Chapter 13 Aggregate Planning Operations Management - 5th Edition Roberta Russell & Bernard W. Taylor, III Copyright 2006 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Lecture Outline Aggregate Planning Process Strategies for Adjusting Capacity Strategies for Managing Demand Quantitative Techniques for Aggregate Production Planning Hierarchical Nature of Planning Aggregate Planning for Services Copyright 2006 John Wiley & Sons, Inc. 13-2 Aggregate Planning Determine the resource capacity needed to meet demand over an intermediate time horizon Aggregate refers to product lines or families Aggregate planning matches supply and demand Objectives Establish a company wide game plan for allocating resources Develop an economic strategy for meeting demand Copyright 2006 John Wiley & Sons, Inc. 13-3 Aggregate Planning Process Copyright 2006 John Wiley & Sons, Inc. 13-4 Meeting Demand Strategies Adjusting capacity Resources necessary to meet demand are acquired and maintained over the time horizon of the plan Minor variations in demand are handled with overtime or under-time Managing demand Proactive demand management Copyright 2006 John Wiley & Sons, Inc. 13-5 Strategies for Adjusting Capacity Level production Overtime and under-time Producing at a constant rate Increasing or decreasing and using inventory to working hours absorb fluctuations in Subcontracting demand Let outside companies Chase demand complete the work Hiring and firing workers to Part-time workers match demand Hiring part time workers to Peak demand complete the work Maintaining resources for Backordering high-demand levels Providing the service or product at a later time period Copyright 2006 John Wiley & Sons, Inc. 13-6 Level Production Demand Units Production Time Copyright 2006 John Wiley & Sons, Inc. 13-7 Chase Demand Demand Units Production Time Copyright 2006 John Wiley & Sons, Inc. 13-8 Strategies for Managing Demand Shifting demand into other time periods Incentives Sales promotions Advertising campaigns Offering products or services with countercyclical demand patterns Partnering with suppliers to reduce information distortion along the supply chain Copyright 2006 John Wiley & Sons, Inc. 13-9 Quantitative Techniques For APP Pure Strategies Mixed Strategies Linear Programming Transportation Method Other Quantitative Techniques Copyright 2006 John Wiley & Sons, Inc. 13-10 Pure Strategies Example: QUARTER Spring Summer Fall Winter SALES FORECAST (LB) 80,000 50,000 120,000 150,000 Hiring cost = $100 per worker Firing cost = $500 per worker Regular production cost per pound = $2.00 Inventory carrying cost = $0.50 pound per quarter Production per employee = 1,000 pounds per quarter Beginning work force = 100 workers Copyright 2006 John Wiley & Sons, Inc. 13-11 Level Production Strategy Level production (50,000 + 120,000 + 150,000 + 80,000) = 100,000 pounds 4 QUARTER Spring Summer Fall Winter SALES FORECAST 80,000 50,000 120,000 150,000 PRODUCTION PLAN INVENTORY 100,000 100,000 100,000 100,000 400,000 Cost of Level Production Strategy (400,000 X $2.00) + (140,00 X $.50) = $870,000 Copyright 2006 John Wiley & Sons, Inc. 20,000 70,000 50,000 0 140,000 13-12 Chase Demand Strategy QUARTER SALES PRODUCTION FORECAST PLAN Spring Summer Fall Winter 80,000 50,000 120,000 150,000 80,000 50,000 120,000 150,000 WORKERS NEEDED 80 50 120 150 WORKERS WORKERS HIRED FIRED 0 0 70 30 20 30 0 0 100 50 Cost of Chase Demand Strategy (400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000 Copyright 2006 John Wiley & Sons, Inc. 13-13 Mixed Strategy Combination of Level Production and Chase Demand strategies Examples of management policies no more than x% of the workforce can be laid off in one quarter inventory levels cannot exceed x dollars Many industries may simply shut down manufacturing during the low demand season and schedule employee vacations during that time Copyright 2006 John Wiley & Sons, Inc. 13-14 General Linear Programming (LP) Model LP gives an optimal solution, but demand and costs must be linear Let Wt = workforce size for period t Pt =units produced in period t It =units in inventory at the end of period t Ft =number of workers fired for period t Ht = number of workers hired for period t Copyright 2006 John Wiley & Sons, Inc. 13-15 LP MODEL Minimize Z = $100 (H1 + H2 + H3 + H4) + $500 (F1 + F2 + F3 + F4) + $0.50 (I1 + I2 + I3 + I4) Subject to Demand constraints Production constraints Work force constraints P1 - I1 I1 + P2 - I2 I2 + P3 - I3 I3 + P4 - I4 1000 W1 1000 W2 1000 W3 1000 W4 100 + H1 - F1 W1 + H2 - F2 W2 + H3 - F3 W3 + H4 - F4 Copyright 