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INTRODUCTION TO

INDUSTRIAL

ENGINEERING

(2)

Adedeji B. Badiru

Air Force Institute of Technology (AFIT) – Dayton, Ohio

PUBLISHED TITLES

Carbon Footprint Analysis: Concepts, Methods, Implementation, and Case Studies, Matthew John Franchetti & Defne Apul

Cellular Manufacturing: Mitigating Risk and Uncertainty, John X. Wang Communication for Continuous Improvement Projects, Tina Agustiady

Computational Economic Analysis for Engineering and Industry, Adedeji B. Badiru & Olufemi A. Omitaomu

Conveyors: Applications, Selection, and Integration, Patrick M. McGuire Culture and Trust in Technology-Driven Organizations, Frances Alston

Global Engineering: Design, Decision Making, and Communication, Carlos Acosta, V. Jorge Leon, Charles Conrad, & Cesar O. Malave

Global Manufacturing Technology Transfer: Africa–USA Strategies, Adaptations, and Management, Adedeji B. Badiru

Guide to Environment Safety and Health Management: Developing, Implementing, and Maintaining a Continuous Improvement Program, Frances Alston & Emily J. Millikin Handbook of Emergency Response: A Human Factors and Systems Engineering Approach,

Adedeji B. Badiru & LeeAnn Racz

Handbook of Industrial Engineering Equations, Formulas, and Calculations, Adedeji B. Badiru & Olufemi A. Omitaomu

Handbook of Industrial and Systems Engineering, Second Edition, Adedeji B. Badiru Handbook of Military Industrial Engineering, Adedeji B. Badiru & Marlin U. Thomas Industrial Control Systems: Mathematical and Statistical Models and Techniques,

Adedeji B. Badiru, Oye Ibidapo-Obe, & Babatunde J. Ayeni

Industrial Project Management: Concepts, Tools, and Techniques, Adedeji B. Badiru, Abidemi Badiru, & Adetokunboh Badiru

Inventory Management: Non-Classical Views, Mohamad Y. Jaber Kansei Engineering—2-volume set

Innovations of Kansei Engineering, Mitsuo Nagamachi & Anitawati Mohd LokmanKansei/Affective Engineering, Mitsuo Nagamachi

Kansei Innovation: Practical Design Applications for Product and Service Development, Mitsuo Nagamachi & Anitawati Mohd Lokman

Knowledge Discovery from Sensor Data, Auroop R. Ganguly, João Gama, Olufemi A. Omitaomu, Mohamed Medhat Gaber, & Ranga Raju Vatsavai

Learning Curves: Theory, Models, and Applications, Mohamad Y. Jaber

Managing Projects as Investments: Earned Value to Business Value, Stephen A. Devaux Modern Construction: Lean Project Delivery and Integrated Practices, Lincoln Harding Forbes &

Syed M. Ahmed

Moving from Project Management to Project Leadership: A Practical Guide to Leading Groups, R. Camper Bull

Project Management: Systems, Principles, and Applications, Adedeji B. Badiru

Samuel O. Osisanya

Quality Management in Construction Projects, Abdul Razzak Rumane Quality Tools for Managing Construction Projects, Abdul Razzak Rumane

Social Responsibility: Failure Mode Effects and Analysis, Holly Alison Duckworth & Rosemond Ann Moore

Statistical Techniques for Project Control, Adedeji B. Badiru & Tina Agustiady STEP Project Management: Guide for Science, Technology, and Engineering Projects,

Adedeji B. Badiru

Sustainability: Utilizing Lean Six Sigma Techniques, Tina Agustiady & Adedeji B. Badiru Systems Thinking: Coping with 21st Century Problems, John Turner Boardman & Brian J. Sauser Techonomics: The Theory of Industrial Evolution, H. Lee Martin

Total Productive Maintenance: Strategies and Implementation Guide, Tina Agustiady & Elizabeth A. Cudney

Total Project Control: A Practitioner’s Guide to Managing Projects as Investments, Second Edition, Stephen A. Devaux

Triple C Model of Project Management: Communication, Cooperation, Coordination, Adedeji B. Badiru

FORTHCOMING TITLES

3D Printing Handbook: Product Development for the Defense Industry, Adedeji B. Badiru & Vhance V. Valencia

Company Success in Manufacturing Organizations: A Holistic Systems Approach, Ana M. Ferreras & Lesia L. Crumpton-Young

Design for Profitability: Guidelines to Cost Effectively Management the Development Process of Complex Products, Salah Ahmed Mohamed Elmoselhy

Essentials of Engineering Leadership and Innovation, Pamela McCauley-Bush & Lesia L. Crumpton-Young

Handbook of Construction Management: Scope, Schedule, and Cost Control, Abdul Razzak Rumane

Handbook of Measurements: Benchmarks for Systems Accuracy and Precision, Adedeji B. Badiru & LeeAnn Racz

Introduction to Industrial Engineering, Second Edition, Avraham Shtub & Yuval Cohen Manufacturing and Enterprise: An Integrated Systems Approach, Adedeji B. Badiru,

Oye Ibidapo-Obe & Babatunde J. Ayeni

Project Management for Research: Tools and Techniques for Science and Technology, Adedeji B. Badiru, Vhance V. Valencia & Christina Rusnock

Project Management Simplified: A Step-by-Step Process, Barbara Karten

A Six Sigma Approach to Sustainability: Continual Improvement for Social Responsibility, Holly Allison Duckworth & Andrea Hoffmeier Zimmerman

Work Design: A Systematic Approach, Adedeji B. Badiru

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Project Management for the Oil and Gas Industry: A World System Approach, Adedeji B. Badiru & Samuel O. Osisanya

Quality Management in Construction Projects, Abdul Razzak Rumane Quality Tools for Managing Construction Projects, Abdul Razzak Rumane

Social Responsibility: Failure Mode Effects and Analysis, Holly Alison Duckworth & Rosemond Ann Moore

Statistical Techniques for Project Control, Adedeji B. Badiru & Tina Agustiady STEP Project Management: Guide for Science, Technology, and Engineering Projects,

Adedeji B. Badiru

Sustainability: Utilizing Lean Six Sigma Techniques, Tina Agustiady & Adedeji B. Badiru Systems Thinking: Coping with 21st Century Problems, John Turner Boardman & Brian J. Sauser Techonomics: The Theory of Industrial Evolution, H. Lee Martin

Total Productive Maintenance: Strategies and Implementation Guide, Tina Agustiady & Elizabeth A. Cudney

Total Project Control: A Practitioner’s Guide to Managing Projects as Investments, Second Edition, Stephen A. Devaux

Triple C Model of Project Management: Communication, Cooperation, Coordination, Adedeji B. Badiru

FORTHCOMING TITLES

3D Printing Handbook: Product Development for the Defense Industry, Adedeji B. Badiru & Vhance V. Valencia

Company Success in Manufacturing Organizations: A Holistic Systems Approach, Ana M. Ferreras & Lesia L. Crumpton-Young

Design for Profitability: Guidelines to Cost Effectively Management the Development Process of Complex Products, Salah Ahmed Mohamed Elmoselhy

Essentials of Engineering Leadership and Innovation, Pamela McCauley-Bush & Lesia L. Crumpton-Young

