Production Planning & Scheduling
in Large Corporations:
Dealing with the Complexities of
Product Variety and Structure
The Major Sources of Complexity
• A large variety of products:
– Example 1: IBM (desktops, laptops, mainframes, special-purpose
computers, etc; furthermore, many models for each of the above
categories)
– Example 2: Ford (sedans, SUV’s minivans, trucks, etc; again,
many models and variations in each category)
The Major Sources of Complexity(cont.)
• Product structure: An assembly of a number of components
and subassemblies
– Example:
• (Desktop) Computer
– Motherboard
» CPU-card
» I/O card
» Modem card
» Power supply unit
» Ventilator
» etc.
– Monitor
– Keyboard
– Mouse
– (other peripherals)
Bill of Materials (BOM)
• Some components and subassemblies are produced inhouse, and some are procured from outside.
A typical (logical) Organization of the
Production Activity
Assembly Line 1: Product Family 1
S1,1
Raw
Material
& Comp.
Inventory
S1,i
S1,2
S1,n
Backend Operations
Dept. 1
S2,1
S2,2
Dept. 2
Dept. j
S2,i
Assembly Line 2: Product Family 2
Finished
Item
Inventory
Dept. k
S2,m
Dealing with the Problem Complexity
through Decomposition
Corporate Strategy
Aggregate Unit
Demand
Aggregate Planning
(Plan. Hor.: 1 year, Time Unit: 1 month)
Capacity and Aggregate Production Plans
End Item (SKU)
Demand
Master Production Scheduling
(Plan. Hor.: a few months, Time Unit: 1 week)
SKU-level Production Plans
Manufacturing
and Procurement
lead times
Materials Requirement Planning
(Plan. Hor.: a few months, Time Unit: 1 week)
Component Production lots and due dates
Part process
plans
Shop floor-level Production Control
(Plan. Hor.: a day or a shift, Time Unit: real-time)
Technology Requirements
• Effective Data Collection and Maintenance/Data Integrity: There is a
need for a monitoring tool that will provide a centralized, correct and
efficient representation of the system status at any point in time.
– Industry Solution: Manufacturing Execution Systems (MES)
• e.g., SAP, Oracle, PeopleSoft
• Efficient and Coherent Computerized Planning Tools: There is a need
for a suite of computationally efficient planning tools that will
effectively address the problems arising at the various levels of the
decomposition framework, while maintaining plan consistency across
the different levels.
– Industry Solution: Product and Supply Chain Planning Software
• e.g., I2 Technologies, BAAN, Manugistics
Aggregate Planning
Product Aggregation Schemes
•Items (or Stock Keeping Units - SKU’s): The final products delivered to the
(downstream) customers
•Families: Group of items that share a common manufacturing setup cost;
i.e., they have similar production requirements.
•Types: Groups of families with production quantities that are determined in a
single aggregate production plan.
•Aggregate Unit: A fictitious item representing an entire product type.
•Aggregate Unit Production Requirements: The amount of (labor) time
required for the production of one aggregate unit. This is computed by
appropriately averaging the labor time requirements over the entire set of
items represented by the aggregate unit.
•Aggregate Unit Demand: The cumulative demand for the entire set of items
represented by the aggregate unit.
Remark: Being the cumulate of a number of independent demand series, the
demand for the aggregate unit is a more robust estimate than its constituent
components.
Computing the Aggregate Unit
Production Requirements
Washing machine
Model Number
A5532
Required labor time
(hrs)
4.2
Item demand as % of
aggregate demand
32
K4242
4.9
21
L9898
5.1
17
3800
5.2
14
M2624
5.4
10
M3880
5.8
06
Aggregate unit labor time = (.32)(4.2)+(.21)(4.9)+(.17)(5.1)+(.14)(5.2)+
(.10)(5.4)+(.06)(5.8) = 4.856 hrs
Aggregate Planning Problem
Aggr. Unit
Production Reqs
Corporate Strategy
Aggregate
Unit Demand
Aggregate
Production Plan
Aggregate
Unit Availability
(Current Inventory
Position)
Aggregate Planning
Aggregate Production Plan:
•Aggregate Production levels
•Aggregate Inventory levels
•Aggregate Backorder levels
Required
Production Capacity
Production Capacity Plan:
•Workforce level(s)
•Overtime level(s)
•Subcontracted Quantities
Pure Aggregate Planning Strategies
1. Demand Chasing: Vary the Workforce Level
PC WC HC FC
D(t)
P(t) = D(t)
W(t)
•D(t): Aggregate demand series
•P(t): Aggregate production levels
•W(t): Required Workforce levels
•Costs Involved:
•PC: Production Costs
•fixed (setup, overhead)
•variable(materials, consumables, etc.)
