Viiiton: THIRD EDITION PRODUCTION AND OPERATIONS MANAGEMENT !IMMMMMMIMM• •••••••• •••• MM. m mom m • ••=••• IP R. Panneerselvam Production and Operations Management Production and Operations Management Third Edition R. PANNEERSELVAM Professor Department of Management Studies School of Management, Pondicherry University Puducherry PHI Learning 1)1- 1!wEgg IdBIQA New Delhi-110001 2012 PRODUCTION AND OPERATIONS MANAGEMENT, Third Edition R. Panneerselvam © 2012 by PHI Learning Private Limited, New Delhi. All rights reserved. No part of this book may be reproduced in any form, by mimeograph or any other means, without permission in writing from the publisher. ISBN-978-81-203-4555-3 The export rights of this book are vested solely with the publisher. Twenty-fourth Printing (Third Edition) February, 2012 Published by Asoke K. Ghosh, PHI Learning Private Limited, M-97, Connaught Circus, New Delhi-110001 and Printed by Rajkamal Electric Press, Plot No. 2, Phase IV, HSIDC, Kundli-131028, Sonepat, Haryana. Contents Preface Preface to the First Edition 1. INTRODUCTION 1-19 1.1 Functional Subsystems of Organizations / 1.1.1 Definition 2 1.2 Systems Concept of Production 4 1.3 Types of Production System 7 1.3.1 Flow Shop 7 1.3.2 Job Shop 8 1.3.3 Batch Manufacturing 8 1.3.4 The Project 8 1.4 Productivity 8 1.5 Strategic Management 10 1.5.1 Corporate Strategies 11 1.5.2 Generic Competitive (or Business Unit) Strategies 13 1.5.3 Functional Strategies 13 1.6 Gross Domestic Product (GDP) and Its Impact 15 1.7 World Class Manufacturing 17 Objective Type Questions 18 Questions 18 2. PRODUCT DESIGN AND ANALYSIS 20-59 2.1 What is Product Design and Analysis 20 2.2 New Product Development—Its Concepts 21 2.2.1 Steps of Product Design 22 2.3 Process Planning and Design 24 2.3.1 Selection of Process 24 2.3.2 Process Selection Decisions 24 2.3.3 Process Planning Design 25 2.3.4 Responsibilities of Process Planning Engineer 26 2.3.5 Steps in Process Planning 27 2.3.6 Case Study 27 2.4 Process Design 30 2.4.1 Process Research 30 2.4.2 Pilot Development 33 Vi I Contents 2.4.3 Capacity Consideration 33 2.4.4 Commercial Plan Transfer 33 2.4.5 Enhanced Capacity Using Optimization 34 2.5 Value Analysis/Value Engineering 34 2.5.1 History of Value Analysis/Value Engineering 34 2.5.2 When to Apply Value Analysis 35 2.5.3 Function 36 2.5.4 Aims 37 2.5.5 Value Engineering Procedure 38 2.5.6 Advantages and Application Areas 40 2.6 Standardization 41 2.6.1 Standardization Procedure 42 2.6.2 Advantages of Standardization 42 2.6.3 Application of Standardization 42 2.7 Simplification 43 2.8 Make or Buy Decision 43 2.8.1 Possible Alternatives while Starting for New Products 43 2.8.2 Criteria for Make or Buy 44 2.8.3 Approaches for Make or Buy Decision 45 2.9 Ergonomic Considerations in Product Design 50 2.10 Concurrent Engineering 50 2.10.1 Tools for Concurrent Engineering 51 2.10.2 HRD in Concurrent Engineering 54 Objective Type Questions 54 Questions 56 CASE STUDY 1: VALUE ANALYSIS—FIRE EXTINGUISHER 58 CASE STUDY 2: BUSINESS PROCESS RE-ENGINEERING 58 3. CAPACITY PLANNING AND INVESTMENT DECISIONS 60-90 3.1 Capacity Planning 60 3.1.1 Determination of Plant Capacity 60 3.1.2 Capacity Planning Strategies 60 3.1.3 Equipment Selection 61 3.2 Investment Decisions 63 3.2.1 Interest Formulas 63 3.2.2 Bases for Comparison of Alternatives 71 Objective Type Questions 84 Questions 85 CASE STUDY 1: CAPACITY PLANNING 89 CASE STUDY 2: INVESTMENT DECISION 89 4. FORECASTING 91-114 4.1 Nature and Use of Forecast 91 4.1.1 Factors Affecting Forecast (Demand) 92 4.1.2 Types of Forecasting in Decision Making 92 4.2 Sources of Data 