Handbook of Construction Management: Scope, Schedule, and Cost Control, Abdul Razzak Rumane

Handbook of Measurements: Benchmarks for Systems Accuracy and Precision, Adedeji B. Badiru & LeeAnn Racz

Introduction to Industrial Engineering, Second Edition, Avraham Shtub & Yuval Cohen Manufacturing and Enterprise: An Integrated Systems Approach, Adedeji B. Badiru,

Oye Ibidapo-Obe & Babatunde J. Ayeni

Project Management for Research: Tools and Techniques for Science and Technology, Adedeji B. Badiru, Vhance V. Valencia & Christina Rusnock

Project Management Simplified: A Step-by-Step Process, Barbara Karten

A Six Sigma Approach to Sustainability: Continual Improvement for Social Responsibility, Holly Allison Duckworth & Andrea Hoffmeier Zimmerman

Work Design: A Systematic Approach, Adedeji B. Badiru PUBLISHED TITLES

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INTRODUCTION TO

INDUSTRIAL

ENGINEERING

Avraham Shtub • Yuval Cohen

S E C O N D E D I T I O N

Boca Raton London New York CRC Press is an imprint of the

Taylor & Francis Group, an informa business

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CRC Press

Taylor & Francis Group

6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742

© 2016 by Taylor & Francis Group, LLC

CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works

Version Date: 20151111

International Standard Book Number-13: 978-1-4987-0602-5 (eBook - PDF)

This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint.

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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

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To my wife Ailona Shtub—Avi Shtub To my family—Yuval Cohen

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ix

Contents

Preface ... xix Authors ...xxvii 1. Introduction ...1 Educational Goals ...1

1.1 Definitions and Examples Related to Industrial Engineering ...1

1.1.1 Engineering ...1

1.1.2 Industrial Engineering ...2

1.1.3 Industrial Engineers ...2

1.1.4 Production/Service Systems ...3

1.1.5 What Do Industrial Engineers Do? ...3

1.1.6 Tools Used by the Industrial Engineer ...3

1.1.6.1 Understanding “Engineering Language”: Drawings, Specifications, etc. ...3

1.1.6.2 Understanding the Physical Processes, Knowledge of the Basic Laws of Physics ...3

1.1.6.3 Knowledge of Economics and Financial Management ...4

1.1.6.4 Understanding Mathematical and Statistical Models ...4

1.1.6.5 Knowledge of Human Resources Management ....5

1.1.6.6 Knowledge of Computerized Information Systems ...5

1.2 Models ...5

1.2.1 Use of Models ...6

1.2.2 Dynamic Aspect: Simulation and Dynamics Systems ...7

1.2.3 Simulation Models and Decision Making ...8

1.3 Teaching Industrial Engineering ...9

1.3.1 Industrial Engineering Curricula ... 10

1.4 Historical Overview ... 10

1.4.1 Industrial Revolution: Eighteenth Century ... 11

1.4.2 New Developments in the Early Twentieth Century ... 11

1.4.3 Historical Timeline ... 16

1.5 Impact of Globalization on the Industrial Engineering Profession ... 17 1.5.1 Cost ... 17 1.5.2 Quality ... 18 1.5.3 Time ... 18 1.5.4 Flexibility ... 19

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1.6 Industrial Engineering and Systems ...20

1.7 Industrial Engineering and Process Design ...20

1.8 Need for Integrated and Dynamic Processes ... 21

1.9 Summary ...22

References ...22

2. Modeling the Organizational Structure and the Facility Layout ...23

Educational Goals ...23

2.1 Introduction ...23

2.1.1 What Is an Organization? ... 24

2.1.2 Organizations as a Human Creation ...25

2.1.3 Organizations as Production Systems ...25

2.1.4 Organizations as Economic Entities ...25

2.1.5 Organizations as Social Systems ...25

2.1.6 Organizations as Goal-Oriented Systems ...26

2.1.7 Organizations as Open Systems ...26

2.2 Development of Organizations ...26

2.3 Examples of Organizational Structures...28

2.3.1 Project-Oriented Organizational Structure ...29

2.3.2 Matrix Organization ...30

2.3.3 Functional Organization ... 32

2.3.4 Process-Based and Concurrent Engineering Organizations ...34

2.3.5 Product/Service-Based Organizations ... 37

2.3.6 Humans and Organizations ...38

2.3.6.1 Human Factor Industrial Engineering Courses ... 39

2.3.6.2 Learning ...40

2.3.6.3 Motivation ...43

2.4 Organizing Workplace Equipment and Machinery ...46

2.4.1 Workshop Layout ...47

2.4.2 Functional Layout (for Job Shop and Batch Processing) ...47

2.4.3 Group Technology: Cellular Manufacturing ...50

2.4.4 Flow Shop ... 52

2.4.5 Assembly Line ...54

2.4.6 Continuous Production Layout...54

2.5 Organization-Wide Processes ...55

2.5.1 Overcoming the Organizational Structure and Walls for Better Competitiveness ...55

2.5.2 Automation ... 57

2.6 Summary ... 57

References ...58

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xi Contents 3. Project Management ... 61 Educational Goals ... 61 3.1 Introduction ... 61 3.1.1 What Is a Project? ...63

3.1.2 Uncertainty and Risks ...65

3.1.3 Project Life Cycle ...68

3.2 Project Initiation ... 69

3.2.1 Gathering Information ... 69

3.2.2 Selection of Alternatives within the Project Scope ...71

3.3 Project Scheduling ... 74

3.3.1 Project-Scheduling Models ...75

3.3.2 Gantt Chart ... 76

3.3.3 Critical Path Method and Network Models ...77

3.3.3.1 CPM Analysis ... 78

3.3.4 Critical Path Network Analysis ...80

3.3.5 Uncertainty and Project Duration ...80

3.3.6 Resource Scheduling ... 81

3.4 Implementation Phase—Project Execution Monitoring and Control ...83

3.4.1 Monitoring and Control ...83

3.4.2 Testing ...84

3.4.3 Project Ending ...84

3.5 Computerized Systems for Project Management ...85

3.6 Summary ...85

Further Reading ...86

4. Information Systems ...87

Educational Goals ...87

4.1 Introduction ...87

4.1.1 Use of Information to Support Decision Making ...90

4.1.2 Data Handling ...93

4.2 Components of the Information System ...95

4.2.1 Database Systems ...96

4.2.2 Queries and Structured Query Language (SQL) ...97

4.2.3 Data Flow Diagrams ...97

4.2.4 Model Base ...98

4.3 Quality of Information ... 102

4.4 Forecasting ... 102

4.4.1 Moving Average Model ... 103

4.4.2 Estimating the Quality of Forecasts ... 103

4.4.3 Exponential Smoothing Model ... 104

References ... 107

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5. Supply Chain Management: The Interface with the Customer ... 109

