Operations Management (Aggregate planning and
Master scheduling)
Chapter 10

Agenda – Chapter 20
 Define aggregate planning
 Identify optional strategies for developing an aggregate plan
 Prepare a graphical aggregate plan
 Solve an aggregate plan via the transportation method of linear programming
Operations Management

Aggregate Planning
 Determine the quantity and timing of production for the future
 Objective of Aggregate planning ;
1) Objective is to minimize cost over the planning period by adjusting
2) Production rates
3) Labor levels
4) Inventory levels
5) Overtime work
6) Subcontracting rates
7) Other controllable variables
Operations Management p. 3

Aggregate Planning
 Required for aggregate planning
1) A logical overall unit for measuring sales and output.
2) A forecast of demand for an intermediate planning period in these aggregate terms
3) A method for determining costs
4) A model that combines forecasts and costs so that scheduling decisions can be made for the planning period
Operations Management p. 4

The Planning Process
Operations Management p. 5

Aggregate Planning
 Combines appropriate resources into general terms
 Part of a larger production planning system
 Disaggregation breaks the plan down into greater detail
 Disaggregation results in a master schedule
Operations Management p. 6

Aggregate Planning
Operations Management

Concept of Aggregate Planning
Pic : Aggregate planning sequence
Operations Management

Aggregate Planning Inputs
 Resources
Workforce/production rate
Facilities and equipment
 Demand forecast
 Policies
Subcontracting
Overtime
Inventory levels
Back orders
 Costs
Inventory carrying
Back orders
Hiring/firing
Overtime
Inventory changes
subcontracting
Operations Management p. 9

Aggregate Planning Outputs
 Total cost of a plan
 Projected levels of:
Inventory
Output
Employment
Subcontracting
Backordering
Operations Management p. 10

Aggregate Planning Strategies
 Proactive
- Involve demand options: Attempt to alter demand to match capacity
 Reactive
- Involve capacity options: Attempt to alter capacity to match demand
 Mixed
- Some of each
Operations Management p. 11

Demand Options
Pricing
Promotion
Back orders
New demand
Operations Management p. 12

Aggregate Planning Strategies (Pricing)
 Pricing differential are commonly used to shift demand from peak periods to off-peak periods, for example:
Eg.
1.
Some hotels offer lower rates for weekend stays
2.
Some airlines offer lower fares for night travel
3.
Movie theaters offer reduced rates for matinees
4.
Some restaurant offer early special menus to shift some of the heavier dinner demand to an earlier time that traditionally has less traffic.
 To the extent that pricing is effective, demand will be shifted so that it correspond more closely to capacity.
 An important factor to consider is the degree of price elasticity of demand; the more the elasticity, the more effective pricing will be in influencing demand patterns p. 13
Operations Management

Aggregate Planning Strategies (Promotion)
 Advertising and any other forms of promotion, such as displays and direct marketing, can sometimes be very effective in shifting demand so that it conforms more closely to capacity.
 Timing of promotion and knowledge of response rates and response patterns will be needed to achieve the desired result.
 There is a risk that promotion can worsen the condition it was intended to improve, by bringing in demand at the wrong time. p. 14
Operations Management

Aggregate Planning Strategies (Back-Order)
 An organization can shift demand to other periods by allowing back orders. That is , orders are taken in one period and deliveries promised for a later period.
 The success of this approach depends on how willing the customers are to wait for delivery.
 The cost associated with back orders can be difficult to pin down since it would include lost sales, annoyed or disappointed customers, and perhaps additional paperwork. p. 15
Operations Management

Aggregate Planning Strategies (New Demand)
 Manufacturing firms that experience seasonal demand are sometimes able to develop a demand for a complementary product that makes use of the same production process. For example, the firms that produce water ski in the summer, produce snow ski in the winter. p. 16
Operations Management

Capacity Options
 Hire and layoff workers
 Overtime/slack time
 Part-time workers
 Inventories
 Subcontracting (in- out)
Operations Management p. 17

Aggregate Planning Strategies for meeting uneven demand
 Maintain a level workforce
 Maintain a steady output rate
 Match demand period by period
 Use a combination of decision variables
Operations Management p. 18

A general procedure for Aggregate Planning
1.
Determine demand for each period
2.
Determine capacities (regular time, over time, and subcontracting) for each period
3.
Identify policies that are pertinent
4.
Determine units costs for regular time, overtime, subcontracting, holding inventories, back orders, layoffs, and other relevant costs
5.
Develop alternative plans and compute the costs for each
6.
Select the best plan that satisfies objectives. Otherwise return to step 5. p. 19
Operations Management

Cumulative Graph
Surplus output
Demand exceeds output
Period p. 20
Operations Management

