Production Planningand Control

Text and CasesThird Edition

S.K. MukhopadhyayFormer Professor

National Institute of Industrial Engineering (NITIE)Mumbai

andFormer Principal

Ramarao Adik Institute of Technology (RAIT)University of Mumbai

Delhi-1100922015

PRODUCTION PLANNING AND CONTROL—Text and Cases, Third EditionS.K. Mukhopadhyay

© 2015 by PHI Learning Private Limited, Delhi. All rights reserved. No part of this book maybe reproduced in any form, by mimeograph or any other means, without permission in writingfrom the publisher.

ISBN-978-81-203-5084-7

The export rights of this book are vested solely with the publisher.

Eighth Printing (Third Edition) . . . . . . . . . April, 2015

Published by Asoke K. Ghosh, PHI Learning Private Limited, Rimjhim House, 111, PatparganjIndustrial Estate, Delhi-110092 and Printed by Mudrak, 30-A, Patparganj, Delhi-110091.

Tomy wife, Madhabi, and

children, Sanghamitra and Aniruddha,for unstinted encouragement and support

Preface xv

Preface to the Second Edition xvii

Preface to the First Edition xix

Acknowledgements xxiii

1. FACILITIES LOCATION AND LAYOUT 1–26

1.1 Introduction 11.2 Plant Location 11.3 Facility Location 1

1.3.1 Single Facility Layout Problem 31.4 Facilities Layout 5

1.4.1 Classification of Layouts 51.4.2 Modular Design Concept 61.4.3 Facilities Layout in Manufacturing 71.4.4 Layout Design Procedures 7

1.5 Computerized Relative Allocation of FacilitiesTechnique (CRAFT) 121.5.1 Features of CRAFT 121.5.2 Major Disadvantages of Using CRAFT 13

1.6 Automated Layout Design Program (ALDEP) 151.7 Computerized Relationship Layout Planning

(CORELAP) 19Summary 23Unsolved Problems 24

2. FORECASTING 27–732.1 Introduction 27

2.1.1 Basic Steps in a Forecasting Task 282.1.2 Categories of Forecasting Techniques 28

2.2 Simple Averaging Method 322.3 Moving Averages 342.4 Double Moving Average 342.5 Exponential Smoothing 38

2.5.1 Single Exponential Smoothing (SES) 38

Contents

v

Contentsvi

2.6 Holt’s Linear Method 412.7 Holt–Winter’s Trend and Seasonality Method 432.8 Forecast Potentials Related to MAPE 452.9 Box–Jenkins Method 45

2.9.1 Time-Series 462.9.2 Sample Autocorrelation 472.9.3 Autoregressive Models (AR) 482.9.4 Moving Average (MA) Models 492.9.5 Back Shift Operator 502.9.6 Mixed AR and MA Models 502.9.7 Model Identification 502.9.8 ARIMA Model 542.9.9 Parameter Estimation 542.9.10 Diagnostic Checking 55

2.10 A Sample Situation 56Unsolved Problems 70

3. AGGREGATE PLANNING 74–993.1 Introduction 743.2 Linear Decision Rules (LDR) 75

3.2.1 The Alternatives for Responding toFluctuation in Orders 75

3.2.2 Time Sequence of Decisions 763.2.3 Costs Involved in Planning Production

and Employment 763.3 Graphical Approach 87

3.3.1 Preparation of Inventory Balance 873.4 Mathematical Programming Model 90Unsolved Problems 95

4. DISAGGREGATION 100–134

4.1 Introduction 1004.2 Disaggregation 1014.3 Master Production Schedule (MPS) 106

4.3.1 Role of Master Production Scheduling 1074.3.2 Inputs to MPS 1084.3.3 Outputs of MPS 1114.3.4 An MPS Approach to Production Strategy 1114.3.5 The Twelve Principles of Master

Scheduling 1154.3.6 MPS Terminology 1164.3.7 Misconception about MPS 1174.3.8 Master Schedule Performance Measures 117

