynamic RAM, 203;
F-16 fighter jet, 53; gear train
motor, 327; hospital billing errors,
140; hourmeter, 165; ignition amplifier, 343; instrument intermittency, 274; lettuce bag leakage,
220; maximizing Schottky diode
yields, 357; micro-motor noise,
199; moire effect minimization,
295; Motorola six sigma, 76–79;
Nippon Telegraph & Telephone
(NTT), 53; non-firing burner, 177;
operator performance differences,
189; pick and place machine, 273;
plastic injection molding machine,
373; press brake, 250, 320; radio
‘‘no trouble found,’’ 126; refrigerator door gaps, 187; rotor shaft, 121;
SCAP metallization, 384; sensor
capacitance, 396; shorted horizontal output transistor, 154; software
applications, 271; spring torque482 Index
difference, 189; ‘‘tombstone’’ defects, 139, 265; travel motor, 273;
university recruitment drive, 155;
wave solder defects, 148, 288,
447–57
cause and effect diagrams: CEDAC, 23,
24; futility, 109, 110; Ishikawa, 109,
110
circuit analysis, 3
classical DOE, 70, 73–85, 235
combination formula, 197, 312
commodity teams, 42
comparison of three DOE approaches,
73–85
Components Search: 157–93; applications in administrative work, 196;
applications in processes/lines,
188; applications when disassembly/re-assembly not repeatable,
186; bypassing the Multi-Vari, 158;
capping run, 162, 164; decision
limits, 167; determining correct
specifications, 176; factorial analysis, 173; four stages of, 161; graphical plots, 167; main and interaction
effects, 171; prerequisites, 162; procedure in 12 steps, 163–64; quiz:
‘‘find the Red X ball,’’ 190–92
computer simulation: 3, 5, 69, 73;
Monte Carlo, 70, 73
Concentration Chart: 147–56; applications in administrative work,
154–55; construction of, 147–48;
‘‘measles’’ chart, 147
confounding, 235–36
control charts: disadvantages vis-a`-vis
Pre-Control, 412, 413; history, 393;
slip-shod practices, 397–98; weaknesses, 393–97
correlation, 351–53
cost of poor quality, 7, 54, 76
cost reduction, 7, 8, 78
C
p, Cpk: 5, 7, 12, 54–64; calculations, formulas, 54–59; correction factor, K,
57; pitfalls to avoid, 59–60; relationship between Cp, ppm, and
sigma, 56
culture, problem solving: 467–78; conversion of the design engineer,
472; energizing, 468; learning by
doing, 467–75; line worker contribution, 475; managing complex
change, 468; practice, practice,
practice, 467; skunk works, 475;
top management commitment, 469
customer: internal customer, 39, 40;
loyalty/satisfaction, 7, 9, 351–53;
mass customization, 32; Next Operation as Customer, 3, 5, 36, 39,
40; quality function deployment,
29, 32
cycle-time reduction: 6–9, 39–46; flow
charting, 40, 42; MRP II, 45, 46;
push-pull, 45
data collection/analysis, 20
decision limits, 167
Deming, Dr. W. Edwards, 65, 380, 476,
477
design engineering: conversion of, 472,
473; DOE in design, 233–81,
335–54; importance of DOE to, 7,
8; ‘‘parts are smarter than the engineers,’’ 7, 8; product/process characterization, 5, 233–81; product/
process optimization, 5, 335–54;
traditional approach to problem
solving, 28
Design of Experiments (DOE): benefits,
7–9; block diagram, 87; case studies, see case studies; classical DOE,
74–85; clue generation techniques,
105–6; comparison of three DOE
approaches, 73–85; Components
Search, see Components Search;
continuum of linked tools, 445–64;
C
p, Cpk, see Cp, Cpk; Evolutionary
Operation (EVOP), 351–61; fraction factorials: weaknesses,
234–40; Full Factorials, see Full
Factorial; generic problem-solving
framework, 89; Green Y, 93; instrumentation accuracy, 109–13; logical sequence in DOE, 445–64;Index 483
Multi-Vari analysis, see Multi-Vari
analysis; need for, 3–5; objectives,
6, 7; Paired Comparisons, see
Paired Comparisons; Pale Pink X,
93; Pink X, 93; Positrol, see Positrol;
problem-solving roadmap, 95;
Process Certification, see Process
Certification; product/process