Educational Goals ... 109

5.1 Introduction to the Customer Interface and Its Design ... 110

5.2 The Impact of Inventory ... 113

5.2.1 Forecast-Based Orders ... 113

5.2.2 Production to Order ... 114

5.2.3 Assemble to Order ... 115

5.2.4 Customer Interface Policy Considerations ... 115

5.3 Bill of Materials ... 116

5.4 Master Production Schedule ... 118

5.5 Delivery Time and Time-Based Competition ... 120

5.6 Avoiding Unnecessary Activities ... 121

5.7 Shortening the Duration of Value-Added and Necessary Activities ...122

5.7.1 Reducing Delays in the Process ... 123

5.7.1.1 Several Reasons for Transportation Delays ... 123

5.7.1.2 Delays in Operations Are Created for Several Reasons ... 123

5.7.1.3 Delays in the Decision-Making Process Are Created for Several Reasons ... 124

5.8 Quality-Based Competition ... 125

5.8.1 What Is Quality? ... 125

5.8.2 Quality Function Deployment Model ... 127

5.9 Cost-Based Competition... 133

5.9.1 Effect of Cost on Profit ... 133

5.10 Flexibility-Based Competition... 134

5.11 Summary ... 136

References ... 136

6. Interface with Suppliers and Subcontractors ... 139

6.1 Procurement and Outsourcing for Gaining Competitive Advantage ... 139

6.2 Purchasing from an External Source: The “Make or Buy” Decisions ... 141

6.2.1 Capacity Considerations ... 142

6.2.2 Know-How Considerations ... 142

6.2.3 Core Technology Considerations ... 142

6.2.4 Economies of Scale Considerations ... 142

6.2.5 Quality Considerations ... 143

6.2.6 Control Considerations ... 143

6.2.7 Accessibility Considerations ... 143

6.3 Introduction to Suppliers Management ... 144

6.3.1 Finding Potential Suppliers by Requests for Information, Quotations, Bids, or Proposals ... 144

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xiii

Contents

6.3.2 Developing the Specifications ... 146

6.3.3 Delivery Issues ... 147

6.3.4 Quality Issues ... 147

6.3.5 Contractual Issues... 148

6.4 Selecting the Right Suppliers ... 149

6.5 Managing the Process: Contract Management ... 150

6.6 E-commerce and Supplier Management ... 152

6.6.1 Inventory Management: Cost/Benefit Considerations ... 154

6.7 Benefits of Inventories ... 155

6.7.1 Time-Based Competition ... 155

6.7.2 Cost-Based Competition ... 156

6.7.3 Technological Considerations ... 157

6.8 Costs Related to Inventory ... 157

6.8.1 Pareto Analysis (or ABC Analysis) ... 159

6.9 Inventory Management Models and the Assumptions on Which They Are Based ... 160

6.9.1 Economic Order Quantity Model ... 161

6.10 Summary ... 164

References ... 164

7. Scheduling ... 167

7.1 Introduction to Operational Scheduling ... 167

7.1.1 Simple Gantt Chart ... 168

7.1.2 Flow Time ... 168

7.1.3 Due Dates ... 168

7.1.4 Delays ... 168

7.2 Single-Machine Scheduling ... 170

7.2.1 Simple Priority Rules ... 170

7.2.2 Complex Priority Rules ... 172

7.3 Scheduling the Job Shop ... 173

7.3.1 Single-Machine Scheduling in a Job Shop ... 175

7.3.2 Use of the Gantt Chart as a Job Shop Scheduling Aid ...175

7.4 Schedule Control ... 182

7.5 Flow Shop Scheduling ... 183

7.5.1 Johnson Algorithm ... 184

7.5.2 Scheduling the Example Problem ... 185

7.6 Applying the JIT Philosophy in Scheduling ... 186

7.6.1 Illustrating the Kanban Card System ... 189

7.7 Theory of Constraints and the Drum Buffer Rope Approach to Scheduling ... 190

7.7.1 Illustrating the Drum Buffer Rope System ... 191

7.8 Summary ... 194

References ... 195

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8. Streamlining the Transformation Process: Material

Requirements Planning Systems ... 197

8.1 Need for Material Requirements Planning ... 197

8.2 Basic MRP Record ... 201

8.3 Input Data and Data Quality Issues ...203

8.4 Capacity Considerations: The Evolution of MRP2 Systems ...206

8.4.1 Rough-Cut Capacity Planning ... 207

8.4.1.1 Example of RCCP ... 207

8.4.2 Capacity Requirement Planning ...208

8.5 Using the MPS for Available to Promise Analysis ...209

8.6 Lot Sizing Considerations ... 211

8.6.1 Example of Mixed LFL and POQ Lot Sizing ... 212

8.7 Uncertainty and Buffering Considerations ... 214

8.8 MRP2 as a Predecessor of the ERP ... 215

8.8.1 Enterprise Resource Planning ... 216

8.9 Summary ... 216

References ... 217

9. Enterprise Resource Planning ... 219

Educational Goals ... 219

9.1 Introduction ...220

9.2 Functionalities and Components of ERP Systems ...223

9.2.1 Production Management ...223

9.2.2 Project Management ... 224

9.2.3 Human Resources ... 224

9.2.4 Materials Management ... 224

9.2.5 Financial Module ...225

9.2.6 Asset Management Module ...225

9.2.7 Plant Maintenance ...226

9.2.8 Quality Management ...226

9.2.9 Sales and Distribution ...226

9.3 The Database and the Model Base ...226

9.3.1 Workflow Management...227

9.4 Business Intelligence ... 231

9.4.1 Data Mining ... 231

9.5 Process Design and Reengineering ... 232

9.6 ERP Implementation Projects ...233

9.6.1 Critical Success Factors in ERP Implementation Projects ...235

9.6.1.1 Listening to the Stakeholders (Do the Right Project) ...235

9.6.1.2 Developing a Good and Agreed on Plan (Do the Project Right) ...235

9.6.1.3 Selecting the Project Manager ...235

9.6.1.4 Risk Management ...235

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xv Contents 9.6.1.5 Process Reengineering ...236 9.6.1.6 Customization ...236 9.6.1.7 User Training ...236 9.6.1.8 Testing ... 237

9.6.1.9 The Role of Industrial Engineers in ERP Projects ... 237 9.7 Summary ... 237 References ...238 10. Human Factor ... 239 Educational Objectives ... 239 10.1 Introduction ... 239

10.1.1 Employee’s Work Environment ... 240

10.1.1.1 Physical Aspect ... 240 10.1.1.2 Functional Aspect ... 240 10.1.1.3 Organizational Aspect ... 240 10.1.1.4 Compensation Aspects ... 240 10.2 History ... 241 10.3 Ergonomics ... 246

10.3.1 Motoric Tasks (Primarily Manual Labor) ... 248

10.3.2 Cognitive Tasks (Primarily Office Work) ... 249

10.4 Motoric Tasks ... 249

10.5 Body Posture ...250

10.6 Access and Space Design ... 252

10.7 Anthropometry ... 252

10.8 Workload Lifting and Exertion in the Workplace ...255

10.9 Workplace Environmental Factors ...256

10.9.1 Noise ... 257

10.9.1.1 Noise Exposure Limits ... 257

10.9.2 Lighting ...258

10.9.3 Temperatures and Humidity ... 259

10.9.4 Ventilation ... 259

10.10 Specialization and the Development of Workers’ Medical Problems ...260

10.11 Design Flexibility ... 262

10.12 Cognitive Tasks ...263

10.12.1 Complex Cognitive Systems: Diagnosis and Decision Making ... 267

10.13 Key Elements in Work Environment Design ... 269

10.13.1 Types of Users ... 271

10.13.2 Nielsen’s Ten Principles for Designing a Convenient System ... 272

10.14 Human Resources Management ... 273

10.14.1 Job Design ... 274

10.14.2 Basic Terms ... 274

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10.14.3 Approaches to Job Design ... 275