4.4 Bill of Material 1194.4.1 Bill of Material—Types 120

viiContents

4.5 Material Requirements Planning 1234.5.1 Netting 1234.5.2 MRP Terminology 1234.5.3 MRP Outputs 1294.5.4 Nervousness in MRP 131

Unsolved Problems 132

5. CAPACITY MANAGEMENT 135–155

5.1 Introduction 1355.2 Capacity 1355.3 Measuring Capacity 1365.4 Determination of Available Capacity 1365.5 Load 137

5.5.1 Planned Load 1375.5.2 Unplanned Load 138

5.6 Capacity Expansion Strategy 1385.7 Capacity Management 139

5.7.1 Capacity Control 1405.7.2 Capacity Planning 140

5.8 Resource Requirement Planning (RRP) 1415.9 Rough-Cut Capacity Planning (RCCP) 141

5.9.1 Benefits of RCCP 1415.9.2 Pitfalls of RCCP 142

5.10 Capacity Requirement Planning (CRP) 1425.10.1 Inputs to CRP 1435.10.2 CRP Output 146

5.11 Scheduling Strategies 1475.12 Infinite Versus Finite Loading 1475.13 Benefits of CRP 1485.14 Drawbacks of CRP 1485.15 Comparing the Strategies 148Unsolved Problems 154

6. LOT SIZING RULES 156–172

6.1 Introduction 1566.1.1 Fixed Order Quantity (FOQ) 1566.1.2 Economic Order Quantity (EOQ) 1576.1.3 Lot-for-lot (LFL) 1576.1.4 Fixed Period Requirement (FPR) 1576.1.5 Periodic Order Quantity (POQ) 1586.1.6 Least Unit Cost (LUC) 1586.1.7 Least Total Cost (LTC) 1596.1.8 Part-Period Balancing (PPB) 1596.1.9 Wagner–Whitin Algorithm (W–W

Algorithm) 162

Contentsviii

6.2 Analysis of Different Lot Sizing HeuristicMethods 1636.2.1 The Different Methods—An Outline 1636.2.2 Analysis of EOQ 1646.2.3 Analysis of W–W Method 1656.2.4 The Groff (GR) Method 1676.2.5 Silver Meal (SM) Heuristic 1696.2.6 Freeland–Colley Method 1706.2.7 Analysis of the Entire Data Set 172

7. SCHEDULING DECISION RULES 173–219

7.1 Popularity of Scheduling 1737.1.1 Global Competition, Scheduling, and JIT 173

7.2 Broad Scheduling Approaches 1747.3 Kinds of Decisions 1757.4 Types of Manufacturing Scheduling 1767.5 Single Machine Sequencing 1777.6 Shop Floor Control 1797.7 Input-Output Control 1807.8 Infinite and Finite Loading 1817.9 Forward and Backward Scheduling 1817.10 Flow Shop 1817.11 Techniques for Sequencing 182

7.11.1 First Come, First Served 1827.11.2 Earliest Due Date 1827.11.3 Shortest Processing Time 1827.11.4 Last Arrived, First Processed 1827.11.5 Least Slack Time 182

7.12 Critical Ratio 1827.13 Least Changeover Cost 1837.14 Non-quantifiable Sequencing Rules 183

7.14.1 Criteria for Comparing Sequencing Rules 1837.14.2 Performance Measure for the Shop 1857.14.3 Relation between Flow Time and

Inventory 1857.15 Two-machine Scheduling Problem 1937.16 Three-machine Scheduling Problem 1957.17 Job Shop Scheduling 196