characterization, 3, 5, 33, 317, 318;
product/process optimization, 3,
5, 33, 429; Product/Process Search,
see Product/Process Search; randomization, 81, 284; Red X, 93;
replication, 283; Response Surface
Methodology, see Response Surface Methodology; root cause
identification, 445; simplex,
361–63; Taguchi DOE, see Taguchi
DOE; ten DOE tools summary,
90–92; three approaches to DOE,
74–85; Variables Search, see Variables Search; workshop exercises,
see workshop exercises; workshops in DOE, 470–72
destruct limits, 429
early supplier involvement (ESI), 42
8-D, see under Ford
elimination stage, 161
employees: brain fertility, 474; error
cause removal, 379; human shortcomings, 380, 383; involvement,
28, 77; joy in the workplace, 476,
477; Kaizen, 28; morale, 6, 8, 9,
473–77; Quality Circles, 28; skunk
works, 475; Total Customer Satisfaction competition, 78
end-counts, 196, 201
environmental neglect, 379, 382
equipment inattention, 379, 382
error cause removal (ECR), 379
errors: type I and II, 313
European Quality Award, 11, 12, 15
Evolutionary Operation (EVOP),
351–61
excellence, business, 14, 17
factorial analysis, 173, 246
factory overall efficiency (FOE), 33
failure mode effects analysis, 5, 6, 422
Fisher, Sir Ronald, 74
flow chart, 40
Ford: 25, 52–53, 74, 88; 8-D, 25, 74, 88;
versus Mazda, 52; fraction factorials: weaknesses, 234–40
frequency distributions, 21
Full Factorial: 234, 287–308; balance,
283; fraction factorials: weaknesses, 234–40; limitations, 282;
methodology, 287; objectives, 283;
principles, 283; randomization, 81,
284; replication, 287
fundamental weaknesses of classical
and Taguchi DOE, 78–85
Galvin, Robert W., 76, 77, 468
glass wall management, 381
good manufacturing practices, 379, 381
graphics, 20
Green Y, 93
Highly Accelerated Life Tests (HALT),
427–30, 437–39
Highly Accelerated Stress Screens
(HASS), 430, 437–39
histograms, 21
House of Quality, 30, 31
improvement, quality, 5, 7, 8, 9
improvement, reliability, 5, 7
Institute of Environmental Science
guidelines, 422
interaction effects, 393–98
internal customer, 39, 40
ISO-9000, 11, 381
Japanese, 19, 28
Japanese seven management tools, 19,
25–27
Juran, Dr. Joseph M., 65, 89
Kaizen, 19, 381
Kepner-Tragoe, 4, 74, 78484 Index
leadership, of Bob Galvin, 76, 77, 468
learning by doing, 467–77
Likert scale, 102–4, 114
log, Positrol, 370
logical sequence of DOE tools, 443–64
main effects, 393–98
Malcolm Baldrige National Quality
Award, 11, 15
management: commitment and
involvement, 469–72; comparison
of three quality systems, 15–18;
poor management, 65, 66, 379–81;
production management, 473, 474;
quality management, 473; seven
tools of Japanese management, 19,
25–27, 70
manufacturing management: 379–82,
473, 474; actions required, 473, 474;
poor manufacturing practices, 65–
68, 379–82
mass customization, 32
matrix diagram, 27
Mazda versus Ford, 52
‘‘measles’’ chart, 147
measurement: accuracy check list, 101,
116–18; bias, precision, discrimination, 98; Likert scale, 102–4
measurement accuracy, 97–102
Motorola: cost of poor quality, 76; Galvin, Bob, 76–77; quality improvement 10:1 to 1,000:1, 76–78; six
sigma, 12, 75–78
Multiple Environment Over Stress Test
(MEOST): HALT/HASS versus
MEOST, 437–39; history, objectives, benefits, 430–33; maximum
practical over stress limit, 430;
methodology, a roadmap, 433–34;
seven stages, 434–38; tie-in with
DOE, 438, 440
multiple regression analysis, 351
Multi-Vari analysis: 107–46; applications in administrative work, 140;
card trick analogy, 107–9; constructing a Multi-Vari chart,
119–21; designing/conducting a
Multi-Vari study, 112–14; family
tree, 113–16; principles, 107–9;
sample sizes and frequency,
114–16; three families of variation,
111–12
Next Operation As Customer (NOAC),
39, 40
nonparametric experiments, 309–22
no overlap technique, 316
null hypothesis, 311
numeric scale, converting attributes to,
