The most important keywords used in this book are as follows: product, process, production system, productivity, reliability, availability, maintainability, risk, safety, failure modes a
Trang 1Springer Series in Reliability Engineering
Trang 2Professor Hoang Pham
Department of Industrial and Systems Engineering
Rutgers, The State University of New Jersey
96 Frelinghuysen Road
Piscataway, NJ 08854-8018
USA
Other titles in this series
The Universal Generating Function
in Reliability Analysis and Optimization
Gregory Levitin
Warranty Management and Product
Manufacture
D.N.P Murthy and Wallace R Blischke
Maintenance Theory of Reliability
Toshio Nakagawa
System Software Reliability
Hoang Pham
Reliability and Optimal Maintenance
Hongzhou Wang and Hoang Pham
Applied Reliability and Quality
Terje Aven and Jan Erik Vinnem
Satisfying Safety Goals by Probabilistic
Risk Assessment
Hiromitsu Kumamoto
Offshore Risk Assessment (2nd Edition)
Jan Erik Vinnem
The Maintenance Management Framework
Adolfo Crespo Márquez
Human Reliability and Error in portation Systems
Trans-B.S Dhillon
Complex System Maintenance Handbook
D.N.P Murthy and Khairy A.H Kobbacy
Recent Advances in Reliability and Quality
Poong Hyun Seong
Risks in Technological Systems
Torbjörn Thedéen and Göran Grimvall
Trang 3Riccardo Manzini · Alberto Regattieri Hoang Pham · Emilio Ferrari
Maintenance for
Industrial Systems
With 504 figures and 174 tables
123
Trang 496 Frelinghuysen RoadPiscataway NJ 08854-8018USA
hopham@rci.rutgers.edu
Prof Emilio FerrariUniversità di BolognaDipartimento Ingegneriadelle Costruzioni Meccaniche,Nucleari, Aeronautiche
e di Metallurgia (DIEM)Viale Risorgimento, 2
40136 BolognaItaly
emilio.ferrari@unibo.itISSN 1614-7839
ISBN 978-1-84882-574-1 e-ISBN 978-1-84882-575-8
DOI 10.1007/978-1-84882-575-8
Springer Dordrecht Heidelberg London New York
British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Control Number: 2009937576
© Springer-Verlag London Limited 2010
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Trang 5to Sara and Marta
Trang 6Billions of dollars are currently spent producing high-technology products and vices in a variety of production systems operating in different manufacturing andservice sectors (e g., aviation, automotive industry, software development, banksand financial companies, health care) Most of these products are very complex andsophisticated owing to the number of functions and components As a result, theproduction process that realizes these products can be very complicated.
ser-A significant example is the largest passenger airliner in the world, the ser-AirbusA380, also known as the “Superjumbo,” with an operating range of approximately15,200 km, sufficient to fly directly from New York City to Hong Kong The failureand repair behaviors of the generic part of this system can be directly or indirectlyassociated with thousands of different safety implications and/or quality expecta-tions and performance measurements, which simultaneously deal with passengers,buildings, the environment, safety, and communities of people
What is the role of maintenance in the design and management of such a uct, process, or system? Proper maintenance definitely helps to minimize problems,reduce risk, increase productivity, improve quality, and minimize production costs.This is true both for industrial and for infrastructure assets, from private to govern-ment industries producing and supplying products as well as services
prod-We do not need to think about complex production systems, e g., nuclear powerplants, aerospace applications, aircraft, and hospital monitoring control systems, tounderstand the strategic role of maintenance for the continuous functioning of pro-duction systems and equipment
Concepts such as safety, risk, and reliability are universally widespread andmaybe abused, because daily we make our choices on the basis of them, willingly
or not That is why we prefer a safer or a more reliable car, or why we travel with
a safer airline instead of saving money with an ill-famed company The acquisition
of a safer, or high-quality, article is a great comfort to us even if we pay more.The strategic role of maintenance grows in importance as society grows in com-plexity, global competition increases, and technological research finds new applica-tions Consequently the necessity for maintenance actions will continue to increase
in the future as will the necessity to further reduce production costs, i e., increaseefficiency, and improve the safety and quality of products and processes In particu-lar, during the last few decades the so-called reliability and maintenance engineering
vii
Trang 7viii Preface
discipline has grown considerably in both universities and industry as well as in
gov-ernment
The activities of planning, design, management, control, and optimization of
maintenance issues are very critical topics of reliability and maintenance
engineer-ing These are the focus of this book, whose aim is to introduce practitioners and
researchers to the main problems and issues in reliability engineering and
mainte-nance planning and optimization
Several supporting decision models and methods are introduced and applied: the
book is full of numerical examples, case studies, figures, and tables in order to
quickly introduce the reader to very complicated engineering problems Basic theory
and fundamentals are continuously combined with practical experience and exercises
useful to practitioners but also to students of undergraduate and graduate schools of
engineering, science, and management
The most important keywords used in this book are as follows: product, process,
production system, productivity, reliability, availability, maintainability, risk, safety,
failure modes and criticality analyses (failure modes and effects analysis and failure
mode, effects, and criticality analysis), prediction and evaluation, assessment,
pre-ventive maintenance, inspection maintenance, optimization, cost minimization, spare
parts fulfillment and management, computerized maintenance management system,
total productive maintenance, overall equipment effectiveness, fault tree analysis,
Markov chains, Monte Carlo simulation, numerical example, and case study
The book consists of 12 chapters organized as introduced briefly below
Chapter 1 identifies and illustrates the most critical issues concerning the
plan-ning activity, the design, the management, and the control of modern production
systems, both producing goods (manufacturing systems in industrial sectors) and/or
supplying services (e g., hospital, university, bank) This chapter identifies the role
of maintenance in a production system and the capability of guaranteeing a high level
of safety, quality, and productivity in a proper way
Chapter 2 introduces quality assessment, presents statistical quality control
mod-els and methods, and finally Six Sigma theory and applications A brief illustration
and discussion of European standards and specifications for quality assessment is
also presented
Chapter 3 introduces the reader to the actual methodology for the implementation
of a risk evaluation capable of reducing risk exposure and guaranteeing the desired
level of safety
Chapter 4 examines the fundamental definitions concerning maintenance, and
discusses the maintenance question in product manufacturing companies and
ser-vice suppliers The most important maintenance engineering frameworks, e g.,
reliability-centered maintenance and total productive maintenance, are presented
Chapter 5 introduces the reader to the definition, measurement, management, and
control of the main reliability parameters that form the basis for modeling and
eval-uating activities in complex production systems In particular, the basic maintenance
terminology and nomenclature related to a generic item as a part, component, device,
subsystem, functional unit, piece of equipment, or system that can be considered
in-dividually are introduced
Chapter 6 deals with reliability evaluation and prediction It also discusses the
elementary reliability configurations of a system in order to introduce the reader to
the basic tools used to evaluate complex production systems
Trang 8Chapter 7 discusses about the strategic role of the maintenance information tem and computerized maintenance management systems in reliability engineering.Failure rate prediction models are also illustrated and applied.