•WC: Regular labor costs
•HC: Hiring costs: e.g., advertising, interviewing, training
•FC: Firing costs: e.g., compensation, social cost
Pure Aggregate Planning Strategies
2. Varying Production Capacity with Constant Workforce:
PC SC WC OC UC
D(t)
P(t)
S(t)
O(t)
U(t)
W = ct
•S(t): Subcontracted quantities
•O(t): Overtime levels
•U(t): Undertime levels
•Costs involved:
•PC, WC: as before
•SC: subcontracting costs: e.g., purchasing, transport, quality, etc.
•OC: overtime costs: incremental cost of producing one unit in overtime
•(UC: undertime costs: this is hidden in WC)
Pure Aggregate Planning Strategies
3. Accumulating (Seasonal) Inventories:
PC WC IC
D(t)
P(t)
I(t)
W(t), O(t), U(t), S(t) = ct
•I(t): Accumulated Inventory levels
•Costs involved:
•PC, WC: as before
•IC: inventory holding costs: e.g., interest lost, storage space, pilferage,
obsolescence, etc.
Pure Aggregate Planning Strategies
4. Backlogging:
PC WC BC
D(t)
P(t)
B(t)
W(t), O(t), U(t), S(t) = ct
•B(t): Accumulated Backlog levels
•Costs involved:
•PC, WC: as before
•BC: backlog (handling) costs: e.g., expediting costs, penalties, lost sales
(eventually), customer dissatisfaction
Typical Aggregate Planning Strategy
A “mixture” of the previously discussed pure options:
PC WC HC FC OC UC SC IC BC
P
W
H
F
O
U
S
I
B
D
+
Additional constraints arising from the company strategy; e.g.,
•maximal allowed subcontracting
•maximal allowed workforce variation in two consecutive periods
•maximal allowed overtime
•safety stocks
•etc.
Solution Approaches
• Graphical Approaches: Spreadsheet-based simulation
• Analytical Approaches: Mathematical (mainly linear
programming) Programming formulations
Proactive approaches to
demand management
• Influencing demand variation so that it aligns to available
production capacity:
– advertising
– promotional plans
– pricing
(e.g., airline and hotel weekend discounts, telecommunication
companies’ weekend rates)
• “Counter-seasonal” product (and service) mixing: Develop
a product mix with antithetic (seasonal) trends that level
the cumulative required production capacity.
– (e.g., lawn mowers and snow blowers)
Modern Trends in
Aggregate Planning
• To effectively achieve the competitive advantages and economies of
scale required in today’s markets, large corporations must plan and
manage their production activity across the entire supply chain.
• This introduces another spatial/geographical dimension to the
aggregate/capacity planning problem, and extends the initial cost
structure with additional items like transportation and storage/handling
costs.
• The problem get especially complicated for companies with
multinational operations, since these companies must factor into their
planning additional issues like:
–
–
–
–
duties and tariffs and quotas
exchange rates
local corporate tax rates
cultural, language and political issues
Master Production Scheduling
(MPS)
The (Master) Production Scheduling Problem
Capacity Company Product Economic
Consts. Policies Charact. Considerations
Placed Orders
Forecasted Demand
Current Inventory Positions
Master Production
Schedule:
When & How Much
to produce for each
product
MPS
Already Initiated Production
Planning
Horizon
Time
unit
Capacity
Planning
The Driving Logic for the Empirical Approach
Demand
Availability:
•Initial Inventory Position
•Scheduled Receipts
Compute Future
Inventory Positions
Net
Requirements
Future inventories
Lot Sizing
Scheduled
Releases
Resource (Fermentor)
Occupancy
Feasibility
Testing
Product i
Schedule
Infeasibilities
Master Production Schedule
Revise
Prod. Reqs
(Typical) Analytical Approaches to MPS
• Recognizing that switching production from item to item
(or family to family) requires long set-up times, during
which the effective productivity of the line is equal to zero,
these (formal) approaches try to minimize the (long-run)
number of set-ups while meeting the production needs, as
expressed by the aggregate production plan and the current
SKU availability.
• Examples:
– Textbook, pg. 145
– Elsayed & Boucher, “Analysis and Control of Production Systems”
(2nd ed.), Prentice Hall, 1994, pgs 145-159: “Blocked Maximal
Cycle” Heuristic.
Materials Requirements Planning
(MRP)
The “MRP Explosion” Calculus
BOM
Lead
Times
Planned
Order Releases
MPS
Current
Availabilities
Lot Sizing
Policies
MRP
Priority
Planning
Bill Of Materials (BOM)
A formal/systematic representation of the product structure and the
assembly steps required for its synthesis from its components and
subassemblies.