102–4
operator certification, 381
operator errors, 71
optimization of products/processes,
335–54
orthogonal array, 79, 234
out-of-box thinking, 40
overlap technique, 316
Paired Comparisons: 194–216; applications in administrative services,
210; combination formulas, 197,
312; methodology: A and B, 195;
Tukey test, 196, 207
Pale Pink X, 89, 93
Pareto’s law/principle, 22, 89, 90, 94
Peterson, Don, 53
Pink X, 89, 93
Plan, do, check, act (PDCA), 20
positional variation, 111
Positrol: 89, 369–77; chart, 370; concept,
369; plan, 369
Pre-Control: 6, 399–418; advantages
over control charts, 410; alpha ()
risk, 404; beta () risk, 406; charting, 408; discovery, 399; mechanics, 400; modifications, 403;
opposition to, 409; theory, 404
problem solving: chronic, 6; culture,
468–469; energizing a culture for,
468; engineering approach, 28; generic process for, 97; prevention, 6,
7; roadmap, 95; three approaches
to, 73–85; worker involvement, 28Index 485
process capability, 51–64, 402
Process Certification: 378–90; audits,
383; environmental neglect, 382;
error cause removal (ECR), 381;
good manufacturing practices violation, 381; methodology, 383;
Murphy’s law, 378; operator certification, 381; peripheral causes of
poor quality, 378–80; plant/equipment inattention, 382; scrubs, 383
process mapping, 40
productivity, 6
product/process characterization, 3, 5,
33, 317, 318
product/process optimization, 3, 5, 33,
429
Product/Process Search: 217–30; methodology, 218; principles, 217;
when individual process parameters cannot be measured, 219
profitability, 6, 7, 8
quality: acceptable quality level (AQL),
10; ‘‘baby’’ six sigma system, 13,
17; big Q (Bhote) quality system,
14; cost of poor quality, 7, 54, 76;
fads, 10–15; Ford 8-D, 25, 74, 88;
House of Quality, 30, 31; improvement, 5, 7–9; ISO-9000, 11, 15;
parts per billion (ppb) defects, 6;
parts per million (ppm) defects, 6;
poor systems and tools, 70; Quality Circles, 28; quality function deployment, 29–32; quality
management, 473; QS-9000, 12, 15;
relationship: Cp, sigma, and defect
levels, 56; sampling plans, 10; six
sigma systems, 12, 13, 16, 17; systems, comparisons of three, 17;
Total Quality Management (TQM),
12, 13, 17; ultimate six sigma, 13,
17; yields, 6; zero defects movement, 10, 18
Random Evolutionary Operation
(REVOP), 363
randomization, 81, 284
rank order, 102, 196
Rath and Strong, 399
R chart, 394–96
realistic tolerances, 335–54
Red X, 89, 93
reliability: failure mode effects analysis
(FMEA), 5, 6, 422; fault tree analyses (FTA), 5; Highly Accelerated
Life Tests (HALT), 427–30; importance of, 8, 9, 421; mass life testing,
3, 422; Miner’s equation, 424; Multiple Environment Over Stress Test
(MEOST), see MEOST; relationship
of failure to stress, 424; reliability
prediction studies, 5, 422; revolutionary test principles, 423–27;
shortcomings in traditional reliability, 421; thermal cycling, 425;
versus quality, 421; vibration,
425–27
Response Surface Methodology (RSM):
355–66; approaches, 355; Evolutionary Operation (EVOP),
356–61; objectives, 355; Random
Evolutionary Operation (REVOP),
363; simplex, 361–63
Scatter Plots: 335–54; administrative
applications, 350; correlations, 339;
methodology, 337; multiple regression analysis, 351; objective,
335; realistic specifications/tolerances, 335
Shainin, Dorian, 75
Shainin DOE, strengths, 74–85
Shewhart, Walter, 393
sigma, 56
simplex, 361–63
six sigma systems, 12, 13, 16, 17
space reduction, 7, 8
specifications: determining correct,
176; determining realistic, 335–54;
poor component, 68–70; poor
product, 68–70; target values, 52,
53; worst case tolerances, 4
spider chart, 8, 9
statistical process control (SPC): 6, 74,486 Index
78, 391–418; control charts, 393–98;
Pre-Control, 399–418; transition
to, 391–418; stress test to failure,
95, 438–41
supply management: benefits, 7; commodity teams, 42; early supplier