2006 John Wiley & Sons, Inc. = 80,000 = 50,000 = 120,000 = 150,000 = P1 = P2 = P3 = P4 = W1 = W2 = W3 = W4 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 13-16 Transportation Method QUARTER EXPECTED DEMAND REGULAR CAPACITY OVERTIME CAPACITY SUBCONTRACT CAPACITY 1 2 3 4 900 1500 1600 3000 1000 1200 1300 1300 100 150 200 200 500 500 500 500 Regular production cost per unit Overtime production cost per unit Subcontracting cost per unit Inventory holding cost per unit per period Beginning inventory Copyright 2006 John Wiley & Sons, Inc. $20 $25 $28 $3 300 units 13-17 Transportation Tableau PERIOD OF USE PERIOD OF PRODUCTION 1 Beginning 1 2 2 0 Inventory 300 Regular 600 3 — 20 300 6 — 23 100 29 1000 100 34 100 37 500 Subcontract 28 31 34 Subcontract Regular 23 — 26 1200 25 28 150 31 150 28 31 — 1300 Overtime 200 Regular 250 — 23 25 — 28 500 1300 Overtime 200 Subcontract 500 Demand 900 1500 1600 34 20 28 Subcontract 4 — 31 20 300 26 28 1200 Capacity 9 — 25 Regular Unused Capacity 4 Overtime Overtime 3 3 3000 250 500 1300 200 31 500 20 1300 25 200 28 500 250 18 Burruss’ Production Plan REGULAR SUBENDING PERIOD DEMAND PRODUCTION OVERTIME CONTRACT INVENTORY 1 2 3 4 Total 900 1500 1600 3000 7000 1000 1200 1300 1300 4800 Copyright 2006 John Wiley & Sons, Inc. 100 150 200 200 650 0 250 500 500 1250 500 600 1000 0 2100 13-19 Other Quantitative Techniques Linear decision rule (LDR) Search decision rule (SDR) Management coefficients model Copyright 2006 John Wiley & Sons, Inc. 13-20 Hierarchical Nature of Planning Production Planning Capacity Planning Resource Level Product lines or families Aggregate production plan Resource requirements plan Plants Individual products Master production schedule Rough-cut capacity plan Critical work centers Components Material requirements plan Capacity requirements plan All work centers Manufacturing operations Shop floor schedule Input/ output control Individual machines Items Copyright 2006 John Wiley & Sons, Inc. 13-21 Available-to-Promise (ATP) Quantity of items that can be promised to the customer Difference between planned production and customer orders already received AT in period 1 = (On-hand quantity + MPS in period 1) – - (CO until the next period of planned production) ATP in period n = (MPS in period n) – - (CO until the next period of planned production) Copyright 2006 John Wiley & Sons, Inc. 13-22 ATP: Example Copyright 2006 John Wiley & Sons, Inc. 13-23 ATP: Example (cont.) Copyright 2006 John Wiley & Sons, Inc. 13-24 ATP: Example (cont.) Take excess units from April ATP in April = (10+100) – 70 = 40 = 30 ATP in May = 100 – 110 = -10 =0 ATP in June = 100 – 50 = 50 Copyright 2006 John Wiley & Sons, Inc. 13-25 Rule Based ATP Product Request Yes Is the product available at this location? No Availableto-promise Yes Is an alternative product available at this location? No Allocate inventory Yes Is this product available at a different location? No Copyright 2006 John Wiley & Sons, Inc. Is an alternative product available at an alternate location? Yes No Allocate inventory Capable-topromise date Is the customer willing to wait for the product? No Availableto-promise Yes Revise master schedule Trigger production Lose sale 13-26 Aggregate Planning for Services Most services can’t be inventoried Demand for services is difficult to predict Capacity is also difficult to predict Service capacity must be provided at the appropriate place and time 5. Labor is usually the most constraining resource for services 1. 2. 3. 4. Copyright 2006 John Wiley & Sons, Inc. 13-27 Yield Management Copyright 2006 John Wiley & Sons, Inc. 13-28 Yield Management (cont.) Copyright 2006 John Wiley & Sons, Inc. 13-29 Yield Management: Example NO-SHOWS PROBABILITY P(N < X) 0 1 2 3 .15 .25 .30 .30 .00 .15 .40 .70 .517 Optimal probability of no-shows Cu 75 P(n < x) = = .517 Cu + Co 75 + 70 Hotel should be overbooked by two rooms Copyright 2006 John Wiley & Sons, Inc. 13-30 Copyright 2006 John Wiley & Sons, Inc. All rights reserved. Reproduction or translation of this work beyond that permitted in section 117 of the 1976 United States Copyright Act without express permission of the copyright owner is unlawful. Request for further information should be addressed to the Permission Department, John Wiley & Sons, Inc. The purchaser may make back-up copies for his/her own use only and not for distribution or resale. The Publisher assumes no responsibility for errors, omissions, or damages caused by the use of these programs or from the use of the information herein. Copyright 2006 John Wiley & Sons, Inc. 13-31