sys-Chapter 8 introduces models and methods supporting the production system signer and the safety and/or maintenance manager to identify how subsystems andcomponents could fail and what the corresponding effects on the whole system are,and to quantify the reliability parameters for complex systems In particular models,methods, and tools (failure modes and effects analysis and failure mode, effects, andcriticality analysis, fault tree analysis, Markov chains, Monte Carlo dynamic simu-lation) for the evaluation of reliability in complex production systems are illustratedand applied to numerical examples and case studies
de-Chapter 9 presents basic and effective models and methods to plan and conductmaintenance actions in accordance with corrective, preventive, and inspection strate-gies and rules Several numerical examples and applications are illustrated
Chapter 10 discusses advanced models and methods, including the block ments, age replacements, and inspection policies for maintenance management.Chapter 11 presents and applies models and tools for supporting the activities offulfillment and management of spare parts
replace-Chapter 12 presents two significant case studies on reliability and maintenanceengineering In particular, several models and methods introduced and exemplified
in previous chapters are applied and compared
We would like to thank our colleagues and students, particularly those who dealwith reliability engineering and maintenance every day, and all professionals fromindustry and service companies who supported our research and activities, Springerfor its professional help and cooperation, and finally our families, who encouraged
us to write this book
Bologna (Italy) and Piscataway (NJ, USA) Riccardo Manzini
Hoang PhamEmilio Ferrari
Trang 91 A New Framework for Productivity in Production Systems 1
1.1 Introduction 1
1.2 A Multiobjective Scenario 2
1.2.1 Product Variety 3
1.2.2 Product Quality 3
1.3 Production System Design Framework 4
1.4 Models, Methods, and Technologies for Industrial Management 5 1.4.1 The Product and Its Main Features 5
1.4.2 Reduction of Unremunerated Complexity: The Case of Southwest Airlines 6
1.4.3 The Production Process and Its Main Features 7
1.4.4 The Choice of Production Plant 7
1.5 Design, Management, and Control of Production Systems 10
1.5.1 Demand Analysis 10
1.5.2 Product Design 10
1.5.3 Process and System Design 10
1.5.4 Role of Maintenance in the Design of a Production System 11
1.5.5 Material Handling Device Design 11
1.5.6 System Validation and Profit Evaluation 11
1.5.7 Project Planning and Scheduling 11
1.5.8 New Versus Existing Production Systems 11
1.6 Production System Management Processes for Productivity 13
1.6.1 Inventory and Purchasing Management 14
1.6.2 Production Planning 14
1.6.3 Distribution Management 14
1.7 Research into Productivity and Maintenance Systems 14
xi
Trang 102 Quality Management Systems and Statistical Quality Control 17
2.1 Introduction to Quality Management Systems 17
2.2 International Standards and Specifications 19
2.3 ISO Standards for Quality Management and Assessment 19
2.3.1 Quality Audit, Conformity, and Certification 19
2.3.2 Environmental Standards 21
2.4 Introduction to Statistical Methods for Quality Control 23
2.4.1 The Central Limit Theorem 23
2.4.2 Terms and Definition in Statistical Quality Control 24
2.5 Histograms 25
2.6 Control Charts 25
2.7 Control Charts for Means 26
2.7.1 The R-Chart 26
2.7.2 Numerical Example, R-Chart 29
2.7.3 The Nx-Chart 29
2.7.4 Numerical Example, Nx-Chart 30
2.7.5 The s-Chart 30
2.7.6 Numerical Example, s-Chart and Nx-Chart 33
2.8 Control Charts for Attribute Data 33
2.8.1 The p-Chart 35
2.8.2 Numerical Example, p-Chart 36
2.8.3 The np-Chart 37
2.8.4 Numerical Example, np-Chart 37
2.8.5 The c-Chart 37
2.8.6 Numerical Example, c-Chart 39
2.8.7 The u-Chart 40
2.8.8 Numerical Example, u-Chart 40
2.9 Capability Analysis 40
2.9.1 Numerical Example, Capability Analysis and Normal Probability 42
2.9.2 Numerical Examples, Capability Analysis and Nonnormal Probability 46
2.10 Six Sigma 48
2.10.1 Numerical Examples 51
2.10.2 Six Sigma in the Service Sector Thermal Water Treatments for Health and Fitness 51
3 Safety and Risk Assessment 53
3.1 Introduction to Safety Management 53
3.2 Terms and Definitions Hazard Versus Risk 54
3.3 Risk Assessment and Risk Reduction 57
3.4 Classification of Risks 58
3.5 Protective and Preventive Actions 60
3.6 Risk Assessment, Risk Reduction, and Maintenance 63
3.7 Standards and Specifications 63
Trang 11Contents xiii
4 Introduction to Maintenance in Production Systems 65
4.1 Maintenance and Maintenance Management 65
4.2 The Production Process and the Maintenance Process 66
4.3 Maintenance and Integration 69
4.4 Maintenance Workflow 70
4.5 Maintenance Engineering Frameworks 70
4.6 Reliability-Centered Maintenance 72
4.7 Total Productive Maintenance 73
4.7.1 Introduction to TPM 73
4.7.2 The Concept of TPM 74
4.7.3 TPM Operating Instruments 75
4.7.4 From Tradition to TPM: A Difficult Transition 76
4.8 Maintenance Status Survey 80
4.9 Maintenance Outsourcing and Contracts 83
5 Basic Statistics and Introduction to Reliability 87
5.1 Introduction to Reliability 88
5.2 Components and Systems in Reliability 88
5.3 Basic Statistics in Reliability Engineering 89
5.4 Time to Failure and Time to Repair 90
5.5 Probability Distribution Function 90
5.6 Repairable and Nonrepairable Systems 91
5.7 The Reliability Function – R(t) 91
5.8 Hazard Rate Function 92
5.8.1 Hazard Rate Profiles 94
5.8.2 Mean Time to Failure 95
5.9 Stochastic Repair Process 95
5.10 Parametric Probability Density Functions 97
5.10.1 Constant Failure Rate Model: The Exponential Distribution 97
5.10.2 Exponential Distribution Numerical example 99
5.10.3 The Normal and Lognormal Distributions 103
5.10.4 Normal and Lognormal Distributions Numerical example 106
5.10.5 The Weibull Distribution 110
5.10.6 Weibull Distribution Numerical Example 112
5.11 Repairable Components/Systems: The Renewal Process and Availability A(t) 113
5.12 Applications and Case Studies 117
5.12.1 Application 1 – Nonrepairable Components 117
5.12.2 Application 2 – Repairable System 122
6 Reliability Evaluation and Reliability Prediction Models 133
6.1 Introduction 133
6.2 Data Collection and Evaluation of Reliability Parameters 134
6.2.1 Empirical Functions Direct to Data 135
6.2.2 Theoretical Distribution Research 145
6.3 Introduction to Reliability Block Diagrams 152
6.4 Serial Configuration 153
6.4.1 Numerical Example – Serial Configuration 154
6.5 Parallel Configuration 161
Trang 126.5.1 Numerical Example – Parallel Configuration 163
6.6 Combined Series–Parallel Systems 168
6.7 Combined Parallel–Series Systems 170
6.8 k-out-of-n Redundancy 170
6.8.1 Numerical Examples, k-out-of-n Redundancy 171
6.9 Simple Standby System 174
6.9.1 Numerical Example – Time-Dependent Analysis: Standby System 180
6.10 Production System Efficiency 183
6.10.1 Water Supplier System 185
6.10.2 Continuous Dryer System 187
7 Maintenance Information System and Failure Rate Prediction 189
7.1 The Role of a Maintenance Information System 189
7.2 Maintenance Information System Framework 190
7.2.1 Data Collection 190
7.2.2 Maintenance Engineering 192
7.2.3 Interventions and Workload Analysis 194
7.2.4 Spare Parts and Equipment Management 195
7.3 Computer Maintenance Management Software 196
7.4 CMMS Implementation: Procedure and Experimental Evidence 199 7.4.1 System Configuration and Integration 199
7.4.2 Training and Data Entry 200
7.4.3 Go Live 200
7.4.4 Postimplementation Phase and Closing 200
7.4.5 Experimental Evidence Concerning CMMS Implementation 200
7.5 Failure Rate Prediction 204
7.5.1 Accelerated Testing 204
7.5.2 Failure Data Prediction Using a Database 206
7.6 Remote Maintenance/Telemaintenance 214
7.6.1 Case Study 216
8 Effects Analysis and Reliability Modeling of Complex Production Systems 219
8.1 Introduction to Failure Modes Analysis and Reliability Evaluation 220
8.2 Failure Modes and Effects Analysis 220
8.2.1 Product Analysis 221
8.2.2 Failure Mode, Effects, and Causes Analysis 222
8.2.3 Risk Evaluation 222
8.2.4 Corrective Action Planning 225
8.2.5 FMEA Concluding Remarks 229
8.3 Failure Mode, Effects, and Criticality Analysis 229
8.3.1 Qualitative FMECA 231
8.3.2 Quantitative FMECA 231
8.3.3 Numerical Examples 232
8.4 Introduction to Fault Tree Analysis 236
8.5 Qualitative FTA 239
8.5.1 Fault Tree Construction Guidelines 239
Trang 13Contents xv
8.5.2 Numerical Example 1 Fault Tree Construction 240
8.5.3 Boolean Algebra and Application to FTA 241
8.5.4 Qualitative FTA: A Numerical Example 242
8.6 Quantitative FTA 244
8.6.1 Quantitative FTA, Numerical Example 1 248
8.6.2 Quantitative FTA, Numerical Example 2 252
8.6.3 Numerical Example Quantitative Analysis in the Presence of a Mix of Statistical Distributions 254
8.7 Application 1 – FTA 263
8.7.1 Fault Tree Construction 264
8.7.2 Qualitative FTA and Standards-Based Reliability Prediction 266
8.7.3 Quantitative FTA 269
8.8 Application 2 – FTA in a Waste to Energy System 277
8.8.1 Introduction to Waste Treatment 277
8.8.2 Case study 278
8.8.3 Emissions and Externalities: Literature Review 279
8.8.4 SNCR Plant 280
8.8.5 SNCR Plant Reliability Prediction and Evaluation Model 281
8.8.6 Qualitative FTA Evaluation 283
8.8.7 NOxEmissions: Quantitative FTA Evaluation 287
8.8.8 Criticality Analysis 292
8.8.9 Spare Parts Availability, What-If Analysis 295
8.8.10 System Modifications for ENF Reduction and Effects Analysis 300 8.9 Markov Analysis and Time-Dependent Components/Systems 301
8.9.1 Redundant Parallel Systems 302
8.9.2 Parallel System with Repairable Components 304
8.9.3 Standby Parallel Systems 306
8.10 Common Mode Failures and Common Causes 309
8.10.1 Unavailability of a System Subject to Common Causes 310
8.10.2 Numerical Example, Dependent Event 311
9 Basic Models and Methods for Maintenance of Production Systems 313 9.1 Introduction to Analytical Models for Maintenance of Production Systems 314
9.1.1 Inspection Versus Monitoring 315
9.2 Maintenance Strategies 315
9.3 Introduction to Preventive Maintenance Models 318
9.4 Component Replacement 319
9.4.1 Time-Related Terms and Life Cycle Management 319
9.4.2 Numerical Example Preventive Replacement and Cost Minimization 320
9.5 Time-Based Preventive Replacement – Type I Replacement Model 323
9.5.1 Numerical Example Type I Replacement Model 324
9.5.2 Numerical Example Type I Model and Exponential Distribution of ttf 325
9.5.3 Type I Replacement Model for Weibull distribution of ttf 326
9.5.4 The Golden Section Search Method 326
Trang 149.5.5 Numerical Example Type I Model and the Golden Section
Method 328
9.6 Time-Based Preventive Replacement Including Duration of Replacements 333
9.6.1 Numerical Example 1: Type I Replacement Model Including Durations Tpand Tf 333
9.6.2 Type I Model with Duration of Replacement for Weibull Distribution of ttf 335
9.6.3 Numerical Example 2: Type I Model with Durations Tpand Tf 335
9.6.4 Practical Shortcut to tp Determination 335
9.7 Block Replacement Strategy – Type II 339
9.7.1 Renewal Process 340
9.7.2 Laplace Transformation: W(t) and w(t) 341