10.14.4 Job Design Strategies ...277

10.14.5 Job Evaluation ...280

10.14.6 Introducing a Job Evaluation System into the Organization ...285

10.15 Summary ... 287

References ...288

11. Introduction to Supply Chain Management ... 291

Educational Goals ... 291

11.1 Introduction ... 291

11.2 Background: Terms, Definitions, and Historic Overview ... 293

11.2.1 What Is a Supply Chain? ... 293

11.2.1.1 Intuitive Description of the Term Supply Chain ... 293

11.2.2 Terms and Definitions ... 295

11.2.2.1 Supply Chain ... 295

11.2.2.2 Supply Chain Management ... 296

11.2.3 Historical Development of the Term Supply Chain Management ... 298

11.2.3.1 Vertical Integration ... 298

11.2.3.2 Creation of the Area of Supply Chains ...299

11.2.3.3 Information Integration Era (Present Era) ...299

11.2.3.4 Supply Chain Maturity ...300

11.2.3.5 Globalization Era (Continuing to the Present Day) ... 301

11.2.3.6 Specialization in Core Fields and SCM Outsourcing ... 301

11.2.3.7 SCM in Shared Platforms and Portals...302

11.3 Supply Chain Characteristics ...303

11.3.1 Major Roles of Supply Chain Organizations ...303

11.3.2 Bullwhip Effect ...307

11.3.3 Advantage of Integrated Chain Management: Cost Reduction and Bullwhip Effect Eradication... 311

11.4 Major Characteristics and Considerations in Supply Chain Planning ... 313

11.5 Types of Contracts and Engagements ... 314

11.5.1 Short-Term Engagements ... 315

11.5.2 Long-Term Engagements ... 316

11.5.3 Management of Supply Contracts ... 317

11.6 Information and Its Importance ... 318

11.6.1 Value of Information in Supply Chains ... 318

11.6.2 Information Technology in Supply Chains ... 319

11.6.3 Use of Information ... 320

11.7 Designing the Supply Chain ... 323

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xvii

Contents

11.7.1 Choosing the Participants ... 323

11.7.2 Selection of Information System ... 325

11.7.3 Design Considerations and Tools ... 327

11.8 Supply Chain Monitoring and Control ... 328

11.8.1 Objectives and Constraints ... 328

11.8.2 Long-Term and Short-Term Decisions ... 332

11.8.3 Supply Chain Performance Control and Monitoring ...333

11.9 Summary ...334

References ...335

12. Introduction to Service Engineering ... 337

Educational Goals ... 337

12.1 Introduction ... 337

12.2 Service Processes ... 341

12.2.1 General Characteristics of Service Processes ... 341

12.2.1.1 Extent of Customer Contact ...344

12.2.1.2 Service Pack ...345

12.2.1.3 Customer Experience ...346

12.2.1.4 Response Time Limitation (Availability) ...347

12.2.1.5 Demand Randomness ...348

12.2.1.6 Demand Dynamism ...348

12.2.1.7 Level of Service ...348

12.3 Classification of Service Systems ...350

12.3.1 Major Service Processes Common to Most Types of Service Systems ...350

12.3.2 Classifying Service Processes by Type of Service-Providing Organization and Type of Customer ... 352

12.3.3 Classification of Service Systems by Industrial Sector ... 352

12.4 Key Characteristics and Considerations in Designing Service Systems ...354

12.4.1 In-House Repairs ... 359

12.4.2 Repairs at the Customer’s Home or at a Customer Service Lab ...360

12.4.3 Planning Customer Satisfaction Surveys (or Service Surveys) ...360

12.4.4 Service Arrival Processes ... 361

12.4.5 Arrival Processes That Change over Time ...364

12.5 Introduction to Queuing Systems ...366

12.5.1 Example 1: A Queue at the Bank ... 367

12.5.2 Example 2: Urban Garden Maintenance ... 367

12.5.3 Example 3: Car Interior Cleaning Stations ... 367

12.5.4 Example 4: Self-Service Airline Check-in Kiosks ... 367

12.5.5 Kendall’s Standard Queue Notation ...368

12.6 Main Service Disciplines ... 370

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12.7 Service System Simulation ... 371

12.7.1 What Is Simulation? ... 372

12.7.2 Major Types of Simulation ... 373

12.7.3 Monte Carlo Simulation ... 375

12.7.4 Discrete Event Simulation Programs ... 376

12.7.5 Important Characteristics of Discrete Simulation Programs ... 379

12.8 Customer Patience: Level of Service ...380

12.8.1 Level of Service ...380

12.8.2 Customer Patience ... 382

12.9 General Approach to Planning Number of Service Personnel ...383

12.9.1 Rush Hours and Their Importance ...383

12.9.2 The Term Utilization and Its Connection to Wait Time Expectancy ...384

12.9.3 Additional Methods of Reducing Service Time ...385

12.10 Feedback: Customer Satisfaction Surveys ...386

12.11 Summary ... 389

References ... 390

Index ... 393

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xix

Preface

This book presents the major tasks performed by industrial engineers, and the tools that support these tasks. The focus is on the organizational pro-cesses for which these tasks are needed, and the terminology used to describe the tasks, tools, and processes. The tools discussed here are basic tools that do not require in-depth knowledge of mathematics, statistics, psychology, or sociology. The book also examines the role of the industrial engineer in the production and service sectors. The intention is to help new students under-stand current pathways for professional development, and help them decide in which area to specialize during the advanced stages of their studies.

This book delineates the broad scope of areas in which industrial engineers are engaged, including areas that became part of industrial engineering (IE) in recent decades such as information systems, supply chain management, and service engineering. These fields are becoming an important part of the IE profession, alongside the traditional areas of IE such as operations man-agement, project manman-agement, quality manman-agement, work measurement, and operations research. Industrial engineers require a strong understand-ing and good knowledge in all of these fields in order to perform their tasks.

This book contains the following chapters.

Chapter 1. Introduction

Here we discuss the nature of the IE profession and provide answers to basic questions such as

• What is engineering? • What is IE?

• What is the IE profession?

• How do you acquire this profession? Other points covered in this chapter are

• The system concept and its implementation in manufacturing and service.

• Tools needed by industrial engineers in order to perform their jobs. • Frequently used methods of teaching in this field.

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To give students a historical perspective, we show the development of the profession from its early days until recent years. Today, the profession must take into consideration the intense competition in industry due to globaliza-tion. Elements of competition include

• Cost reduction

• Shortening delivery times—time-based competition • Quality improvement

• Achieving maximum flexibility

These elements of competition are the essence of the challenge facing industrial engineers. They are charged with designing systems and organi-zations that not only survive in the global competitive environment but also succeed.