93 4.3 Demand Patterns 93 4.4 Forecasting Models 95 4.4.1 Selection of a Forecasting Technique 95 4.4.2 Measures of Forecast Accuracy 96 Contents I Vii 4.4.3 Simple Moving Average Method 98 4.4.4 Weighted Moving Average Method 99 4.4.5 Double Moving Average Method 100 4.4.6 Simple (Single) Exponential Smoothing Method 101 4.4.7 Adjusted Exponential Smoothing Method 102 4.4.8 Linear Regression 104 4.4.9 Semi-average Method 107 4.4.10 Delphi Method 108 Objective Type Questions 109 Questions: 111 CASE STUDY: BETA ATM MACHINES (FORECASTING) 114 5. FACILITY LOCATION 115-158 5.1 Introduction 115 5.1.1 Factors Influencing Plant Location 115 5.1.2 Break-even Analysis 116 5.2 Single Facility Location Problem 120 5.3 Multifacility Location Problems 124 5.3.1 Model for Multifacility Location Problem 125 5.3.2 Method of Transformation 125 5.3.3 Model to Determine X-coordinates of New Facilities 126 5.3.4 Model to Determine Y-coordinate 127 5.4 Minimax Location Problem 134 5.5 Gravity Location Problem 137 5.6 Euclidean-distance Location Problem 139 5.7 Covering Problem 144 5.7.1 Introduction 144 5.7.2 Total Covering Problem 145 5.7.3 Multiple Objective Partial Covering Problem 147 5.8 Model for Warehouse Location Problem 148 5.8.1 Problem Definition 149 5.8.2 Descriptive Model 149 5.8.3 Working Mathematical Model 150 Objective Type Questions 151 Questions 153 CASE STUDY: PLANT LOCATION 158 6. PLANT LAYOUT AND MATERIALS HANDLING 159-218 6.1 Introduction 159 6.2 Classification of Layout 159 6.2.1 Advantages and Limitations of Process Layout 161 6.2.2 Advantages and Limitations of Product Layout 161 6.2.3 Advantages and Limitations of Group Technology Layout 161 6.3 Layout Design Procedures 162 6.3.1 Systematic Layout Design Procedure 163 6.3.2 Computerized Relative Allocation of Facilities Technique (CRAFT) 163 6.3.3 CRAFT Procedure 164 6.3.4 Application of CRAFT 165 6.3.5 Automated Layout Design Program (ALDEP) 174 6.3.6 Computerized Relationship Layout Planning (CORELAP) 183 6.3.7 Application of CORELAP 184 Viii I Contents 6.4 Algorithms and Models for Group Technology 191 6.4.1 Rank Order Clustering Algorithm (ROC) 191 6.4.2 Bond Energy Algorithm 196 6.4.3 Mathematical Model for Machine-Component Cell Formation 200 6.5 Materials Handling Systems 205 6.5.1 Unit Load Concept 206 6.5.2 Materials Handling Principles 206 6.5.3 Classification of Materials Handling Equipments 206 Objective Type Questions 207 Questions 210 CASE STUDY: PLANT LAYOUT DESIGN 217 7. LINE BALANCING 219-240 7.1 Concept of Mass Production System 219 7.2 Objective of Assembly Line Balancing 220 7.2.1 Generalized Algorithm 220 7.3 Rank Positional Weight Method 221 7.4 The COMSOAL Algorithm 224 7.5 Model for Assembly Line Balancing 226 7.5.1 Zero-one Programming Model to Minimize the Number of Workstations 227 7.6 Stochastic Assembly Line Balancing 231 7.7 Case Study 231 Objective Type Questions 234 Questions 235 CASE STUDY 1: TURBO-CHARGER (ASSEMBLY LINE BALANCING) 238 CASE STUDY 2: HIGH VOLTAGE FUSE (ASSEMBLY LINE BALANCING) 239 8. LINE OF BALANCE 241-248 8.1 Introduction 241 8.2 Application Areas of LOB 241 8.3 Input to LOB 242 8.4 Steps of LOB 242 Objective Type Questions 247 Questions 235 9. MATERIALS MANAGEMENT AND INVENTORY CONTROL 249-321 9.1 Integrated Materials Management 249 9.2 Components of Integrated Materials Management 249 9.2.1 Materials Planning 250 9.2.2 Inventory Control 250 9.2.3 Purchase Management 250 9.2.4 Stores Management 250 9.3 Inventory Control 251 9.3.1 Inventory Decisions 251 9.3.2 Costs Trade-off 251 9.4 Models of Inventory 252 9.4.1 Purchase Model with Instantaneous Replenishment and