9.7.3 Renewal Process and W(t) Determination, Numerical Example 341 9.7.4 Numerical Example, Type II Model 343
9.7.5 Discrete Approach to W(t) 348
9.7.6 Numerical Examples 349
9.7.7 Practical Shortcut to W(t) and tp Determination 352
9.8 Maintenance Performance Measurement in Preventive Maintenance 353
9.8.1 Numerical Example 354
9.9 Minimum Total Downtime 355
9.9.1 Type I – Minimum Downtime 355
9.9.2 Type II – Downtime Minimization 357
9.10 Group Replacement: The Lamp Replacement Problem 358
9.11 Preventive Maintenance Policies for Repairable Systems 359
9.11.1 Type I Policy for Repairable Systems 360
9.11.2 Type II Policy for Repairable Systems 370
9.12 Replacement of Capital Equipment 372
9.12.1 Minimization of Total Cost 372
9.12.2 Numerical Example 372
9.13 Literature Discussion on Preventive Maintenance Strategies 372
9.14 Inspection Models 373
9.15 Single Machine Inspection Model Based on a Constant Value of Conditional Probability Failure 375
9.15.1 Numerical Example 1, Elementary Inspection Model 376
9.15.2 Numerical Example 2, Elementary Inspection Model 377
9.16 Inspection Frequency Determination and Profit per Unit Time Maximization 378
9.17 Inspection Frequency Determination and Downtime Minimization 380
9.18 Inspection Cycle Determination and Profit per Unit Time Maximization 381
9.18.1 Exponential Distribution of ttf 381
9.18.2 Weibull Distribution of ttf 382
9.18.3 Numerical Example 382
9.19 Single Machine Inspection Model Based on Total Cost per Unit Time Minimization 383
Trang 15Contents xvii
9.20 Single Machine Inspection Model Based on Minimal Repair
and Cost Minimization 384
9.21 Inspection Model Based on Expected Availability per Unit Time Maximization 385
9.22 Group of Machines Inspection Model 386
9.23 A Note on Inspection Strategies 387
9.24 Imperfect Maintenance 388
9.24.1 Imperfect Preventive Maintenance p – q 388
9.25 Maintenance-Free Operating Period 390
9.25.1 Numerical Example (Kumar et al 1999) 391
9.25.2 MFOPS and Weibull Distribution of ttf 392
9.26 Opportunistic Maintenance Strategy 393
10 Advanced Maintenance Modeling 397
10.1 Introduction 397
10.2 Maintenance Policy 398
10.2.1 Age Replacement 398
10.2.2 Block Replacement 399
10.3 Modeling of Nonrepairable Degraded Systems 399
10.4 Modeling of Inspection-Maintenance Repairable Degraded Systems 402
10.4.1 Calculate EŒNI 403
10.4.2 Calculate Pp 404
10.4.3 Expected Cycle Length Analysis 405
10.4.4 Optimization of Maintenance Cost Rate Policy 405
10.4.5 Numerical Example 406
10.5 Warranty Concepts 406
10.6 Conclusions 408
11 Spare Parts Forecasting and Management 409
11.1 Spare Parts Problem 409
11.2 Spare Parts Characterization 410
11.3 Forecasting Methods 411
11.4 Croston Model 412
11.5 Poisson Model 413
11.6 Binomial Model 414
11.6.1 Numerical Example 415
11.7 Spare Parts Forecasting Accuracy 416
11.8 Spare Parts Forecasting Methods: Application and Case Studies 417 11.8.1 Case Study 1: Spare Parts Forecasting for an Aircraft 417
11.8.2 Case Study 2: Spare Parts Forecasting in a Steel Company 418
11.9 Methods of Spare Parts Management 422
11.9.1 Spare Parts Management: Qualitative Methods 423
11.9.2 Spare Parts Management: Quantitative Methods 426
12 Applications and Case Studies 433
12.1 Preventive Maintenance Strategy Applied to a Waste to Energy Plant 433
12.1.1 Motor System Reliability Evaluation 434
Trang 1612.1.2 Bucket Reliability Evaluation 436
12.1.3 Motor System Determination of Maintenance Costs 437
12.1.4 Time-Based Preventive Replacement for the Motor System 439
12.1.5 Time-Based Preventive Replacement for the Bucket Component 439 12.1.6 Time-Based Preventive Replacement with Durations Tpand Tf 441 12.1.7 Downtime Minimization 442
12.1.8 Monte Carlo Dynamic Analysis 442
12.1.9 Monte Carlo Analysis of the System 446
12.2 Reliability, Availability, and Maintainability Analysis in a Plastic Closures Production System for Beverages 446
12.2.1 RBD construction 448
12.2.2 Rotating Hydraulic Machine 449
12.2.3 Data Collection and Reliability Evaluation of Components 449
12.2.4 Reliability Evaluation, Nonrepairable Components/Systems 454
12.2.5 Data on Repairs and Maintenance Strategies 456
12.2.6 Monte Carlo Analysis of the Repairable System 456
12.2.7 Alternative Scenarios and System Optimization 460
12.3 Conclusions and Call for New Contributions 462
A Appendix 463
A.1 Standardized Normal Distribution 463
A.2 Control Chart Constants 464
A.3 Critical Values of Student’s Distribution with Degree of Freedom 465
Bibliography 467
Index 475
Trang 17A New Framework for Productivity
Contents
1.1 Introduction 1
1.2 A Multiobjective Scenario 2
1.2.1 Product Variety 3
1.2.2 Product Quality 3
1.3 Production System Design Framework 4
1.4 Models, Methods, and Technologies for Industrial Management 5
1.4.1 The Product and Its Main Features 5
1.4.2 Reduction of Unremunerated Complexity: The Case of Southwest Airlines 6
1.4.3 The Production Process and Its Main Features 7 1.4.4 The Choice of Production Plant 7
1.5 Design, Management, and Control of Production Systems 10
1.5.1 Demand Analysis 10
1.5.2 Product Design 10
1.5.3 Process and System Design 10
1.5.4 Role of Maintenance in the Design of a Production System 11
1.5.5 Material Handling Device Design 11
1.5.6 System Validation and Profit Evaluation 11
1.5.7 Project Planning and Scheduling 11
1.5.8 New Versus Existing Production Systems 11
1.6 Production System Management Processes for Productivity 13
1.6.1 Inventory and Purchasing Management 14
1.6.2 Production Planning 14
1.6.3 Distribution Management 14
1.7 Research into Productivity and Maintenance Systems 14
The pressure of the global market we all face
in-creased competition for share The fundamental key is
the productivity of the system All players in the
indus-try are in the same race to become low cost producers, including manufacturers, our suppliers, and their sup-pliers, too And each of us must do it while improv-ing quality, because consumers require it (Alain Batty, CEO, Ford Motor Company of Canada, 2004)
High levels of product personalization and qual-ity standardization are essential requirements in cur-rent market conditions, in which prices are falling, and
in which a new production paradigm for a production system has come into existence
The planning, management, and control of a pro-duction system are crucial activities requiring an in-tegrated approach examining the internal features of available production resources and guiding their ratio-nal exploitation
Maintenance techniques play a major role in sup-porting research into productivity, and these very ef-fective tools must be adopted by modern companies
1.1 Introduction
In this book explicitly devoted to maintenance, the first chapter aims to identify and to illustrate the most critical issues concerning the planning activ-ity, the design, the management, and the control of modern production systems, both producing goods (manufacturing systems in industrial sectors) and/or supplying services (e g., hospital, university, bank)
By this discussion it is possible to identify the role of maintenance in a production system and the capability
of guaranteeing a high level of safety, quality, and pro-ductivity in a proper way In particular, the expression
© Springer 2010
Trang 18“research for productivity” frequently animates the
sections of this chapter
The following section introduces the uncertain
op-erating scenario that modern companies have to face
to compete in a globalized market
Section 1.3 illustrates a meta-framework for the
de-sign of a production system with an enterprise
per-spective The aim is to underline the most important
tasks and decisional steps affecting the performance
of the system with particular attention being given to
the business and corporate strategies of the enterprise
and its related companies
Section 1.4 briefly discusses the models, methods,
and technologies currently available to support the
de-cision-making process dealing with production
sys-tems
Section 1.5 presents a conceptual framework,
pro-posed by the authors, for the integration of the design,
management, and control of a production system
1.2 A Multiobjective Scenario
Vaughn et al (2002) identified the most critical factors
affecting the performance of a production system as
part of an enterprise system The enterprise does not
have complete control over these factors:
• Market uncertainty This is defined as the demand
fluctuations for the product, including both
short-term random variability and long-short-term step/cyclical
variability The uncertainty of demand can create
overcapacity or undercapacity, generating customer
dissatisfaction
• Production volume, i e., the number of products to
be manufactured over a time period Market
uncer-tainty and production volume are tightly coupled
Production volume determines the production
sys-tem capacity and most of the factory physical
de-sign, e g., floor space needed, machine selection,
layout, and number of workers
• Product mix This is the number of different
prod-ucts to be manufactured The production system
has to be capable of producing various versions of
a product, or different products simultaneously in
the same plant in order to fulfill the market need
with the best exploitation of the resources
Prod-uct mix and prodProd-uct volume are closely related
(Manzini et al 2004)
• Frequency of changes This is the number of
engi-neering changes per time period The changes can
be either structural or upgrades to existing systems
It is not possible to foresee all the changes thatmight be introduced into a product in the future Forexample, the frequency of changes is a very criticalissue for the electronic control systems of packag-ing machines A packaging system can be used by
a generic customer for a few decades: the electronictechnologies change very quickly and the customercould need to replace failed parts with new, differ-ent spare parts
• Complexity There are several ways to measure
product, process, or system complexity A few amples are the number of parts, the number of pro-cess steps, and the number of subsystems Com-plexity deals with the level of difficulty to design,manufacture, assemble, move, etc a part, and it
ex-is affected by the available process capability (seeChap 2)
• Process capability, as the ability to make
some-thing repeatedly with minimal interventions Thisfactor deals with the quality of the process, prod-uct, and production systems, as properly illustrated
in Chap 2
• Type of organization and in particular the
innova-tion of the workforce participating in product, cess, and system improvements
pro-• Worker skill level, i e., the availability of high-level
employee skills This factor is strongly linked to thenecessary and/or available level of automation
• Investment, as the amount of financial resources
re-quired This is one of the most critical constraints
in the production system design, management, andcontrol
• Time to first part This is another very critical
con-straint and represents the time from the initial tem design to the full rate of production
sys-• Available/existing resources (financial,
technologi-cal, human, etc.)