Mathematical Techniques
 Linear programming: Methods for obtaining optimal solutions to problems involving allocation of scarce resources in terms of cost minimization.
 Linear decision rule: Optimizing technique that seeks to minimize combined costs, using a set of cost-approximating functions to obtain a single quadratic equation.
 Simulation models: Developing a computerized models that can be tested under a variety of conditions in an attempt to identify reasonably acceptable (although not always optimal) solutions to problem. p. 21
Operations Management

Mathematical Techniques (Linear programming)
 Linear programming models are methods for obtaining optimal solutions to problems involving the allocation of scarce resources in terms of cost minimization or profit maximization.
 With aggregate planning, the goal is usually to minimize the sum of costs related to regular labor time, overtime, subcontracting, carrying inventory, and cost associated with changing the size of the workforce. Constraints involve the capacities of the workforce, inventories, and subcontracting.
 The aggregate planning problem can be formulated as a transportation problem (special case of linear programming). p. 22
Operations Management

Aggregate planning notation
Operations Management p. 23

Transportation notation for aggregate planning
Operations Management p. 24

Transportation notation for aggregate planning (Note)
 Regular cost, overtime cost, and subcontracting cost are at their lowest level when output is consumed in the same period it is produced.
 If goods are made available in one period but carried over to later period, holding costs are incurred at the rate of (h) per period.
 With back orders, the unit cost increases as you move across a row from right to left, beginning at the intersection of a row and column for the same period.
 Beginning inventory is given a unit cost of 0 if it is used to satisfy demand in period 1. however, if it is held over for use in later periods, a holding cost of h per unit is added for each period. p. 25
Operations Management

Transportation notation for aggregate planning (Example)
 Given the following information set up the problem in a transportation table and solve for the minimum cost plan. p. 26
Operations Management

Transportation notation for aggregate planning (Solution)
 The transportation table and solution are shown in the next slide.
Some entries require additional explanation:
 Inventory carrying cost, h = $1 per unit per period. Hence, units produced in one period and carried over to a later period will incur a holding cost that is a linear function of the length of time held.
 Linear programming models of this type require that supply
(capacity) and demand be equal. A dummy column has been added
(nonexistent capacity) to satisfy that requirement. Since it does not
“cost” anything extra to not use capacity in this case, cell costs of
$0 have been assigned.
 No backlogs were needed in this example
 The quantities (e.g., 100, 450 in column 1) are the amounts of output or inventory that will be used to meet demand requirements.
Thus, the demand of 550 units in period 1 will be met using 100 units from inventory and 450 obtained from regular time output. p. 27
Operations Management

Period Beginning inventory
1
100
1
0
2
1
3
2
Regular
Overtime subcontract
450 60
50
61 62
80 50 81 82
90 30 91 92
2
3
Regular
Overtime subcontract
Regular
Overtime subcontract demand
63 500 60 61
83 50 80 81
93 20 90 100 91
66 63
500
60
86 83 50 80
96 93 100 90
550 700 750
Operations Management capacity
0 100
90
90
0 500
0 50
0 120
0 500
0 50
0 120
0 500
0 50
0 100
2090 p. 28

Trial and error techniques
 Trial and error approaches consist of developing simple tables or graphs that enable planners to visually compare projected demand requirements with existing capacity.
 Different plans are conducted and evaluated in terms of their overall costs. The one with the minimum cost will be chosen.
 The disadvantage of such techniques is that they do not necessarily result in the optimal aggregate plan. p. 29
Operations Management

Trial and error techniques (Assumption)
1. The regular output capacity is the same in all periods.
2. Cost ( back order, inventory, subcontracting, etc) is a linear function composed of unit cost and number of units.
3. Plans are feasible; that is, sufficient inventory capacity exists to accommodate a plan, subcontractors with appropriate quality and capacity are standing by, and changes in output can be made as needed.
4. All costs associated with a decision option can be represented by a lump sum or by unit costs that are independent of the quantity involved
5. Cost figures can be reasonably estimated and are constant for the planning horizon.
6. Inventories are built up and drawn down at a uniform rate and output occurs at a uniform rate throughout each period. p. 30
Operations Management

Trial and error techniques (Some important relationships) p. 31
Operations Management

Trial and error techniques (Cost calculation)
Operations Management p. 32

Trial and error techniques (Example1)
Operations Management p. 33

Trial and error techniques (Solution1)
Operations Management p. 34

Trial and error techniques (Example 2)
 After reviewing the plan developed in the preceding example, planners have decided to develop an alternative plan. They have learned that one is about to retire from the company. Rather than replace that person, they would like to stay with the smaller workforce and use overtime to make up for lost output. The reduced regular time output is 280 units per period. The maximum amount of overtime output per period is 40 units. Develop a plan and compare it to the previous one. p. 35
Operations Management