Chapter 2. Organizations and Organizational Structures

This chapter deals with the organization of people and resources in order to achieve organizational goals. The chapter begins by explaining the need for a well-designed organization of human resources. Classical organizational structures are presented as

• Functional organization • Project organization • Matrix organization

Relative advantages and disadvantages of each of these organizational types are discussed, with an emphasis on communication, responsibility, and authority as tools for achieving a competitive advantage.

The discussion leads to the question of which organizational structure is best for today’s competitive environment and the conclusion is that the organization must be (1) modern, (2) process based, and (3) supported by an appropriate information system. These three conditions are essential for success.

In addition to the organization of human resources, other resources such as production resources must also be efficiently organized. Production resources are mainly machines and equipment such as material handling equipment. The chapter reviews different layouts used to organize these resources:

• Flow shop

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• Job shop

• Cells of group technology-based layout

Advantages and disadvantages of these layouts are discussed, alongside a survey of the fixed location layout where people, material, and equipment are transported to the place of work. This layout is quite common in nonre-petitive environments or projects such as home or ship building.

The relationship between the organizational structure and equipment lay-out leads to a discussion on processes in production and services and how these processes should be organized.

Chapter 3. Project Management

This chapter discusses organizations that perform projects (i.e., nonrepeti-tive undertakings). The discussion opens with a mapping of a project’s stake-holders and understanding their needs and expectations from the project. Needs and expectations are translated into a conceptual design, using spe-cial decision-making tools to choose between technological and operational alternatives. Analysis of the cost/benefit/risk and time is discussed and the appropriate analytical tools are presented. A review of the project life cycle serves as a guideline for displaying methods for scheduling, budgeting, management, and control of projects, with emphasis on the relatively simple methods used in the industry.

The discussion of project management leads to discussion on information and its use—especially, turning data into information that supports decision making.

Chapter 4. Information and Its Uses

This chapter extends the discussion on data and information. It examines data collection, storage, retrieval, and processing, and using appropriate models to create the information necessary to support decision making.

The discussion emphasizes the following topics: • Quality of information

• Data collection methods and how to use raw data to create useful information

• How to forecast future data

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The chapter aims to develop a basic understanding of the nature of infor-mation systems, decision support systems, and database systems. We show the relationship between the knowledge base and models used to analyze data and to support decision-making processes.

Chapter 5. Marketing Considerations

This chapter is the first in a series of two chapters focusing on the interface between the industrial engineer and other professionals within the organi-zation. This chapter deals with the customers, while the following chapter deals with suppliers and subcontractors. We present the tool that links pro-duction to marketing—the Master Propro-duction Schedule—and discuss the relationship between inventory and delivery times. The chapter introduces the classic dilemma between having high levels of inventory (for which a price must be paid) and the resulting shorter delivery times and lower inven-tory levels causing longer lead times. We discuss some policies including

• Make to stock • Make to order • Assemble to order • Design/engineer to order

Chapter 6. Purchasing and Inventory Management

The industrial engineer must understand the organization’s relationship with suppliers and subcontractors. Procurement is important in the competi-tive world, and this chapter discusses some key points of this topic:

• What to buy from suppliers and subcontractors and what to make in house—the make or buy problem.

• If the decision is to buy, how to find suitable suppliers to form a list of candidates.

• How is a supplier chosen from the list of suitable suppliers? • How to manage the relationship with the supplier over time.

When it comes to purchasing materials, inventory management issues are also important such as

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Preface

• How often to order? • What quantity to order?

• What are the costs associated with inventories? • What are the advantages in maintaining inventories?

Resolving these issues is not simple, and there is a need for decision sup-port tools. This chapter presents the basic models and the assumptions underlying each model.

Some purchasing decisions are repetitive, and some are not. How these decisions are made and how to take advantage of procurement and inven-tory to achieve competitive advantage are the main subjects of this chapter.

Chapter 7. Scheduling

This chapter focuses on scheduling the organization’s operations. Scheduling an organization’s operations is dependent both on marketing and the inter-face with customers (Chapter 5) and on procurement and the interinter-face with suppliers (Chapter 6).

Scheduling issues exist in both manufacturing and service systems. Competition drives many scheduling goals and constraints. After setting scheduling goals and constraints, the industrial engineer has to select the right scheduling method.

Our discussion starts with scheduling of the job shop. Next, we discuss the scheduling of the flow shop, and finally we present a general discussion about scheduling, using a concept of the Toyota production system (TPS): Just In Time (JIT), and we also discuss the Theory of Constraints (TOC) that focuses on scheduling bottlenecks.

We explain the logic of simple scheduling methods and provide exam-ples highlighting the effectiveness, advantages, and disadvantages of these methods.

Chapter 8. Material Requirements Planning

This chapter introduces the basic computerized approach for managing production and procurement of material. Material requirements planning (MRP) was developed in the 1970s when the price of computers dropped enough for commercial organizations to be able to buy them. The method

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is based on simple logic and common processing of data from multiple files including

• The bill of material (BOM) file • Inventory files

• The master production schedule (MPS)

Processing these files enables detailed planning and coordination between procurement and manufacturing activities. MRP logic comprises several components such as

• Gross to net • Time phasing • Lot sizing

MRP systems are the basis for planning and management of material in many organizations. It is important that industrial engineers understand, early on in their studies, the logical principles underlying these systems.

The discussion in this chapter reveals the weakness of the first genera-tion MRP systems, which did not include mechanisms for planning produc-tion capacity. Soluproduc-tions to this problem were developed later in the form of rough-cut capacity planning and capacity requirement planning (CRP).

Chapter 9. Enterprise Resource Planning

This chapter presents a framework of the information systems that manage the entire enterprise: enterprise resource planning (ERP) systems.

ERP systems are advanced organizational information systems, and many organizations have implemented them.

Industrial engineers play a major role in implementing these systems. Their tasks include, among others:

• Setting the system requirements • Defining organizational processes

• Choosing the suitable system for the organization • Recruiting participants

• Implementing the ERP system

We explain the principles of ERP systems and discuss their selection and implementation.

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Preface

Chapter 10. The Human Factor and Its Treatment

This chapter presents principles from psychology, sociology, and ergonomics that industrial engineers use in their work.

Industrial engineers must learn how to integrate the human factor as a key component in their analysis and design. Questions concerning motivation, team-building, leadership, and organizational learning are discussed in this chapter, focusing on integrating the human factor in the different systems. In addition, industrial engineers must have knowledge of ergonomics in order to fit the environment and the task to the human operator. The chapter introduces basic issues in ergonomics and human–machine interface that are often used by industrial engineers.

Chapter 11. Supply Chain Management

In this chapter, we explain the need for the management of supply chains. Each organization is a link in the chain receiving goods and/or services from its suppliers and supplying goods and/or services to its customers. The end customers can choose between products produced by alternative supply chains. Thus, a competitive supply chain must act as a coordinated team to reduce costs and provide high quality products in a competitive time and with flexibility.

Characteristics of supply chains and the bullwhip effect are discussed and explained as the basis for understanding the advantage of managing the chain in an integrated manner. In particular, we emphasize the importance of information systems and their integration along the supply chain.

Primary considerations in the design of supply chains are discussed, including the selection of participants in the chain, and the design of inter-faces between participants. Finally, the chapter discusses the necessary information for supply chain design, implementation, monitoring, and con-trol of the chain’s operations.