Current markets have changed a great deal from those
of a few years ago Mass production (large quantities
of a limited range of products) has declined in severalproduction systems and been replaced by customer-oriented production Sales and quantities have essen-tially remained constant, but the related product mix
is growing ever larger Companies are attempting tospread risk over a wider range of base products and
Trang 191.2 A Multiobjective Scenario 3
meet (or anticipate) customer needs and desires This
trend is intensified by global competition: different
players throughout the world are supplying “similar”
products to the same markets
This situation has produced significant changes in
production systems (which either produce products or
supply services): production batches are very small,
production lead times are kept very short, product life
cycle is also brief, and consequently product time to
market is very compressed
In conclusion, production systems must possess
two important features: flexibility and elasticity
Flex-ibility deals with the ability of the production
sys-tem to evolve continuously and manufacture wide
ranges of products On the other hand, elasticity
al-lows great variation in production volumes without
a significant change in the production system
configu-ration (i e., without needing time-consuming and
ex-pensive work) The literature also names these
con-cepts “capability flexibility” and “capacity
flexibil-ity.”
1.2.1 Product Variety
The great increase in product variety is easily verified
in several case studies It is sufficient to investigate
a single product in order to see how many different
versions are now offered in comparison with 10 years
ago
Some significant results from the research
con-ducted by Thonemann and Bradley (2002) on product
variety analysis are reported below
Table 1.1 shows the increase of product mix in
dif-ferent industrial sectors in the decade 1990–2000 The
smallest increase of a little over 50% occurred in
com-modities
Table 1.1 Product variety increase in various industrial sectors
Consequently, companies must not only producebut also supply products and services to very highquality standards, meaning stand-alone quality is nolonger a marginal success factor
In addition to these observations of “new markettrends,” industrial and service companies also needtheir industrial investments to be remunerated Thisfield is also significantly affected by global competi-tion: with prices falling, companies are forced to re-duce production costs Therefore, modern companiesmust expand their product mix, increase the quality ofthe product and the process, and reduce costs: a verystimulating challenge!
Moreover, companies are striving to improve the
productivity and quality of their production systems,
with the most relevant targets in this multiscenariodecision-making process including:
• a great degree of flexibility and elasticity in the duction system;
pro-• short lead times;
• high-quality products and production processes;
• short time to market;
• control of production costs
Trang 201.3 Production System Design
Framework
This section presents a conceptual framework for
sup-porting the design of a production system with an
enterprise perspective It takes inspiration from the
study by Fernandes (2001) in the aerospace industry
and lean production The illustration of this
frame-work is very useful for identification of the operating
context of modern production systems and for
justi-fication of the introduction of an integrated quality-,
safety-, and reliability-based approach to support the
design, management, and control of a complex system
In particular, maintenance models and methods reveal
themselves as very effective tools to conduct this
pro-cess
Figure 1.1 presents the meta-framework which also
contain other tools, methods, and processes applicable
to the design process of production systems operating
in different industrial and service sectors, such as
System design
Corporate level
Physical implications
Corporate business strategy
Manufacturing
Product strategy
Trial & error
DFA, DFM, current engineering
con-Fig 1.1 Production system design framework DFA design for assembly, DFM manufacturing (Fernandes 2001)
motive, food, health care, pharmaceutical, education,and public administration
The proposed framework is made of three main anddistinct elements:
1 Infrastructure, as a result of the enterprise
strat-egy formulation which defines important and cal attributes of the system as operating policy, or-ganizational structure, location, and environment(see the top portion of Fig 1.1) This strategy isthe result of long-term objectives and programs,and is focused on creating operating capabilities.The corporate-level strategy balances the conflict-ing needs of the numerous stakeholders (e g., cus-tomers, employees, and owners) facing the overallenterprise the production system belongs to, by theformulation of a corporate strategy which is trans-ferred to the business units throughout the corpo-ration
criti-2 Structure (see the bottom portion Fig 1.1) It is
the physical manifestation of the detailed
Trang 21produc-1.4 Models, Methods, and Technologies for Industrial Management 5
tion system design and is the result of the factory
layout, number and configuration of machines, and
production methods and processes
3 Product strategy. congruence between the
corporate-level business strategy and the
func-tional strategies It involves funcfunc-tional elements
such as marketing, product design, supplier, and
manufacturing (see the concurrent engineering
overlapping of functions in Fig 1.1)
This meta-framework gives the concurrent
engineer-ing approach a great and strategic importance and
pro-vides enlightenment on the validation analysis, and the
continuous improvement (see the so-called
modifica-tion loop in Fig 1.1)
1.4 Models, Methods, and Technologies
for Industrial Management
Which resources are capable of supporting companies
in meeting the challenge introduced in the previous
section?
First of all, it is important to state that only
re-sources relating to products (or services) and to
pro-duction processes (i e., manufacturing and assembly
activities in industrial companies) are considered in
this chapter It is not the authors’ purpose to take into
account some other factors associated with
advertis-ing, marketadvertis-ing, or administrative areas
In brief, research supports productivity via three
fundamental and interrelated drivers: the product, the
process, and the production system
1.4.1 The Product and Its Main Features
Products are usually designed with reference to their
performance (i e., the ability to satisfy customer
needs) and to the aesthetic appearance required by
the market Requirements derived from the
produc-tion system are sometimes neglected, thus having
a negative effect on final production costs As a
conse-quence, during the last few decades several strategies
or techniques for product design, such as design for
manufacturing (DFM) and design for assembly (DFA),
which, respectively, consider manufacturing and
as-sembly requirements during the design process, have
been proposed in the literature and applied in modernproduction systems They provide a valid support tothe effective management of total production costs
In recent years, the matter of reuse and/or recycling
of products has become extremely pressing wide, and many countries are facing problems relating
world-to waste evaluation and disposal The significance ofthese topics is demonstrated by the wide diffusion ofproduct life cycle management, as the process of man-aging the entire life cycle of a product from its con-ception, through design and manufacture, to serviceand disposal Figure 1.2 presents a conceptual model
of the product life cycle, including the design, tion, support, and ultimate disposal activities Main-tenance of production facilities and recovery of prod-ucts explicitly play a strategic role in product life cyclemanagement
produc-As a consequence, a product design process thatalso considers product disassembly problems at theend of the product life cycle has become a success fac-tor in modern production systems This approach tothe design process is known as “design for disassem-bly” (DFD) In several supply chains (e g., tires andbatteries) the manufacturer is burdened with the reuse
or final disposal of the product, and DFD is a ularly effective tool for the reduction of productioncosts Section 1.2 discusses the advantages and dis-advantages associated with the production of a widevariety of products: wide ranges of product mix are
partic-an effective strategy in meeting customer expectations,but companies must reach this goal with the minimumnumber of components and parts
In particular, any part or function not directly ceived by the customer implies both an unnecessaryand a harmful addition of complexity because it is notremunerated Research and trials examining this spe-cial kind of complexity lead to the formulation of the
per-following production strategy: what is visible over the
skin of the product is based on a very high degree of
modularity under the skin.
The so-called product platforms are a good
solu-tion to support product variability, and so have beenadopted in modern production systems Several fam-ilies of similar products are developed on the sameplatform using identical basic production guidelinesfor all “derivative” products A well-known example
is the “spheroid platform” developed by Piaggio (theItalian manufacturer of the famous Vespa scooter): theproducts named Zip, Storm, Typhoon, Energy, Skip-
Trang 22Fig 1.2 Product life cycle
model
per, Quartz, and Free are all derived from the same
underlying fundamental design of the scooter called
“Sphere” (hence the spheroid platform) Another
sig-nificant example is the standardization of car speed
in-dicators in the automotive sector: the manufacturers
tend to use the same component in every product mix
regardless of the speed attainable by each individual
car model As a result of this strategy, the range of the
product mix is reduced and the management of parts
is simplified without affecting product performance
Every remark or comment about the techniques and
strategies cited is also effective both in production
sys-tems and in supply services such as hospitals, banks,
and consultants
1.4.2 Reduction of Unremunerated
Complexity: The Case
of Southwest Airlines
Southwest Airlines has developed several interesting
ideas for reducing complexity in the service sector
Figure 1.3 shows the cost per passenger for each miletraveled with the main US airlines
Two fundamental facts can be observed in Fig 1.3:since 2004 the cost per passenger for each miletraveled (extrapolated from available seat miles) forSouthwest Airlines has been lower than for its com-petitors, clearly competing in the same market andover the same routes Moreover, the available seatmile costs of Southwest Airlines have continued todecrease since 11 September 2001, in contrast tothose of its competitors Moreover, these costs havesignificantly increased owing to the increase in thecost of petroleum and owing to the introduction ofnew safety and security standards
How can this be explained? The answer lies in theefforts of Southwest Airlines, since 1996, to reduce thevariety and complexity of services offered to its cus-tomers but not directly perceived by them
A significant analysis of the fleet configurations ofmajor American airlines is reported in Table 1.3.The average number of different models of airplaneused by the major USA airlines is 14, but SouthwestAirlines employs only Boeing 737 airplanes In fact,
Trang 231.4 Models, Methods, and Technologies for Industrial Management 7
Table 1.3 Number of different models of airplane used by USA airlines (June 2008)
Boeing 737
Fig 1.3 Cost per passenger for each mile traveled ASM
avail-able seat miles (United States Securities and Exchange
Com-mission 2000)
in June 2008, Southwest Airlines owned 535 airplanes
of this particular type but using various internal
con-figurations, ranging from 122 to 137 seats
Variety based on the type of airplane is completely
irrelevant to customers Furthermore, when a
passen-ger buys a ticket, the airline companies do not
commu-nicate the model of airplane for that flight However,
reducing the number of different models of airplane in
the fleet directly results in a significant saving for the
airline company: only one simulator for pilot training
is required, only one training course for technicians
and maintenance staff, spare parts management and
control activities are optimized, “on ground”
equip-ment such as systems for towing and refueling are
standard, etc
In spite of critical safety problems and high fuel
costs, Southwest Airlines has been able to compete
very effectively Among a great many original proaches proposed during the last two decades for thereduction of complexity in a production system, thewell-known Variety Reduction Program (VRP) devel-oped by Koudate and Suzue (1990) is worthy of men-tion
ap-1.4.3 The Production Process and Its Main Features
Production processes in several industrial sectors haverecently been forced to undergo significant transfor-mations in order to ensure both cost reductions andhigh quality A good example from the wood sector isthe nonstop pressing process used to simplify the as-sembly process by using small flaps, gluing, and othertechniques instead of screw junctions
Every process innovation capable of consuming toomany production resources such as energy, manpower,and raw materials is a very useful motivating factor
driving research into productivity.