100 units
022
115
(3)
251
(1)
119
(2)
252
(4)
251
(1)
291
(2)
•Subassembly 115: 3x(number of 022)
•Subassembly 119: 2x(number of 022)
•Component 251: 1x(number of 115)
1x(number of 119)
•Component 252: 4x(number of 115)
•Component 291: 2x(number of 119)
3x100
2x100
1x300
1x200
4x300
2x200
300
200
500
1200
400
(Production) Lead Times
The expected time interval between the time that the order for
a new production lot is released, and the time that the lot is available
(to be used in the fabrication of its parent component).
Lead times incorporate:
•set-up times
•processing times
•transfer time
•waiting times
022
1 week
115(3)
2 weeks
251(1)
1 week
119(2)
3 weeks
252(4)
2 weeks
291(2)
1 week
251(1)
1 week
“Time-Phased” Product Structure
[1] 215
(1)
[2]
[2]
[1]
5
252
(4)
291
(2)
[1]
115
(3)
[1]
[3]
119
(2)
251
(1)
4
3
Time in weeks
2
1
022
Example: Time-Phased
Production Requirements
Week
Part
No.
1
2
3
4
5
6
Ord. Rec.
022
115
1 week
100
Ord. Rec.
300
2 weeks
200
3 weeks
300
Ord. Rec.
119
Ord. Rel.
200
Ord. Rec.
200
300
Ord. Rel.
200
Ord. Rec.
252
Ord. Rel.
291
Lead Time
Ord. Rel.
Ord. Rel.
251
7
100
1 week
1200
2 weeks
1200
400
Ord. Rec.
Ord. Rel.
300
400
1 week
Gross Requirements
The cumulative time-phased demand for a certain part, integrating
the part demand generated from the production plans of its parent
items, and also, additional external demand, arising, for instance,
from the need for spare parts, inter-plant shipments, etc.
A
B
C(2)
Item A
Period
……….
Planned Ord. Rel.
Item B
Period
…………
Planned Ord. Rel.
Item C
Period
Gross Requirements
D(1)
1
2
C(1)
3
4
5
6
7
8
9
E(1)
10
11
12
10
11
12
30
1
2
3
4
5
6
7
8
9
30
1
2
3
4
5
Interplant Shipment
6
12
7
10
8
9
90
75
10
11
75
Service order
12
Taking into Account the
Current Item Availability
Item C
Period
Gross Requirements
Scheduled Receipts
Inventory Position: 20
Net Requirements
Planned Sched. Receipts
Planned Sched. Releases
1
2
3
20
20
40
40
4
40
5
6
12
7
10
40
28
18
72
Safety Stock
Requirements
Parent
Sched. Rel.
Item External
Demand
Synthesizing
item demand
series
Gross
Reqs
Projecting Net
Inv. Positions Reqs
and
Net Reqs.
Scheduled
Receipts
Initial
Inventory
8
9
90
18
-72
72
72
10
11
75
0
-75
75
75
12
0
75
Lot Sizing
Policy
Lot Sizing
Lead Time
Planned
Order
Receipts
TimePhasing
Planned
Order
Releases
BOM Levels
•Level 0: End Items (SKU’s)
•Level 1: Items that constitute components (are children) of level-0
item(s) only
•Level 2: Items that are children of level 1, and, potentially, some
level 0 items only
•Level i: Items that are children of level i-1, and, potentially, some
level 0 to i-2 item(s) only
A
B
C
E
D
F
E
C
E
Level 0: A, B
F
G
F
Level 1: D, H
D
E
H
C
E
Level 2: C, G
G
F
Level 3: E, F
The “MRP Explosion” Calculus
External Demand
Level 0
Initial
Inventories
Level 1
Capacity
Planning
Level 2
Scheduled
Receipts
Level N
Gross Requirements
Planned
Order Releases
Capacity Planning (Example)
Available
labor
hours
150
100
50
1
2
3
4
5
6
7
8
Periods
Example: The (complete) MRP Explosion
Calculus
(J. Heizer and B. Render “Operations Management”, 6th Ed. Prentice Hall)
Item BOM:
Alpha
B(1)
D(2)
C(1)
C(2)
E(1)
E(1)
F(1)
F(1)
Item
Alpha
B
C
D
E
F
Gross Reqs for Alpha
Period
Gross Reqs.
Item Levels:
Level 0: Alpha Level 1: B Level 2: C, D Level 3: E, F
Lead Time
1
2
3
1
1
1
6
7
8
9
50
Current Inv. Pos.
10
20
0
100
10
50
10
11 12
50
13
100