Chapter 12. Service Engineering

This chapter opens with a review of service processes, and the characteris-tics of service systems and service systems design. Next, we discuss arrival processes and randomness inherent to these processes. The calculation of queue lengths and waiting times in simple systems is discussed and the

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relationship between the level of service and the workforce is explained, including the tradeoff between waiting time cost and service capacity cost.

The chapter presents simulation as a major tool in analyzing service sys-tems, which have inherent uncertainty in their processes. Simulation is an invaluable tool in analyzing the effect of service capacity (e.g., number of servers) on waiting times, queue length, and service level.

We also introduce basic considerations regarding reliability, maintenance, and issue of warranty.

Finally, the chapter ends with a discussion of the important subject of cus-tomer feedback that often needs to be actively explored using various tech-niques including questionnaires.

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xxvii

Authors

Professor Avraham Shtub holds the Stephen and Sharon Seiden chair in project manage-ment at the faculty of Industrial Engineering and Management of the Technion—Israel Institute of Technology. He earned a BSc in electrical engineering from the Technion— Israel Institute of Technology (1974), an MBA from Tel Aviv University (1978), and a PhD in management science and industrial engineer-ing from the University of Washengineer-ington (1982).

Professor Shtub is a certified Project Management Professional (PMP) and a mem-ber of the Project Management Institute (PMI-USA). He is the recipient of the Institute of Industrial Engineering 1995 “Book of the Year Award” for his book Project Management: Engineering, Technology, and Implementation (coauthored with Jonathan Bard and Shlomo Globerson), Prentice-Hall, 1994. He is the recipient of the Production Operations Management Society’s Wick Skinner Teaching Innovation Achievements Award for his book Enterprise Resource Planning (ERP): The Dynamics of Operations Management. His books on project manage-ment have been published in English, Hebrew, Greek, and Chinese.

He is the recipient of the 2008 Project Management Institute Professional Development Product of the Year Award for the training simulator Project Team Builder—PTB.

Professor Shtub was a department editor for IIE Transactions and was on the editorial boards of the Project Management Journal, The International Journal of Project Management, IIE Transactions, and the International Journal of Production Research. He was a faculty member of the Department of Industrial Engineering at Tel Aviv University from 1984 to 1998 where he also served as a chairman of the department (1993–1996). He joined the Technion in 1998 and was the associate dean and head of the MBA program.

He has been a consultant to industry in the areas of project management, training by simulators, and the design of production operation systems. He has been invited to speak at special seminars on project management and opera-tions in Europe, the Far East, North America, South America, and Australia.

Professor Shtub visited and taught at Vanderbilt University, The University of Pennsylvania, Korean Institute of Technology, Bilkent University in Turkey, Otego University in New Zealand, Yale University, Universidad Politécnica de Valencia, and the University of Bergamo in Italy.

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Yuval Cohen is a senior faculty member at the Industrial Engineering Department of the Tel-Aviv Afeka College of Engineering. Previously, he was the head of the Industrial Engineering Program at the Open University of Israel. His areas of expertise are plan-ning and operation of assembly lines, design and management of production and logistic systems, project management, supply chain management, and business decision making. He has published many papers in these areas. Dr. Cohen served several years as a senior operations planner at FedEx Ground (USA) and received several awards for his contri-butions to hub and terminal network planning. Dr. Cohen earned his PhD from the University of Pittsburgh (USA), his MSc from the Technion—Israel Institute of Technology, and BSc from Ben-Gurion University. Dr. Cohen is a fellow of the Institute of Industrial Engineers (IIE), and a full member of the Institute for Operations Research and Management Sciences (INFORMS).

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1

1

Introduction

Educational Goals

This chapter presents the profession of industrial engineering (IE), the broad scope of areas in which industrial engineers are engaged in manufacturing and services, the market in which they operate, and the roles that they play in the economy.

Understanding the historical background is an important component of the training in IE. The following historical review highlights significant events and people that have contributed to the development of the profession.

We explain the need for integrated processes, supported by modern infor-mation systems, with an emphasis on the competitive market today.

1.1 Definitions and Examples Related to Industrial Engineering

1.1.1 Engineering

The Merriam-Webster dictionary defines engineering as the design and creation of large structures such as roads and bridges or new products or systems by using scientific methods.

According to the Merriam-Webster dictionary, “to design” is to plan and make decisions about something that is being built or created—to create the plans, drawings, etc., that show how something will be made.

Engineering design is a process of translation of requirements, specifica-tions, and needs into a language understood by the people responsible for making the new product, service, facility, or system.

For example, the civil engineer translates the requirements for transport-ing a volume of traffic over a water barrier into the design of a bridge, includ-ing the geometry of the bridge, quantities of materials required to construct the bridge, the processing of materials, the layout and assembly of the parts, and finally the testing of the bridge during its construction and after its

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completion. The design is in a language understood by construction work-ers, purchasing agents, suppliwork-ers, subcontractors, quality control experts, and so on.

1.1.2 Industrial Engineering

According to the Merriam-Webster dictionary, IE deals with the design, improvement, and installation of integrated systems (as of people, materials, and energy) in the industry.

Modern IE is concerned with the design, management, and control of operational processes. For that purpose, IE combines classical knowledge in physics, mathematics, computing, and statistics with tools for incorporating the human factor, ergonomics, sociology, and psychology.

For example, in the design of a new business branch, industrial engineers plan the work packages and their allocation to operators. Industrial engi-neers also design the work positions using their knowledge of ergonomics, facility layout planning, and efficient work planning.

1.1.3 Industrial Engineers

Industrial engineers design organizational processes and perform projects and ongoing activities that may involve facilities, products, and systems. The facilities, products, systems, and processes are used to supply products or services. Industrial engineers often focus on processes that take into account the human factor. For designing organizational processes, industrial engi-neers collaborate with managers and their subordinates, and sometimes with peers, such as engineers (e.g., mechanical engineers, electrical engi-neers, software engiengi-neers, etc.).

An industrial engineer is also involved in determining how to best utilize the resources of the organization. Resources such as workers, raw materials, capital, information, buildings, equipment, energy, and technological knowl-edge are used by industrial engineers to perform their tasks. Industrial engi-neers translate the goals of the organization, the constraints imposed, and the uncertainty, to find the best solutions for the organization. They do so by utilizing the rules of physics, mathematics, and statistics along with human factor related knowledge, such as ergonomics and psychology, and the rules of law, morality, and ethics.

A relatively new area of industrial engineering is the design and imple-mentation of information systems that supports processes. In the past, industrial engineers integrated material requirement planning (MRP) sys-tems into industrial organizations. Later on, they played a vital role in the incorporation of enterprise resource planning (ERP) systems in many orga-nizations. Today, many industrial engineers work with ERP systems on a daily basis. With the advent of supply chain management, some industrial engineers entered the challenging world of interorganization data sharing.

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3

Introduction

1.1.4 Production/Service Systems

Some organizations are engaged in the production or supply of products. Other organizations provide services and some do both. These organiza-tions use systems to perform their operaorganiza-tions. We define a system as a col-lection of resources such as people, computers, information, machinery, and facilities working to achieve a common goal. The role of this system is to transform “inputs” such as raw material, energy, and demand information into “outputs,” which are products, information, and customer service. The output may include damaged items, which should be avoided or minimized as much as possible.