Consequently, when a new production investment
is being made in a manufacturing or service sector,
a benchmark investigation is required in order to checkthe state of the art of the production processes In ad-dition to this, from an economic or technical point ofview, scouting for alternative processes that could bemore effective is also recommended
1.4.4 The Choice of Production Plant
An effective production process is a basic condition
in making an entire production system effective ough analysis of the specific characteristics of produc-tion factors, e g., resources and equipment required bythe available processes, is one of the most importantaspects of research into productivity
Trang 24Thor-It is possible to have two different production plants
carrying out the same process with their own
specifica-tions and production lead times to get the same results,
but at different costs
A great deal of effort in innovation of the plant
equipment has taken place in recent years, but
in-novation in the production process is a very
diffi-cult problem to solve, often involving contributions
from various industrial disciplines (e g., electronics,
robotics, industrial instrumentation, mechanical
tech-nology) One of the most significant trends in
equip-ment innovation developequip-ments is represented by
flexi-ble automation, which provides the impetus for a
pro-duction system to achieve high levels of productivity
Presently, industrial equipment and resources are
highly automated However, flexible automation is
required so that a wide mix of different products
and services is achieved without long and expensive
setups One of the best expressions of this
con-cept, i e., the simultaneous need for automation and
flexibility, is the so-called flexible manufacturing
system (FMS) A flexible manufacturing system is
Fig 1.4 Different kinds of manufacturing systems (Black and Hunter 2003)
a melting pot where several automatic and flexiblemachines (e g., computer numerical control (CNC)lathes or milling machines) are grouped and linkedtogether using an automatic and flexible materialhandling system The system can operate all job se-quences, distinguish between different raw materials
by their codes, download the correct part programfrom the logic controller, and send each part tothe corresponding machine This basic example of
the integration of different parts shows how
suc-cessful productivity in a modern production systemcan be
The potential offered by flexible automation canonly be exploited effectively if every element of theintegrated system is capable of sharing informationquickly and easily
The information technology in flexible systemsprovides the connectivity between machines, tool stor-age systems, material feeding systems, and each part
of the integrated system in general
Figure 1.4 presents a brief classification, proposed
by Black and Hunter (2003), of the main
Trang 25manufac-1.4 Models, Methods, and Technologies for Industrial Management 9
turing systems in an industrial production context by
comparing different methodologies based on
produc-tion rates and flexibility, i e., the number of different
parts the generic system can handle
In conclusion, the required system integration
means developing data exchange and sharing of
infor-mation, and the development of production systems in
the future will be based on this critical challenge
The current advanced information technology
solu-tions (such as local area networks, the Internet,
wire-SELLING MARKET
• International competition
• Shorter product life cycle
• Increasing product diversity
• Decreasing product quantity
• Shorter delivery times
• Higher delivery reliability
• Higher quality requirements
LABOR MARKET
• Increasing labour costs
• Lack of well-motivated and
• New process strategies
• New joining methods
COMPANY OBJECTIVES
• High flexibility
• Constant and high product quality
• Short throughput times
• Low production costs
ACTIVITIES
COMPANY COMPANY POLICY
EXTERNAL DEVELOPMENTS
• Effective system design
• Effective system management
Fig 1.5 The new productivity paradigm for a production system DFM design for manufacturing, DFA design for assembly, DFD
design for disassembly (Rampersad 1995)
less connectivity, and radio-frequency identification(RFID)) represent a valid support in the effective in-tegration of production activities
Figure 1.5 is extracted from a previous study bythe authors and briefly summarizes the productivityparadigm discussed in this chapter This figure wasproposed for the first time by Rampersad (1995).Research into productivity also requires technical,human, and economic resources Consequently, before
a generic production initiative is embarked upon, it is
Trang 26essential to carry out a feasibility study and an
ap-praisal of the economic impact At the design stage
of a product or service, a multidecision approach is
often required before the production start-up is
ini-tiated Moreover, as it involves a broad spectrum of
enterprise roles and functions, an integrated
manage-ment approach is achieved because brilliant design
so-lutions can be compromised by bad management The
following section deals with the design, management,
and control of a production system in accordance with
a new productivity paradigm proposed by the authors
1.5 Design, Management, and Control
of Production Systems
A systematic and integrated approach to the
manage-ment and control of a production system is essential
for rational and effective use of the above-mentioned
resources and equipment In other words,
productiv-ity must be designed and managed correctly, otherwise
the enterprise will risk not being appropriately
remu-nerated for its investment
In both the manufacturing and the service sectors,
every new industrial initiative at its start-up needs
a complete design process taking the following
criti-cal aspects into consideration: market demand
analy-sis, design activity, validation of design, and
sequenc-ing and schedulsequenc-ing of project activities
Once the production system has been designed and
installed, modern management and optimization
tech-niques and tools need to be applied
Because of this complex scenario, the productivity
goal for a complex production system can be
effec-tively achieved by using the integrated and systematic
approach shown in Fig 1.6 (Manzini et al 2006a)
This approach summarizes the complete design
pro-cedure for a generic production system according to
the current state of the art supporting decision-making
techniques and methods
1.5.1 Demand Analysis
The starting point of the proposed method is the
prod-uct (or service) market analysis, based on up-to-date
statistical forecasting methods (e g., time series,
ex-ponential smoothing, moving average) for the
extrap-olation of the future demand from the current one
The logical sequence of events is therefore the designphase, and only after its approval is it possible to move
on to process design, and lastly the production plantcan be designed Once system optimization has beencarried out, the product can be launched on the market
1.5.2 Product Design
The product design phase involves the very importantstrategies and methodologies of DFM, DFA, and DFDwhich support management decision making in manu-facturing and service companies These two strategiestake manufacturing and assembly problems, respec-tively, into consideration during the product design ac-tivity The results bring about a drastic reduction in thenumber of redesign cases, a significant improvement
in production system performance, and a noteworthycompression of product time to market Another sup-porting decision-making technique is the previouslymentioned VRP, which focuses on reduction of com-plexity
All these supporting design strategies are mented by using several computerized system solu-tions: the well-known design automation tools, par-ticularly computer-aided design and computer-aidedmanufacturing
imple-The design of a new product (or service) is ally based on an interactive loop that verifies and mod-ifies the project by the execution of several fine-tuningiterations
gener-1.5.3 Process and System Design
The product specification forms the input data used
in the production process design, which is thereforestrictly dependent on the product or service to be sup-
plied A benchmarking analysis is fundamental to
ef-fective process design because it analyses the state ofthe art in process technologies
The detailed definition of the production processimmediately outlines the system structure (i e., plant,production resources, and equipment), thus choosingthe right number and type of machines, tools, opera-tors, etc., and defining the corresponding facility lay-out design The plant layout problem can be solved
Trang 271.5 Design, Management, and Control of Production Systems 11
using a dedicated software platform (Ferrari et al
2003; Gamberi et al 2009)
1.5.4 Role of Maintenance in the Design
of a Production System
The maintenance function is a strategic resource during
the preliminary design process of a production system
The analysis and forecasting of the reliability
perfor-mance of a piece of equipment significantly improve the
effectiveness of the design of the whole production
sys-tem It is very important to foresee future maintenance
operations and costs both in the resources/facilities and
in the plant layout design so as to avoid lengthy
down-times due to, e g., the incorrect location of machines, or
to a bad assignment and scheduling of manufacturing
tasks to resources and workload
The role of maintenance has been increasing in
im-portance, thus leading to a new conceptual framework:
the so-called design for maintenance directly
embod-ies maintenance principles in the design process
1.5.5 Material Handling Device Design
In order to complete the illustration of the design
pro-cess of a production system, the material handling
de-vice design has to be considered Several
decision-making models and methods have been developed to
support this critical issue (Gamberi et al 2009), in
par-ticular in logistics and in operations research, e g.,
ve-hicle routing algorithms and traveling scheduling
pro-cedures
1.5.6 System Validation
and Profit Evaluation
Each design activity, for product, process, material
handling device, etc., is very complex As a whole they
form a set of interlaced tasks whose global solution is
not the sum of individual optimizations An integrated
approach generates a set of suitable solutions to be
in-vestigated in depth from an economic and technical
point of view In conclusion, the final design must be
fully validated As the production system does not
ex-ist during the design process, and it is often almost
impossible to experiment on a reliable prototype, formance analysis and system validation are usuallyconducted by using simulation (e g., visual interactivesimulation, Monte Carlo simulation, what-if analysis)
per-This ex ante evaluation checks the formal
con-gruity of the whole design process, supporting the nal choice of system configuration and the fine-tuning
fi-of the solution adopted The technical analysis fi-of theconfiguration examined is not a guarantee of a rapidreturn on the industrial investment: the economic eval-uation, in terms of total amount of money over time, isthe most important deciding factor
For an investment analysis methods such as thewell-known net present value, payback analysis, anddiscounted cash flow rate of return are very frequentlyused The best solution results from this double-check,both technical and economic, and forms the foundationfor the following phase related to execution of the ac-tivities, i e., project planning and activity scheduling
1.5.7 Project Planning and Scheduling
The effective planning and control of each task in
a generic project is crucial in avoiding any delay Torespect the project deadline means to save money, es-pecially when several activities must be performed si-multaneously or according to several precedence con-straints
A great many project scheduling models andmethods are presented in the literature, such as thewell-known program evaluation and review technique(PERT), the critical path method (CPM), and Ganttanalysis
Figure 1.6 presents a nonexhaustive list of ing techniques and tools for the execution of the designtasks previously illustrated in general Most of themhave already been mentioned and briefly described orare discussed in the following sections
support-1.5.8 New Versus Existing Production Systems
Some previous considerations concern research intoproductivity from the design process of a new pro-duction system But what are the requirements for
a production system that has already been set up and
is working?