7.17.1 The n-Job/m-Machine Flow Shop Problem 1977.18 Job Shop 207

7.18.1 Common Rule for the Job Shop SchedulingProblem 208

7.18.2 Minimizing Make Span in Job Shop 208

ixContents

7.19 Additional Techniques 2117.19.1 Line of Balance Technique 2117.19.2 Run Out Technique 211

7.20 Optimized Production Technology 212Unsolved Problems 215

8. CASES AND EXAMPLES 220–3198.1 Design of Continuous Flow Manufacturing

System 2208.1.1 Introduction 2208.1.2 About the Manufacturer 2218.1.3 Manufacturing Overview 2218.1.4 Literature Review 2228.1.5 Principles of CFM 2238.1.6 Changes in the Organization’s Mindset 2238.1.7 Techniques Used for CFM 2248.1.8 Facilities and Resources 2248.1.9 Materials Handling and Layout 2268.1.10 Production Planning 2268.1.11 Problem Analysis 2268.1.12 New System 2288.1.13 Proposed Production Planning 2328.1.14 Implementation 2328.1.15 Cost-Benefit Analysis 2338.1.16 Conclusions 234

8.2 Multi-Agent Manufacturing Planning and ControlSystem 2358.2.1 Introduction 2358.2.2 Manufacturing Resources Planning

(MRP II) 2368.2.3 Just-In-Time (JIT) 2368.2.4 MRP II and JIT—Comparison 2388.2.5 Multi-Agent Manufacturing have Planning

Environment 2398.2.6 JIT Concepts with Kanban 2398.2.7 Implementing a Multi-Agent System 2418.2.8 Steps in Implementing Multi-Agent

System 2438.2.9 Multi-Agent System as Used for a Two

Wheeler Company 2458.2.10 Model Implementation 2478.2.11 Conclusions 247

Contentsx

8.3 Implementation of Kanban in a Process Plant 2488.3.1 Introduction 2488.3.2 Kanban Implementation Methodology at a

Tyre Manufacturing Plant 2498.3.3 Productive Gain Sharing 2618.3.4 Conclusions 263

8.4 Design and Implementation of an IntegratedProduction Planning System for a PharmaceuticalCompany in India 2648.4.1 Introduction 2648.4.2 The Pharmaceutical Industry in India 2648.4.3 SmithKline Beecham Pharmaceuticals (India)

Limited (SBPI) 2658.4.4 Summary of the Environment 2668.4.5 Conceptual Framework for System Design 2678.4.6 Justification for an Integrated PPC System 2688.4.7 System Analysis and Design 2718.4.8 Appraisal of the Existing PPC System 2748.4.9 Design Philosophy of the Proposed System 2748.4.10 Capacity Assessment 275

8.5 Sinopsys Software Package 2778.5.1 Important Aspects of the Redesigned PPC

System 2788.5.2 Immediate Objectives 2808.5.3 Scope for Further Work 2808.5.4 Lessons for Pharmaceutical Companies in

Emerging Markets 2818.5.5 Conclusions 281

8.6 Design of Forecasting Models Using SAP APO forTractor Industry and Its Measurement of Accuracy 2828.6.1 Introduction 2828.6.2 Objectives of the Study 2828.6.3 Assumptions Made 2838.6.4 Introduction to APO 2838.6.5 APO Requirements for Tractor Industry 2858.6.6 Common Benefits of APO 2868.6.7 General Terminology Used in APO 2878.6.8 APO Forecasting Capabilities 2888.6.9 Forecast Accuracy Metrics in APO 2898.6.10 Forecasting Models Used in this Study 2908.6.11 Forecasting Steps Using APO in this Study 2928.6.12 Types of Forecasting Done for the Tractor

Industry 2938.6.13 Forecasting at Area Office Level 2968.6.14 Forecasting at Company Level 297

xiContents

8.6.15 Forecasting at Indian Tractor IndustryLevel 298

8.6.16 Further Work to be Done 2998.6.17 Conclusions 300

8.7 Multi-product, Multi-stage Lot Sizing 3008.7.1 Introduction 3018.7.2 Definition and Characterization of the

Problem 3028.7.3 Formulation of the Model 3058.7.4 Model Validation 3088.7.5 Model Implementation 3098.7.6 Heuristic Model for Determination of Realistic