without Shortages 252 9.4.2 Manufacturing Model without Shortages 254 9.4.3 Purchase Model with Shortages (Instantaneous Supply) 256 9.4.4 Manufacturing Model with Shortages 258 Contents I iX 9.5 Operation of Inventory System 259 9.6 Quantity Discount 261 9.7 Implementation of Purchase Inventory Model 265 9.7.1 Fixed Order Quantity System (Q System) 265 9.7.2 Periodic Review System (P System) 265 9.8 Purchasing Management 268 9.8.1 Purchase Systems 268 9.8.2 Special Purchase Systems 269 9.8.3 Aspects of Purchase Management 270 9.8.4 Vendor Evaluation 272 9.8.5 Contract 290 9.9 Stores Management 297 9.9.1 Incoming Materials Control 298 9.9.2 Store Accounting 299 9.9.3 Obsolete Surplus and Scrap Management 299 9.9.4 ABC Analysis 300 9.9.5 XYZ Analysis 305 9.9.6 VED Analysis 310 9.9.7 FSN Analysis 312 9.9.8 SDE Analysis 312 Objective Type Questions 313 Questions 316 CASE STUDY: INVENTORY CONTROL 321 10. AGGREGATE PLANNING AND MASTER PRODUCTION SCHEDULING 322-349 10.1 Aggregate Planning 322 10.1.1 Nature of Aggregate Planning Decisions 322 10.1.2 Aggregate Planning Strategies 323 10.1.3 Aggregate Planning Methods 324 10.2 Master Production Plan/Schedule 341 10.2.1 Cut-and-Fit Methods 342 Objective Type Questions 343 Questions 345 CASE STUDY 1: AGGREGATE PLANNING-LAXMI MOTORS LIMITED 348 CASE STUDY 2: AGGREGATE PLANNING-ZIGMA AUTOMOBILE LIMITED 349 11. MATERIAL REQUIREMENTS PLANNING 350-372 11.1 Introduction 350 11.2 Product Structure/Bill of Materials (BOM) 350 11.3 MRP Concept 351 11.3.1 MRP Calculations 353 11.4 Lot Sizing in MRP 355 11.4.1 Illustration to Demonstrate Lot Sizing Methods in MRP 355 11.5 Capacity Requirements Planning 362 11.6 Manufacturing Resource Planning II (MRP II) 363 11.6.1 Implementation Design of MRP II 365 Objective Type Questions 367 Questions 369 CASE STUDY: MATERIAL REQUIREMENTS PLANNING 372 X I Contents 12. PRODUCTION PLANNING AND CONTROL 373-378 12.1 Introduction 373 12.1.1 Strategic Decisions 373 12.1.2 Tactical Decisions 373 12.1.3 Operational Decisions 373 12.2 Scheduling—An Introduction 376 Objective Type Questions 377 Questions 378 13. SINGLE MACHINE SCHEDULING 379-411 13.1 Introduction 379 13.2 Concept of Single Machine Scheduling 379 13.2.1 Measures of Performance 380 13.3 Shortest Processing Time (SPT) Rule to Minimize Mean Flow Time 381 13.4 Weighted Mean Flow Time 382 13.5 Earliest Due Date (EDD) Rule to Minimize Maximum Lateness 383 13.6 Model to Minimize Total Tardiness 384 13.7 Introduction to Branch and Bound Technique to Minimize Mean Tardiness 386 13.7.1 Branch and Bound Algorithm 388 13.8 Simple Heuristic to Minimize Total Tardiness in Single Machine Scheduling Problem 395 13.9 Minimizing the Number of Tardy Jobs 398 13.9.1 Hodgson's Algorithm to Minimize NT 398 13.10 Introduction to Parallel Processors under Single Machine Scheduling 400 13.10.1 Minimizing Makespan 401 13.10.2 McNaughton's Algorithm (to minimize M with m parallel, identical machines) 401 13.10.3 A Heuristic Procedure for Minimizing Makespan (Al) 402 13.10.4 An Integer Programming Formulation 403 13.10.5 Algorithm to Minimize Mean Flow Time with Parallel Identical Machines 403 13.10.6 Heuristic for Scheduling n Jobs on Parallel Identical Processors to Minimize Weighted Mean Flow Time 404 Objective Type Questions 406 Questions 408 CASE STUDY: ALPHA PACKAGING LIMITED 411 14. FLOW SHOP SCHEDULING 412-436 14.1 Introduction 412 14.2 Johnson's Problem 413 14.3 Extension of Johnson's Rule 416 14.4 Branch and Bound Technique 417 14.5 CDS Heuristic 427 14.6 Palmer's Heuristic 430 Objective Type Questions 431 Questions 436 CASE STUDY: LAKSHMI ENGINEERING LIMITED 436