Trang 28Obviously the challenge of productivity also
in-volves existing production systems The techniques
previously discussed are illustrated in Fig 1.6 and also
represent a useful benchmark in the process of
ratio-nalization and optimization of existing production
sys-tems
PRODUCT VARIANTS ANALYSIS
NEW PRODUCTS
PRODUCTION QUANTITIES-VARIANCE ANALYSIS
DEMAND &
FORECASTS
PRODUCT DESIGN
PROCESS DESIGN
MHD DESIGN
DEMAND ANALYSIS
PRODUCT-PROCESS-MHD INTEGRATED DESIGN
PROJECT PLANNING &
SCHEDULING
PROJECT EXECUTION
TECHNIQUES AND TOOLS
DATA MINING & DATA WAREHOUSING HISTORICAL & TREND ANALYSIS MARKET INVESTIGATION
DESIGN FOR MANUFACTURING - DFM DESIGN FOR ASSEMBLY - DFA DESIGN FOR DISASSEMBLY - DFD MODULARITY AND STANDARDIZATION VARIETY REDUCTION PROGRAM - VRP DESIGN AUTOMATION TOOL (CAD/CAE, CAPP ) RESOURCES DETERMINATION
LAYOUT DESIGN MATERIAL HANDLING DEVICE DESIGN VEHICLE ROUTING OPTIMIZATION RELIABILITY & MAINTAINABILITY ANALYSIS
VISUAL INTERACTIVE SIMULATION - VIS MONTE CARLO SIMULATION
WHAT-IF ANALYSIS
NET PRESENT VALUE - NPV ECONOMIC VALUE ADDED - EVA DISCOUNTED CASH FLOW RATE OF RETURN PAY BACK ANALYSIS
DECISION TREE ANALYSIS MONTE CARLO SIMULATION PROJECT SCHEDULING ALGORITHMS PROGRAM EVALUATION & REVIEW TECHNIQUE - PERT SCHEDULING
CRITICAL PATH METHOD - CPM GANTT ANALYSIS
ALTERNATIVE SOLUTIONS
PRODUCT DEFINITION MANUFACTURING PROCESS DEFINITION
MANUFACTURING SYSTEM DEFINITION PLANT LAYOUT DEFINITION MATERIAL HANDLING SYSTEM DEFINITION
SYSTEM VALIDATION
SYSTEM SELECTION
PROFIT ANALYSIS
Fig 1.6 Production system: a complete design framework MHD material handling device (Manzini et al 2006a)
An existing production system must follow a tinuous improvement process based on the multitar-get scenario, as described in Sect 1.2 First of all,the company must analyze the structure of the prod-uct mix in the production system, seeking to ratio-nalize it, e g., by applying some effective supporting
Trang 29con-1.6 Production System Management Processes for Productivity 13
decision-making techniques such as DFM, DFA, and
VRP
Modern companies must put continuous
monitor-ing and evaluation of the degree of innovation of their
processes into operation Consequently, process
inno-vation is an important key factor in company success
In recent years, flexible automation has become a valid
reference point in process innovation
Any production plant needs some revision during
its life cycle, including partial or total substitution of
resources, upgrades, and plant layout reengineering
Consequently, planning and execution of prior
deci-sions are also important for a company already
on-the-job In conclusion, the general framework in Fig 1.6
is also valid for existing production systems
The most important question remains how to
choose the most convenient strategy and effective
supporting decision methods from the very large
collection of solutions available in the literature The
generic case study has its specific peculiarities making
it different from all the others That is why, at a first
Distribution management Production planning
Inventory and purchasing management
Production system management
Location allocation problem
Transporation
Vehicle routing
Aggregate programming
Material requirement planning
Manufacturing resource planning
Fig 1.7 Production system management activities
glance, it is not easy to detect a suitable tool from thewide set of models and methods that can be used tosupport management decision making
1.6 Production System Management Processes for Productivity
This book discusses a set of effective managementprocedures, models, methods, and techniques, directlyaffecting the productivity performance of a productionsystem Even though they mainly deal with main-tenance, safety, and quality assessments, we nowillustrate a conceptual framework which classifiesthe most important management activities into threemacro classes: materials and inventory management,production planning, and product/service distributionmanagement (Fig 1.7) All these activities have to
be managed and optimized by whoever in a businessunit, in a production system, or in an enterprise isconcerned with research for productivity
Trang 30This book can effectively support the managers,
an-alysts, and practitioners in a generic production system
in making the best decisions regarding products,
pro-cesses, and production plants, in accordance with
cus-tomer’s expectations of quality and minimizing
pro-duction costs with particular attention to the repro-duction
of the production system downtimes and to the
reli-ability/availability of products, processes, and
equip-ment The focus of this work is coherent with the
defi-nition of maintenance as “the combination of all
tech-nical, administrative and managerial actions during the
life cycle of an item intended to retain it in, or restore
it to, a state in which it can perform the required
func-tion” (European standard EN 13306:2001 –
Mainte-nance terminology), and with the definition of quality
management as the system which assists in
enhanc-ing customer satisfaction (European standard EN ISO
9000:2006 Quality management systems –
Fundamen-tals and vocabulary)
Consequently, the main keywords of this book are
as follows: productivity, quality and safety by
reliabil-ity engineering, maintenance, qualreliabil-ity, and safety
as-sessment
1.6.1 Inventory and Purchasing
Management
A generic production system needs a fulfillment
sys-tem for the continuous supply of raw materials and
therefore has to cope with material management In
modern companies the traditional economic order
quantity (EOQ) and safety stock methods are
com-bined with a great many effective techniques based
on pull logics, such as just-in-time strategy Other
eligible methodologies, such as consignment stock,
electronic data interchange, comakership, business to
business, and e-marketplaces, provide for very close
cooperation between customers (service clients) and
manufacturers (service providers)
1.6.2 Production Planning
Production planning is a second management
macro-area with significant impact on productivity The aim
of a preliminary definition of production planning is
to provide a fundamental prerequisite for resource
re-quirement planning These programs are scheduled
with reference to different time fences, or planning riods, with an increasing degree of detail: from a wideand outermost time fence, related to aggregate pro-gramming, to a narrow and very close time fence, re-lated to detailed programming
pe-After the aggregated programming phase, rial and resource requirements need to be quantified.Techniques such as the well-known material require-
mate-ment planning and manufacturing resource planning
are usually suitable for this purpose, but the literaturealso contains several models and methods for so-called
advanced planning: advanced planning systems (APS).