Batch Size 3098.7.7 Solution with Heuristic Approach 3158.7.8 Discussion and Conclusion 317

APPENDIX 1 SAMPLE CALCULATION FOR EBQ 317APPENDIX 2 INDICATING FLOW CHARTS FOR SIMULATION

RUN 317

9. QUALITY 320–342

9.1 Definition 3209.2 Quality Characteristics 3209.3 The Three Aspects of Quality 3229.4 Quality Assurance 3239.5 Quality Circles 3239.6 Benefits of Quality Control 3239.7 Quality and Reliability 3249.8 Total Quality System 3249.9 Quality Improvement 3249.10 Management of Quality 3259.11 Statistical Process Control 3259.12 Variation and Process Levels 326

9.12.1 Introduction 3269.12.2 Sources of Variation 3279.12.3 Causes of Variation 3289.12.4 Tools for Identifying Process Variation

Type 3299.13 Statistical Process Control Charts 329

9.13.1 How to Construct a Run Chart (ForDynamic Processes) 330

9.13.2 How to Construct a Control Chart (ForDynamic Processes) 333

APPENDIX 1 338APPENDIX 2 341

Contentsxii

10. ERP WITH SAP R/3 343–358

10.1 Introduction 34310.2 Production Planning (PP) Module of SAP R/3 34410.3 Master Data Needed for PP Module in SAP R/3 345

10.3.1 Bills of Material (BOM) 34510.3.2 Work Center Data 34510.3.3 Routing Data 34510.3.4 Production Resources/Tools (PRT) 346

10.4 Production Planning (PP) Module Components inSAP R/3 34610.4.1 Sales and Operations Planning (SOP) 34610.4.2 Distributed Requirement Planning 34610.4.3 Long-term Planning 34710.4.4 Demand Management 34710.4.5 Material Forecast 34710.4.6 Master Production Scheduling (MPS) 348

10.5 Material Requirements Planning (MRP) 34810.6 Production Orders 34910.7 Capacity Planning in SAP R/3 35010.8 Production by Lot Size 351

10.8.1 Sales and Operation Planning (S&OP) 35210.8.2 Demand Management 35310.8.3 Material Requirements Planning (MRP) 35310.8.4 Creation and Execution of Production Orders 354

10.9 Repetitive Manufacturing 35410.9.1 Planning for Repetitive Manufacturing 355

10.10 Production Planning for Process Industries(PP-PI) 355

10.11 Resources 35610.12 Master Recipe 35610.13 Process Order 35610.14 Process Management 35710.15 Process Data Documentation 35710.16 Integration of the PP Module with the

Other SAP R/3 Modules 357

11. LEAGILE MANUFACTURING—A CONTEMPORARYMANUFACTURING SYNDROME 359–38211.1 Introduction 35911.2 Benefits of Leagility in the Context of Production and

Manufacturing Systems 36211.3 Necessary Information for Leagility in the Context of

Production and Manufacturing Systems 36311.3.1 Tactical Information 36411.3.2 Strategic Information 364

xiiiContents

11.4 Connecting Leagility to Production and ManufacturingSystems 365

11.5 Leagility Drivers 36611.5.1 The Essential Drivers of Leagility 368

11.6 Cells of Leagility 36811.7 Leagility Interaction 36911.8 Supply Chain Performance Measurement and

Indices 37111.9 Comparative Analysis of Leagility Index and

Its Proposed Methodology 37411.10 Theory of Constraint (TOC) and Leagility

Conceptual Framing 37611.10.1 Achieving Leagility Through TOC 377

11.11 Benefits of Achieving Leagility through Theory ofConstraint 382

REFERENCES 383–390

SUGGESTED FURTHER READING 391–394

INDEX 395–399

Production Planning And Control: TextAnd Cases

Publisher : PHI Learning ISBN : 9788120350847 Author : Mukhopadhyay

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