Trial and error techniques (Solution2)
Operations Management p. 36

Aggregate Planning in Services
 Aggregate planning for services takes into account projected customer demands, equipment, capacities, and labor capabilities.
The resulting plan is a time-phased projection of service staff requirements.
 Aggregate planning for manufacturing and aggregate planning for services share similarities in some respect, but there are some important differences which are:
Services occur when they are rendered
Demand for service can be difficult to predict
Capacity availability can be difficult to predict
Labor flexibility can be an advantage in services p. 37
Operations Management

Disaggregating the aggregate plan
 For the production plan to be translated into meaningful terms of production, it is necessary to disaggregate the aggregate plan.
 This means breaking down the aggregate plan into specific product requirements in order to determine labor requirements (skills, size of workforce), materials, and inventory requirements.
 To put the aggregate production plan into operation, one must convert, or decompose, those aggregate units into units of actual product or services that are to be produced or offered.
 For example, televisions manufacturer may have an aggregate plan that calls for 200 television in January, 300 in February, and 400 in
March. This company produce 21, 26, and 29 inch TVs, therefore the
200, 300, and 400 aggregate TVs that are to be produced during those three months must be translated into specific numbers of TVs of each type prior to actually purchasing the appropriate materials and parts, scheduling operations, and planning inventory requirements.
Operations Management p. 38

Master scheduling
 The result of disaggregating the aggregate plan is a master schedule showing the quantity and timing of specific end items for a scheduled horizon, which often covers about six to eight weeks ahead.
 The master schedule shows the planned output for individual products rather than an entire product group, along with the timing of production.
 It should be noted that whereas the aggregate plan covers an interval of, say, 12 months, the master schedule covers only a portion of this. In other words, the aggregate plan is disaggregated in stages , or phases, that may cover a few weeks to two or three months.
 The master schedule contains important information for marketing as well as for production. It reveals when orders are scheduled for production and when completed orders are to be shipped. p. 39
Operations Management

Master Scheduling
Operations Management p. 40

Master Scheduling
 Determines quantities needed to meet demand
 Interfaces with
Marketing: it enables marketing to make valid delivery commitments to warehouse and final customers.
Capacity planning: it enables production to evaluate capacity requirements
Production planning
Distribution planning
Operations Management
Pic : Master Scheduling Process p. 41

Master Scheduling Process
 Master production schedule (MPS): indicates the quantity and timing of planned production, taking into account desired delivery quantity and timing as well as on-hand inventory. The MPS is one of the primary outputs of the master scheduling process.
 Rough-cut capacity Planning (RCCP): it involves testing the feasibility of a proposed master relative to available capacities, to assure that no obvious capacity constraints exist. This means checking capacities of production warehouse facilities, labor, and vendors to ensure that no gross deficiencies exist that will render the master schedule unworkable p. 42
Operations Management

Master Scheduling (Example)
 A company that makes industrial pumps wants to prepare a master production schedule for June and July. Marketing has forecasted demand of 120 pumps for June and 160 pumps for July. These have been evenly distributed over the four weeks in each month: 30 per week in June and 40 per week in July.
 Now suppose that there are currently 64 pumps in inventory (i.e., beginning inventory is 64 pumps), and that there are customer orders that have been committed for the first five weeks (booked) and must be filled which are 33, 20, 10, 4, and 2 respectively. The following figure (see next slide) shows the three primary inputs to the master scheduling process: beginning inventory, the forecast, and the customer orders that have been committed. This information is necessary to determine three quantities: the projected on-hand inventory, the master production schedule (MPS) and the uncommitted (ATP) inventory. Suppose a production lot size of 70 pumps is used. p. 43
Operations Management

Master Scheduling (Solution)
Operations Management p. 44

Master Scheduling (Solution)
Operations Management p. 45

Master Scheduling (Solution)
Operations Management p. 46

Master Scheduling (Note)
 The requirements equals the maximum of the forecast and the customer orders
 The net inventory before MPS equals the inventory from previous week minus the requirements.
 The MPS = run size, will be added when the net inventory before
MPS is negative ( weeks 3, 5, 7, and 8).
 The projected inventory equals the net inventory before MPS plus the MPS (70). p. 47
Operations Management

Master Scheduling (Solution)
 The amount of inventory that is uncommitted, and, hence, available to promise is calculated as follows:
 Sum booked customer orders week by week until (but not including) a week in which there is an MPS amount. For example, in the first week, this procedure results in summing customer orders of 33
(week 1) and 20 (week 2) to obtain 53. in the first week, this amount is subtracted from the beginning inventory of 64 pumps plus the
MPS (zero in this case) to obtain the amount that is available to promise [(64 + 0 – (33 + 20)] = 11 p. 48
Operations Management