involvement (ESI), 42; importance
of, 7–9; poor suppliers, 71–73
support services, 39, 40
table, of random numbers, 286
Taguchi, Dr. Genichi, 75
Taguchi DOE: 70, 75, 297, 298; comparisons with classical and Shainin
DOE, 74–85; fundamental weaknesses, 78–85; orthogonal array,
79, 234
tally sheets, 21
thermal cycling, 425
tolerances: build-up, of, 54; geometric,
4; important/unimportant parameters, 3; loose/tight, 40; realistic, 4,
438–41; worst case, 4
tools: awareness, implementation, 47;
benchmarking, 35–36; brainstorming, 4, 16, 22; cause and effect diagrams, 23, 109, 110; CEDAC, 24;
check sheets, 21; classical DOE, 70,
73–85, 235; control charts, see control charts; cycle-time reduction,
45–46; data collection/analysis,
20; Design of Experiments (DOE),
see Design of Experiments; Ford 8-
D, 25, 74, 78, 88; graphs/charts, 20;
histograms/frequency distributions, 21; interrelationship diagram, 26; Kepner-Tragoe, 4, 78;
matrix diagram, 27; Multiple Environment Over Stress Test
(MEOST), see MEOST; Next Operation As Customer (NOAC), see
NOAC; Pareto charts, 22, 89, 92, 94;
plan, do, check, act (PDCA), 20;
Poka-Yoke, 36–38; Pre-Control, see
Pre-Control; process decision program chart, 27; quality function
deployment, 29–32; seven management tools, 19, 25–27, 70; seven
tools of Q.C., 4, 19–24, 70; Shainin
DOE, 74–85; statistical process
control (SPC), see SPC; supply
management, see supply management; Taguchi DOE, 70–75, 297,
298; tally sheets, 21; tool kit for the
21st century, 28–47; Total Productive Maintenance, 7, 8, 9, 32–34;
transition from DOE to SPC, 95,
369–90; tree diagram, 27; value engineering, total, 42–44
Total Productive Maintenance (TPM),
7, 8, 9, 32–34
total quality management, 12–15
Tukey test, 196, 207
type I and II errors, 313
ultimate six sigma, 13–14
validation, 309
value engineering, 42–44
variation: evil, 48; industrial epidemic,
65–72; poor management of,
65–68; poor manufacturing practices, 70; poor specifications,
68–70; poor suppliers, 71; target
value, 50; temporal, 112
Variables Search: 233–81; advantages
over fraction factorials, 9, 234–40,
283; analogy with medical/pharmaceutical work, 276; binary
search, 240; capping run, 246; common mistakes, 254; decision limits,
245; factorial analysis, 246; four
stages, 241; graphical plots, 254;
interaction effects, 247; methodology, 241; objectives, 239; product/
process characterization, 248; software applications, 271; test of significance, 244; Variable Search plus
Paired Comparisons, a derivative
DOE technique, 271
vibration tests, 425–27
white-collar quality, cost, cycle time,
35, 39, 40Index 487
workers, see employees
workshop exercises: belt passivator,
133; bushing, 414; car company ice
cream fiasco, 178; choice between
four suppliers, 324; CNC lathe,
374; contact lens, 201; digital circuit, 350; drilling operation, 298;
engine control module, 256; infrared soldering, 345; light emitting
diodes (LED), 63; memory chips,
386; oscillator time delay, 183; outof-square grills, 204; paint defects
on washing machine tub, 151;
paint yield optimization, 293; plastic injection molding machine, 226;
porcelain paint process, 385; press
brake, 60; printed circuit board
soldering, 374; Red X ball nos. 1
and 2, 190; screen print, 261; semiconductor wafer, 116; sensor capacitance, 415; shaft distortion
after heat treat, 153; spot welding,
268; tile adhesion, 129; walking
machine, 187; wire bond strength,
319
X bar charts, 394–96
zero defects movement, 10–11, 18


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كتاب World Class Quality
الرجوع الى أعلى الصفحة 
صفحة 2 من اصل 1

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منتدى هندسة الإنتاج والتصميم الميكانيكى :: المنتديات الهندسية :: منتدى الكتب والمحاضرات الهندسية :: منتدى الكتب والمحاضرات الهندسية الأجنبية-
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