1.1.5 What Do Industrial Engineers Do?

Industrial engineers are involved in designing organizational processes, performing projects and ongoing activities, and planning their operations. This includes a large variety of activities. A partial example includes, among others, the following: Design of production and service systems, design and implementation of processes, production management, design of sup-ply chains, planning and managing supsup-ply-chains operations, project man-agement, economics analysis, quality control, and design and operations of information systems.

1.1.6 Tools Used by the Industrial Engineer

To succeed in his or her job, the industrial engineer needs understanding, skills, tools, and techniques in a variety of fields. We will review the skills necessary and demonstrate how these skills are used in the case of a com-pany in the automotive industry.

1.1.6.1 Understanding “Engineering Language”: Drawings, Specifications, etc.

For example, in the production of cars, engineering design passes the detailed drawings of the car to production engineering. An industrial engineer in a production engineering department will translate the design into a bill of material with information regarding the car assemblies, subassemblies, and the parts from which it is composed, determine which machines will be used in order to produce parts, design the supply chain that supplies car parts not manufactured by the factory, etc.

1.1.6.2 Understanding the Physical Processes, Knowledge of the Basic Laws of Physics

Physical processes affect machine operation, maintenance, quality, and efficiency, as well as human performance and the associated ergonomics.

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Dexterity requires a compact comfortable work environment. It also requires lightweight tools and parts that are easy to handle and manipulate.

The manufacturing process of a product is a process that combines a sequence of operations, performed by machines and humans, aimed at transforming raw materials into a finished product. The industrial engineer must understand the process and the physical principles involved in the pro-cess such as metal cutting, forging, etc.

For example, in car assembly lines such as those used by Toyota or General Motors, quality problems are caused by physical processes. Industrial engi-neers should be able to analyze these problems and find effective solutions. Physical factors also affect the load and human posture of the assembly operator. The industrial engineer should be able to identify problems along the assembly line, and use ergonomic principles to design solutions for the problematic workstations.

1.1.6.3 Knowledge of Economics and Financial Management

The industrial engineer’s main role in many organizations is contribution to the bottom line profits. Therefore, operational decision making involv-ing intensive financial considerations is a main specialty of an industrial engineer. Investment decisions, and the effects of interest rate and taxation, are common problems that an industrial engineer should be able to tackle. Such problems appear in a car assembly line when buying a new machine or improved conveyor system. In service industries, these problems may be connected to the number of waiting positions (such as car spaces in a park-ing lot, number of chairs in a dentist waitpark-ing room, etc.).

Industrial engineers have to decide what to produce inhouse and what to buy. For purchased items, they must decide from which country and which supplier to buy in order to minimize cost and maximize quality. The indus-trial engineer must make a decision that combines economic considerations, like the cost of production in each country and the cost of transportation of the various parts between the countries, as well as aspects of taxation and customs that should be considered in the decision process.

1.1.6.4 Understanding Mathematical and Statistical Models

For example, in determining the size of production batches on a machine with long set-up time (the time to switch from one operation to another) compared to the time needed to process a single item, it might be better to produce in large batches to reduce the number of set-ups and, thus, the total machine time required. However, large batches create large and expensive inventories.

To solve this problem, mathematical models trade off the desire to mini-mize set-up times and consequently produce large batches and the desire to minimize inventories by producing small batches “just in time.” When demand is random, that is, uncertain, the problem is harder to solve and the

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5

Introduction

industrial engineer must use statistical tools to determine the size of each batch.

1.1.6.5 Knowledge of Human Resources Management

Since human resources are the center of any organization, and since indus-trial engineers are the designers of organizational processes, they need knowledge of human resource management. Some examples of the areas that they need to understand are task design, workplace design (ergonom-ics), workforce scheduling, determining incentives and remunerations, etc.

For example, the decision to implement an incentive-based payment system and how to apply it is a traditional task of industrial engineers. Understanding the structure and the pros and cons of such systems is important, as different employees performing different tasks in different departments of the same organization may react differently to the same incentive-based payment system. Therefore, proper selection and implemen-tation of such systems is crucial.

1.1.6.6 Knowledge of Computerized Information Systems

Organizations handle and generate vast amounts of data in the course of their operations. Daily data updates are commonplace in areas relating to inventories, orders, quality, production, deliveries, workforce, maintenance, sales, payments, etc. No organization can efficiently operate without this data stored and optimally accessed and organized by a computerized infor-mation system.

Efficient scheduling of resources such as machines and employees and their integration with the timing of material supply requires advanced infor-mation systems that can process huge amounts of data, transforming it into information that supports management decisions.

For example, the final assembly of cars, which consists of thousands of parts manufactured by thousands of operations and supplied by hundreds of suppliers, needs to be scheduled. To schedule such operations efficiently, an enterprise information system is necessary. Industrial engineers define the requirements for these enterprise information systems, and help install, adapt, modify, and integrate such systems for the organization.

1.2 Models

Problem solving and decision making are important parts of the job of the industrial engineer. Textbooks and courses are often organized according to the types of problems. Industrial engineering textbooks have chapters dealing with problems related to inventory, production scheduling, service

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system design, procurement, and the like. One of the primary tools pre-sented to students in all their classes and textbooks, which will become a part of their professional toolkit, is problem modeling.

A model is a simplified presentation of reality. Many real problems are very complex due to their size, the number of different factors to consider, and the dynamic and stochastic nature of interactions between many of these factors. By using simplifying assumptions, one develops a model of the problem. A good model of a real problem must not only be simple enough to understand and analyze but also be sufficiently a representative of the real problem so that, its solution can be implemented successfully on the real problem.

Many models are mathematical ones. Most mathematical programming models define an objective function and a set of constraints. Such models are designed to find the values of the “decision variables” that meet the con-straints, while minimizing or maximizing the objective function.

Conceptual models are also common. An organizational chart, for exam-ple, is a model that conceptually describes the relationships among members in the organization.

When the level of uncertainty is high, statistical or stochastic models that represent the uncertainty of the real problem are used. Such tools include regression analysis and stochastic dynamic programming.

When decision makers analyze a model, they are trying to find a good solution to the problem that the model represents. This solution is appropri-ate for solving the original problem if it is not too sensitive to the simplifying assumptions underlying the model. Therefore, a sensitivity analysis of the solution obtained must be performed to assess its suitability for solving the original problem. The relationship between the original problem, the model, and the solution is shown in Figure 1.1.

1.2.1 Use of Models

Models are frequently used for routine repetitive decisions. A computer can handle some of these decisions automatically. Inventory management in a supermarket is a typical example of routine decisions: Orders for new ship-ments are required when the existing inventory level drops below a certain level. The value of this so-called “reorder level” or “order point” is calculated by fitting a model. Computer software can be set up to continuously monitor and update the level of inventory available based on transactions recorded

Reality (problem) Simplifying Assumptions Model Manipulating Analyzing Optimizing Decision (solution) FIGURE 1.1

Models and their use.

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7

Introduction

at the checkout counters and order automatically from suppliers when the inventory level drops below the reorder level.