Lastly, the final step requires the direct “load” of
machines and assignment of workload This is
short-term scheduling The goal is to define the priorities of
different jobs on different items of equipment and chines
ma-1.6.3 Distribution Management
The third important management problem relates tothe final distribution of products and services Themain problems are the following: the planning of ship-ments, generally issued as distribution resource plan-
ning; the location–allocation problem along the
dis-tributive network, i e., the simultaneous location ofequipment and logistic resources such as distributioncenters and warehousing systems; the allocation ofcustomer demand to the available set of resources; theoptimal selection of transportation systems; the vehi-cle routing; and, finally, the execution of distributionactivities
1.7 Research into Productivity and Maintenance Systems
The frameworks for the design and management of
a production system, illustrated in Figs 1.1, 1.5,and 1.6, underline how important the contributions
of reliability, availability, and quality of resources(equipment, employees, and production plants) are tothe production of products or services In particular,
there is a very strong positive link between
mainte-nance and productivity For example, the availability
of a production plant is an absolute necessity for thescheduling of work orders, and spare parts forecasting
Trang 311.7 Research into Productivity and Maintenance Systems 15
is a fundamental part of the planning and design
processes (see Chap 11)
A very important factor in purchasing is the
qual-ity control of raw materials, and the new design
tech-niques, such as DFM and DFA, must guarantee quality
levels set as targets
Modern companies must consider maintenance
strategies, rules, procedures, and actions to be some of
the most important issues and factors in their success
In other words, the effective design and
manage-ment of a production system requires the effective
design and management of the correlated maintenance
process and system
A maintenance system requires strategic planning,
dedicated budgets, relevant investments in terms of
money and human resources, equipment, and spare
parts too In particular, the availability and
commit-ment of personnel at all levels of an organization
also includes the application of the maintenance
pro-cess
An effective maintenance system provides
support-ing decision-maksupport-ing techniques, models, and
method-ologies, and enables maintenance personnel to apply
them in order to set the global production costs at
a minimum and to ensure high levels of customer
ser-vice To achieve this purpose in a production system,
those elements such as the ability, skill, and
knowl-edge required by the whole organization and in
partic-ular by product designers, production managers, and
people who directly operate in the production plants,
are crucial
In conclusion, as illustrated in Fig 1.8,
mainte-nance techniques, including also quality and safety
as-sessment tools and procedures, represent very
effec-tive instruments for research into productivity, safety,
and quality as modern companies are now forced to
pursue them relentlessly This issue will be
demon-strated and supported in detail in the following
chap-ters
The following chapters are organized as follows:
• Chapter 2 introduces quality assessment and
presents statistical quality control models and
methods and Six Sigma theory and applications
A brief illustration and discussion of European
standards and specifications for quality assessment
is also presented
• Chapter 3 deals with safety assessment and risk
as-sessment with particular attention being given to
quality assessment
risk analysis and risk reduction procedures Someexemplifying standards and specifications are illus-trated
• Chapter 4 introduces maintenance and maintenancemanagement in production systems An illustration
of total productive maintenance production ophy is also presented
philos-• Chapter 5 introduces the main reliability and tenance terminology and nomenclature It presentsand applies basic statistics and reliability modelsfor the evaluation of failure (and repair) activities
main-in repairable (and nonrepairable) elementary ponents
com-• Chapter 6 illustrates some effective statistics-basedmodels and methods for the evaluation and predic-tion of reliability This chapter also discusses the el-ementary reliability configurations of a productionsystem, the so-called reliability block diagrams
• Chapter 7 discusses the maintenance informationsystems and their strategic role in maintenance
management A discussion on computer
mainte-nance management software (CMMS) is also
pre-sented Finally, failure rate prediction models areillustrated and applied
• Chapter 8 presents and applies models for theanalysis and evaluation of failure mode, effects,and criticality in modern production systems Thenmodels, methods, and tools (failure modes and ef-fects analysis and failure mode, effects, and criti-
Trang 32cality analysis, fault tree analysis, Markov chains,
Monte Carlo dynamic simulation) for the
evalua-tion of reliability in complex producevalua-tion systems
are illustrated and applied to numerical examples
and case studies
• Chapter 9 presents several models and methods to
plan and conduct maintenance actions in
accor-dance with corrective, preventive, and inspection
strategies and rules Several numerical examplesand applications are illustrated
• Chapter 10 illustrates advanced models and ods for maintenance management
meth-• Chapter 11 discusses spare parts management andfulfillment models and tools
• Chapter 12 presents and discusses significant casestudies on reliability and maintenance engineering
Trang 33Quality Management Systems
Contents
2.3.1 Quality Audit, Conformity, and Certification 19
2.3.2 Environmental Standards 21
2.4.1 The Central Limit Theorem 23
2.4.2 Terms and Definition in Statistical Quality
2.7.6 Numerical Example, s-Chart and N x-Chart 33
2.9.1 Numerical Example, Capability Analysis
and Normal Probability 42
2.9.2 Numerical Examples, Capability Analysis
and Nonnormal Probability 46
2.10.1 Numerical Examples 51 2.10.2 Six Sigma in the Service Sector Thermal Water Treatments for Health and Fitness 51
Organizations depend on their customers and fore should understand current and future customerneeds, should meet customer requirements and strive
there-to exceed custhere-tomer expectations Identifying, derstanding and managing interrelated processes as
un-a system contributes to the orgun-anizun-ation’s ness and efficiency in achieving its objectives (ENISO 9000:2006 Quality management systems – fun-damentals and vocabulary)
effective-Nowadays, user and consumer assume their ownchoices regarding very important competitive factorssuch as quality of product, production process, andproduction system Users and consumers start makingtheir choices when they feel they are able to value andcompare firms with high quality standards by them-selves
This chapter introduces the reader to the main lems concerning management and control of a qual-ity system and also the main supporting decision mea-sures and tools for so-called statistical quality control(SQC) and Six Sigma
prob-2.1 Introduction to Quality Management Systems
The standard EN ISO 8402:1995, replaced by ENISO 9000:2005, defines “quality” as “the totality ofcharacteristics of an entity that bear on its ability tosatisfy stated and implied needs,” and “product” as
© Springer 2010
Trang 34“the result of activities or processes and can be
tan-gible or intantan-gible, or a combination thereof.”
Conse-quently, these definitions refer to production systems
both in industrial sectors, such as insurance, banking,
and transport, and service sectors, in accordance with
the conceptual framework introduced in Chap 1
An-other synthetic definition of quality is the “degree to
which a set of inherent characteristics fulfills
require-ments” (ISO 9000:2005)
A requirement is an expectation; it is generally
re-lated to the organization, customers, or other
inter-ested, or involved, parties We choose to name all
these entities, i e., the stakeholders of the
organiza-tion, as customers and, consequently, the basic
key-word in quality management is customer satisfaction.
Another basic term is capability as the ability of the
organization, system, or process to realize a product
fulfilling the requirements
A quality management system is a particular
man-agement system driving the organization with regard
to quality In other words, it assists companies and
or-ganizations in enhancing customer satisfaction This
is the result of products capable of satisfying the
ever-changing customer needs and expectations that
conse-quently require the continuous improvement of
prod-ucts, processes, and production systems
Quality management is a responsibility at all levels
of management and involves all members of an
organi-Fig 2.1 Process-based
qual-ity management system
Interested parties
Management responsability
Resource management realization
Mesaurement analysis &
zation For this reason, in the 1980s total quality
man-agement (TQM) as a business manman-agement strategy
aimed at embedding awareness of quality in all nizational processes found very great success Accord-ing to the International Organization for Standardiza-tion (ISO) standards (ISO 9000:2006), the basic stepsfor developing and implementing a quality manage-ment system are:
orga-• determination of needs and expectations of tomers and other involved parties;
cus-• definition of the organization’s quality policy andquality objectives;
• determination of processes and responsibilities forquality assessment;
• identification and choice of production resourcesnecessary to attain the quality objectives;
• determination and application of methods to sure the effectiveness and efficiency of each processwithin the production system;
mea-• prevention of nonconformities and deletion of therelated causes;
• definition and application of a process for uous improvement of the quality management sys-tem
contin-Figure 2.1 presents the model of a process-based ity management system, as proposed by the ISO stan-dards
Trang 35qual-2.3 ISO Standards for Quality Management and Assessment 19
2.2 International Standards
and Specifications
According to European Directive 98/34/EC of 22 June
1998, a “standard” is a technical specification for
re-peated or continuous application approved, without
a compulsory compliance, by one of the following
rec-ognized standardization bodies:
• ISO;
• European standard (EN);
• national standard (e g., in Italy UNI)
Standards are therefore documents defining the
char-acteristics (dimensional, performance, environmental,
safety, organizational, etc.) of a product, process, or
service, in accordance with the state of the art, and
they are the result of input received from thousands of
experts working in the European Union and elsewhere
in the world Standards have the following distinctive
characteristics:
• Consensuality: They must be approved with the
consensus of the participants in the works of
prepa-ration and confirmed by the result of a public
en-quiry
• Democracy: All the interested economic/social
par-ties can participate in the works and, above all,
have the opportunity to make observations during
the procedure prior to final and public approval
• Transparency: UNI specifies the basic milestones
of the approval procedure for a draft standard,
plac-ing the draft documents at the disposal of the
inter-ested parties for consultation
• Voluntary nature: Standards are a source of
refer-ence that the interested parties agree to apply freely
on a noncompulsory basis
In particular CEN, the European Committee for
Stan-dardization founded in 1961 by the national standards
bodies in the European Economic Community and
EFTA countries, is contributing to the objectives of the
European Union and European Economic Area with
voluntary technical standards promoting free trade,
safety of workers and consumers, interoperability of
networks, environmental protection, exploitation of
re-search and development programs, and public
procure-ment
CEN works closely with the European
Commit-tee for Electrotechnical Standardization (CENELEC),
the European Telecommunications Standards Institute
(ETSI), and the ISO CEN is a multisectorial zation serving several sectors in different ways, as il-lustrated in the next sections and chapters dealing withsafety assessment
organi-2.3 ISO Standards for Quality Management and Assessment
The main issues developed by the technical committeefor the area of quality are:
1 CEN/CLC/TC 1 – criteria for conformity ment bodies;
assess-2 CEN/SS F20 – quality assurance
Table 2.1 reports the list of standards belonging to thefirst technical committee since 2008
Similarly, Table 2.2 reports the list of standards longing to the technical committee CEN/SS F20 since
be-2008, while Table 2.3 shows the list of standards rently under development
cur-Quality issues are discussed in several standardsthat belong to other technical groups For example,there is a list of standards of the aerospace series deal-ing with quality, as reported in Table 2.4 Table 2.5presents a list of standards for quality managementsystems in health care services Similarly, there areother sets of standards for specific sectors, businesses,
qual-to a standard or a set of standards, e g., ISO 9001 orISO 14001 The audit process is the basis for the dec-laration of conformity
The audit process is conducted by an auditor, or anaudit team, i e., a person or a team, with competence
Trang 36Table 2.1 CEN/CLC/TC 1 criteria for conformity assessment bodies, standards published since 2008
EN 45011:1998 General requirements for bodies operating product certification systems (ISO/IEC Guide
65:1996)
EN 45503:1996 Attestation Standard for the assessment of contract award procedures of entities
operating in the water, energy, transport and telecommunications sectors
EN ISO/IEC 17000:2004 Conformity assessment – Vocabulary and general principles (ISO/IEC 17000:2004)
EN ISO/IEC 17011:2004 Conformity assessment – General requirements for accreditation bodies accrediting
conformity assessment bodies (ISO/IEC 17011:2004)
EN ISO/IEC 17020:2004 General criteria for the operation of various types of bodies performing inspection
(ISO/IEC 17020:1998)
EN ISO/IEC 17021:2006 Conformity assessment – Requirements for bodies providing audit and certification of
management systems (ISO/IEC 17021:2006)
EN ISO/IEC 17024:2003 Conformity assessment – General requirements for bodies operating certification of
EN ISO/IEC 17040:2005 Conformity assessment – General requirements for peer assessment of conformity
assessment bodies and accreditation bodies (ISO/IEC 17040:2005)
EN ISO/IEC 17050-1:2004 Conformity assessment – Supplier’s declaration of conformity – Part 1: General
EN 45020:2006 Standardization and related activities – General vocabulary (ISO/IEC Guide 2:2004)
EN ISO 10012:2003 Measurement management systems – Requirements for measurement processes and
measuring equipment (ISO 10012:2003)
EN ISO 15378:2007 Primary packaging materials for medicinal products – Particular requirements for the
application of ISO 9001:2000, with reference to good manufacturing practice (GMP) (ISO 15378:2006)
EN ISO 19011:2002 Guidelines for quality and/or environmental management systems auditing
(ISO 19011:2002)
EN ISO 9000:2005 Quality management systems – Fundamentals and vocabulary (ISO 9000:2005)
EN ISO 9001:2000 Quality management systems – Requirements (ISO 9001:2000)
EN ISO 9004:2000 Quality management systems – Guidelines for performance improvements
prEN ISO 19011 rev Guidelines for auditing management systems
prEN ISO 9004 Managing for the sustained success of an organization – A quality management
approach (ISO/DIS 9004:2008)
Trang 372.3 ISO Standards for Quality Management and Assessment 21
Table 2.4 Aerospace series, quality standards
EN 9102:2006 Aerospace series – Quality systems – First article inspection
EN 9103:2005 Aerospace series – Quality management systems – Variation management of key
EN 9104:2006 Aerospace series – Quality management systems –Requirements for Aerospace Quality
Management System Certification/Registrations Programs
EN 9111:2005 Aerospace series – Quality management systems – Assessment applicable to
maintenance organizations (based on ISO 9001:2000)
EN 9121:2005 Aerospace series – Quality management systems – Assessment applicable to stockist
distributors (based on ISO 9001:2000)
EN 9132:2006 Aerospace series – Quality management systems – Data Matrix Quality Requirements
for Parts Marking
EN 4179:2005 Aerospace series – Qualification and approval of personnel for nondestructive testing
EN 4617:2006 Aerospace series – Recommended practices for standardizing company standards
EN 9101:2008 Aerospace series – Quality management systems – Assessment (based on
ISO 9001:2000)
EN 9104-002:2008 Aerospace series – Quality management systems – Part 002: Requirements for Oversight
of Aerospace Quality Management System Certification/Registrations Programs
Table 2.5 CEN/TC 362, health care services, quality management systems
CEN/TR 15592:200 Health services – Quality management systems – Guide for the use of
EN ISO 9004:2000 in health services for performance improvement CEN/TS 15224:2005 Health services – Quality management systems – Guide for the use of
EN ISO 9001:2000
to conduct an audit, in accordance with an audit
pro-gram consisting of a set of one or more audits planned
for a specific time frame Audit findings are used to
as-sess the effectiveness of the quality management
sys-tem and to identify opportunities for improvement
Guidance on auditing is provided by ISO 19011:2002
(Guidelines for quality and/or environmental
manage-ment systems auditing)
The main advantages arising from certification are:
• improvement of the company image;
• increase of productivity and company profit;
• rise of contractual power;
• quality guarantee of the product for the client
In the process of auditing and certification, the
docu-mentation plays a very important role, enabling
com-munication of intent and consistency of action Several
types of documents are generated in quality
manage-ment systems
2.3.2 Environmental Standards
Every standard, even if related to product, service,
or process, has an environmental impact For a uct this can vary according to the different stages ofthe product life cycle, such as production, distribu-tion, use, and end-of-life To this purpose, CEN hasrecently been playing a major role in reducing envi-ronmental impacts by influencing the choices that aremade in connection with the design of products andprocesses CEN has in place an organizational struc-ture to respond to the challenges posed by the devel-opments within the various sectors, as well as by theevolution of the legislation within the European Com-munity The main bodies within CEN are:
prod-1 The Strategic Advisory Body on the Environment(SABE) – an advisory body for the CEN TechnicalBoard on issues related to environment Stakehold-ers identify environmental issues of importance
Trang 38to the standardization system and suggest
corre-sponding solutions
2 The CEN Environmental Helpdesk provides
sup-port and services to CEN Technical Bodies on how
to address environmental aspects in standards
3 Sectors – some sectors established a dedicated
body to address environmental matters associated
with their specific needs, such as the
Construc-tion Sector Network Project for the Environment
(CSNPE)
4 Associates – two CEN associate members provide
a particular focus on the environment within
stan-dardization:
• European Environmental Citizens Organization
for Standardization (ECOS);
• European Association for the Coordination of
Consumer Representation in Standardization
(ANEC)
Table 2.6 Technical committees on the environment
CEN/TC 351 Construction Products – Assessment of release of dangerous substances
Table 2.7 Committee CEN/SS S26 – environmental management
EN ISO 14021:2001 Environmental labels and declarations – Self-declared environmental claims (Type II
environmental labelling) (ISO 14021:1999)
EN ISO 14020:2001 Environmental labels and declarations – General principles (ISO 14020:2000)
EN ISO 14040:2006 Environmental management – Life cycle assessment – Principles and framework
(ISO 14040:2006)
EN ISO 14044:2006 Environmental management – Life cycle assessment – Requirements and guidelines
(ISO 14044:2006) prEN ISO 14005 Environmental management systems – Guidelines for a staged implementation of an
environmental management system, including the use of environmental performance evaluation
Table 2.6 reports the list of technical committees onthe environment
There are several standards on environmental agement To exemplify this, Table 2.7 reports the list
man-of standards grouped in accordance with the tee CEN/SS S26 – environmental management.ISO 14000 is a family of standards supporting theorganizations on the containment of the polluting ef-fects on air, water, or land derived by their operations,
commit-in compliance with applicable laws and regulations Inparticular, ISO 14001 is the international specificationfor an environmental management system (EMS) Itspecifies requirements for establishing an environmen-tal policy, determining environmental aspects and im-pacts of products/activities/services, planning environ-mental objectives and measurable targets, implemen-tation and operation of programs to meet objectivesand targets, checking and corrective action, and man-agement review
Trang 392.4 Introduction to Statistical Methods for Quality Control 23
Fig 2.2 Central limit theorem, examples
2.4 Introduction to Statistical Methods
for Quality Control
The aim of the remainder of this chapter is the
intro-duction and exemplification of effective models and
methods for statistical quality control These tools are
very diffuse and can be used to guarantee also the
reliability,1 productivity and safety of a generic
pro-duction system in accordance with the purpose of this
book, as illustrated in Chap 1
2.4.1 The Central Limit Theorem
This section briefly summarizes the basic result
ob-tained by this famous theorem Given a population or
process, a random variable x, with mean and
stan-dard deviation , let Nx be the mean of a random
sam-ple made of n elements x1; x2; : : : ; xnextracted from
this population: when the sample size n is sufficiently
large, the sampling distribution of the random
vari-1 Reliability, properly defined in Chap 5, can be also defined as
“quality in use.”
able Nx can be approximated by a normal distribution
The larger the value of n, the better the approximation.This theorem holds irrespective of the shape of thepopulation, i e., of the density function of the vari-able x
The analytic translation of the theorem is given bythe following equations:
each value of size n
Figure 2.3 quantitatively demonstrates the centrallimit theorem starting from a set of random valuesdistributed in accordance with a uniform distribution
Œ0; 10: the variable Nx is a normally distributed
vari-able when the number of items used for the calculus
of mean Nxi is sufficiently large In detail, in Fig 2.3the size n is assumed be 2, 5, and 20
Trang 409.0 7.5 6.0 4.5 3.0 1.5
0.20 0.15 0.10 0.05 0.00
8 7 6 5 4 3 2
0.8 0.6 0.4 0.2 0.0
DATA (n=1)
Mean (n=2)
Histogram of DATA (n=1) and means (n>1)
2.4.2 Terms and Definition in Statistical
Quality Control
Quality control is a part of quality management
(ISO 9000:2005) focused on the fulfillment of quality
requirements It is a systematic process to monitor and
improve the quality of a product, e g., a manufactured
article, or service by achieving the quality of the
production process and the production plant A list of
basic terms and definitions in accordance with the ISO
standards follows:
• Process, set of interrelated activities turning input
into output It is a sequence of steps that results in
an outcome
• Product, result of a process.
• Defect, not fulfillment of a requirement related to
an intended or specified use
• Measurement process, set of operations to
deter-mine the value of a quantity
• Key characteristic, a quality characteristic the
prod-uct or service should have to fulfill customer
re-quirements and expectations
• Value of a key characteristic For several products
a single value is the desired quality level for a
char-acteristic
• Nominal or target value It is the expected value
for the key characteristic It is almost impossible to
make each unit of product or service identical to the
next; consequently it is nonsense to ask for cal items having a key characteristic value exactlyequal to the target value This need for flexibility
identi-is supported by the introduction of limits and ances
toler-• Specification limit, or tolerance, conformance
boundary, range, specified for a characteristic
The lower specification limit (LSL) is the lower conformance boundary, the upper specification
limit (USL) is the upper conformance
• One-sided tolerance It relates to characteristics
with only one specification limit
• Two-sided tolerance It refers to characteristics with
both USLs and LSLs
• Nonconformity It is a nonfulfillment of a
require-ment It is generally associated with a unit: a conformity unit, i e., a unit that does not meet thespecifications
non-• Nonconforming product or service A product or
service with one or more nonconformities A conforming product is not necessary defective, i e.,
non-no longer fit for use