Commercial business software packages are designed to support routine decisions. For example, software systems based on the logic of MRP auto-matically issue production and purchasing orders of certain items. These systems also provide data about past events, inventory, etc. Historical data are essential for the development of policies and are used to support the cost estimates of labor and materials, needed for bidding and marketing.

Models can be used to solve nonroutine or ad hoc problems as well. A map is an example of such a model. A tourist can find his or her way in a city he or she never visited before using a map that represents real streets and avail-able attractions. The map has only two dimensions and in reality there are three dimensions, it is much smaller than the real city, and it is static while in the real city people and vehicles are moving. Despite all the simplifying assumptions, following the route from an origin to a destination on the map can help the tourist find his or her way in the real city. In much the same way, industrial engineers use various charts that model various aspects of processes (e.g., flow, quality, etc.).

While a map and a chart are static models, industrial engineers often use dynamic simulation modeling to check different scenarios and support a decision-making process seeking the best scenario. This is discussed next.

1.2.2 Dynamic Aspect: Simulation and Dynamics Systems

Simple models such as a map are static in nature, that is, these models pres-ent a snapshot at a given mompres-ent of the organization and its environmpres-ent. In reality, time plays a very important role in decision making. Values of key parameters change over time. These include various factors in the orga-nization and its environment, which are dynamic. Information is collected over time. Competitors enter the market and develop new products at certain points along the timeline.

Lecturers and practitioners in industrial engineering strive to integrate the dynamic aspect into their models. In the 1960s, the system dynamics approach was developed as a new tool for analyzing the dynamic nature of systems and processes (Forrester, 1961, 1968). Advanced simulation model-ing tools are based on the system dynamics approach.

Forrester modeled systems and processes using two types of entities: Levels and rates. Rates generate changes in the levels, and levels are used as state variables so that the value of the levels at a given time determines the state of the system.

Consider the following example of system dynamics: The fuel system in a car is analyzed to develop the best strategy for refueling the car. The objec-tive is to minimize fuel cost, and the constraints are the capacity of the fuel tank and the location of fueling stations. The rate of the car’s fuel consump-tion is determined by factors such as speed, load, road condiconsump-tions, etc.

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Most drivers (decision makers) base their decision on when to refuel on factors such as the current fuel level, the distance to the next fueling station, and the cost per gallon/liter of fuel at each station. Figure 1.2 shows the rela-tionship between levels and rates in this example.

Another simulation model is discrete event simulation (DES) developed at IBM in 1961 by Geoffrey Gordon and initially called general purpose simu-lation system (GPSS). Since the development of DES, many simusimu-lation lan-guages have been developed and evolved. For example, SIMULA evolved into BETA and its concepts are used in SimPy (Python based DES library). SLAM (simulation language for alternative modeling) evolved into SLAM-II, which developed into SIMAN, and finally into ARENA simulation software. Since the turn of the twenty-first century, many other DES software packages have emerged: Promodel, Simul8, SimEvent, Plant Simulation, and SimCAD Pro—to name a few. Modern simulation languages are user-friendly, power-ful, and flexible. Simulation is considered an important tool that is used by industrial engineers for analyzing complex systems, most of which include random processes.

1.2.3 Simulation Models and Decision Making

When using simulation as a tool for decision support, the simulation model presents three aspects of the real world:

1. The flow of objects such as materials, equipment, and people 2. The flow of information

3. The decision-making process + Fuel level Proximity of gas station Refuel decision Fuel consumption Load Speed Road condition + + – – + + – Current location + Cost per gallon – FIGURE 1.2

Levels and rates flow diagram (+ is positive correlation, − is negative).

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9

Introduction

In the inventory system simulation example, the flow of material deals with materials entering the system, their storage, and exit from the system. Information related to the flow of materials is collected during the simula-tion run. The user can see the exact time when a unit of material is created, and when it moves within the system or leaves it. The data collected during the simulation serve as a basis for understanding and analyzing the inven-tory system.

The logic of decision making is part of the simulation model. Such logic can be based, for example, on a simple model that recommends issuing an order for new materials each time the inventory level drops below the des-ignated order point. In this case, the order level is the decision variable, and the simulation compares system performance for various reorder levels. The parameters of the model’s input and the logic by which it operates are built into the simulation model. The advantage of this approach is that one can try out a large number of different decision rules by running the simulation. One more advantage is the possibility of running large simulations offline, that is, when the decision makers are not present. For example, the model can run at night, and in the morning the users get the results for analysis.

The disadvantage of using simulation for decision making is that in real life many decisions are based on intuition and experience, and it is very dif-ficult (sometimes impossible) to program a computer to model intuition and experience. Furthermore, in many organizations, decisions are made by a group of employees from different fields. Group decision making is a very complex process, and there is not enough knowledge to model it with a rea-sonable degree of precision.

1.3 Teaching Industrial Engineering

IE is taught through lectures, books, and projects; mostly using two approaches:

1. The case study approach: based on the analysis of events/specific situ-ations. Some case studies describe real problems and some describe imaginary situations. Each event presents a particular problem and students discuss the problem, analyze it, and find an appropriate solution.

2. The modeling approach: based on the development of models designed to handle the most important aspects of a problem. Some models are based on mathematical programming tools (e.g., linear program-ming), statistical tools (e.g., regression analysis), search techniques (e.g., genetic algorithms), and simulation. These tools are used to get insight into the model and the problem it represents.

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For example, consider the relationship between the price of a product and the demand for this product. Assuming that there is no randomness, a ematical expression will find the price that will maximize revenue. The math-ematical expression is a simple model that shows the relationship between the price and the resulting demand. Using calculus, it is possible to find the opti-mal price that will maximize revenues. If randomness is considered, a math-ematical expression may enable finding the optimal expected (mean) revenue. Some industrial engineering courses combine the two approaches and present case studies that can be analyzed using the models learned during the course.

1.3.1 Industrial Engineering Curricula

Curricula in IE programs in academic institutions, though not uniform, are based on similar principles.

Freshman (first year) curriculum usually covers all core subjects includ-ing mathematics, physics, and information systems, along with the course “Introduction to Industrial Engineering,” which focuses on the role the industrial engineer fills in organizations, the training he or she needs, and the tools that he or she uses.

Sophomore (second year) curriculum focuses on advanced courses in math-ematics including courses in operations research, probability and statistics, as well as basic courses in psychology, sociology, and process-product design.

Junior (third year) curriculum moves to cover advanced courses on pro-duction and service systems.

Senior (fourth year) curriculum is usually reserved for elective courses. Students select subjects that interest them. In many schools, fourth year stu-dents perform a final project. The final project is based on a real IE problem, which gives students an opportunity to get experience in IE, implement the knowledge they learned in the previous three years, and learn about new tools and techniques and new situations.

1.4 Historical Overview

Humanity has been systematically planning major undertakings for thou-sands of years. The Egyptian pyramids, the two Temples in Jerusalem, ancient Roman roads and structures, the Great Wall in China, and Watt Angkor in Cambodia are examples of huge building projects carried out thousands of years ago. These undertakings required the organization of many people and proper planning. They were probably planned using methods that are very different from the methods used today by industrial engineers. For example, the production of most products in the past was carried out in workshops,

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