Production Scheduling for
the McGuiness & Co.
Microbrewery
A Production Planning & Control
Framework
Tactical Planning
Demand
Forecasting
Production
Scheduling
Capacity
Planning
Material
Requirements
Planning
Execution
Sales order
Processing
Purchasing
Production
Control
Inventory
records
Shop-floor
data
Collection
Recording
The Production Scheduling Problem
Capacity Company Product Economic
Consts. Policies Charact. Considerations
Placed Orders
Forecasted Demand
Current Inventory Positions
Production
Scheduling
Already Initiated Production
Planning
Horizon
Master Production
Schedule:
When & How Much
to produce for each
product
Time
unit
Capacity
Planning
Problem Specialization for McGuinness
Microbrewery Case Study
• Capacity Constraints: Number and capacity of fermentors
• Company Policies:
– Product cannot be shelved for more than 2 months
– Production in a fermentor can be started at any level of its capacity.
• Product Characteristics:
– Production lead times
• Economic Considerations: (Unnecessary) Inventories should be
minimized (consistent with the Just-In-Time philosophy)
• Planning Horizon: 6-12 months (based on production lead times,
product seasonalities, and product obsolescence)
• Time unit: 1 week (based on the order of production lead times)
Possible Approaches
• Empirical Approach: Spreadsheet-based Simulation
• Analytical Approach: Mathematical (Integer)
Programming formulation
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
Example: Implementing the Empirical
Approach in Excel
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
0
2
0
3
0
2
0%
0
2
0%
0
2
0%
0
Fermentation Time:
0
1
45
200
1
100
255
Fermentation Time:
0
1
35
150
2
2
115
3
Shelf Life:
20
4
0
5
0
6
0
7
0
8
0
9
0
10
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
4
5
6
7
8
9
10
50
40
40
40
40
40
40
40
40
205
165
125
85
45
5
-35
35
-40
40
-40
40
3
2
3
4
5
6
7
8
9
10
40
30
30
40
40
40
40
50
50
75
45
15
-25
25
-40
40
-40
40
-40
40
-50
50
-50
50
Computing Inventory Positions and
Net Requirements
Inventory Position:
IPi = max{IPi-1,0}+ SRi+BNRi -Di
(Material Balance Equation)
(IPi-1)+
SRi+BNRi
i
Di
IPi
Net Requirement:
NRi = abs(min{0, IPi})
Problem Decision Variables:
Scheduled Releases
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
0
2
0
3
0
2
0%
0
2
0%
0
2
0%
0
Fermentation Time:
0
1
45
200
1
100
2
2
255
3
Shelf Life:
20
4
0
5
0
6
1
7
1
8
0
9
0
10
0
2
0%
0
2
0%
0
2
100%
0
2
100%
0
2
0%
0
2
0%
0
2
0%
0
6
7
8
4
5
9
10
50
40
40
40
40
40
40
40
40
205
165
125
85
45
5
165
125
85
200
200
1
1
Fermentation Time:
0
1
35
150
115
3
2
3
4
5
6
1
7
8
9
10
40
30
30
40
40
40
40
50
50
75
45
15
-25
25
-40
40
-40
40
-40
40
-50
50
-50
50
Testing the Schedule Feasibility
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
0
2
1
3
1
2
0%
0
2
100%
0
2
2
Fermentation Time:
0
1
45
200
1
100
255
Shelf Life:
20
4
1
5
0
6
1
2
100%
0
2
100%
0
2
0%
0
3
4
5
8
1
9
1
10
0
2
100%
0
7
2
NO
2
200%
0
2
100%
0
2
100%
0
2
0%
0
6
7
8
9
10
50
40
40
40
40
40
40
40
40
205
165
125
85
45
5
165
125
85
200
200
1
1
Fermentation Time:
0
1
35
150
115
3
2
3
4
5
6
1
7
8
9
10
40
30
30
40
40
40
40
50
50
75
45
15
175
135
95
55
5
155
200
200
1
1
1
1
200
200
1
1
1
1
Fixing the Original Schedule
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
0
2
1
3
1
2
0%
0
2
100%
0
2
2
Fermentation Time:
0
1
45
200
1
100
255
Shelf Life:
20
4
1
5
1
6
1
7
1
8
1
9
1
10
0
2
100%
0
2
100%
0
2
100%
0
2
100%
0
2
100%
0
2
100%
0
2
100%
0
2
0%
0
3
4
5
6
7
8
9
10
50
40
40
40
40
40
40
40
40
205
165
125
85
45
205
165
125
85
200
200
1
1
Fermentation Time:
0
1
35
150
115
3
2
3
4
5
1
6
7
8
9
10
40
30
30
40
40
40
40
50
50
75
45
15
175
135
95
55
5
155
200
200
1
1
1
1
200
200
1
1
1
1
Infeasible Production Requirements
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
1
2
1
3
1
2
100%
0
2
100%
0
2
2
Fermentation Time:
0
1
45
100
55
Shelf Life:
20
4
1
5
0
6
0
7
0
8
0
9
0
10
0
2
100%
0
2
100%
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
2
0%
0
3
4
5
6
7
8
9
10
50
200
1
40
40
40
40
40
40
40
40
205
165
125
85
45
5
-35
35
-40
40
-40
40
1
Fermentation Time:
0
1
35
150
115
3
2
3
4
5
6
7
8
9
10
40
40
40
40
40
40
40
50
50
75
35
-5
5
160
120
80
40
-10
10
-50
50
200
200
1
1
1
1
Modeling the Inventory Spoilage
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
0
2
0
3
0
2
0%
0
2
0%
0
2
0%
0
Fermentation Time:
0
1
45
200
1
100
255
Fermentation Time:
0
1
35
150
2
2
115
3
Shelf Life:
6
4
0
5
0
6
0
7
0
8
0
9
0
10
0
2
0%
0
2
0%
0
2
0%
0
2
0%
45
2
0%
0
2
0%
0
2
0%
0
4
5
6
7
8
9
10
50
40
40
40
40
40
40
40
40
205
165
125
85
45
45
-40
40
-40
40
-40
40
-40
40
3
2
3
4
5
6
7
8
9
10
40
30
30
40
40
40
40
50
50
75
45
15
-25
25
-40
40
-40
40
-40
40
-50
50
-50
50
A feasible schedule with spoilage effects
# Fermentors:
1
Microbrewery Performance
Week
# Fermentors Req'd
Feasible Loading?
Min # Fermentors Req'd
Fermentor Utilization
Total Spoilage
Pale Ale
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
Stout
Week
Demand
Scheduled Receipts
Fermentors Released
Inventory Spoilage
Inventory Position
Net Requirements
Batched Net Receipts
Scheduled Releases
Fermentors Seized
Total Fermentors Occupied
0
Unit Cap:
200
1
1
2
1
3
1
2
100%
0
2
100%
0
2
2
Fermentation Time:
0
1
45
200
1
100
255
Shelf Life:
6
4
1
5
1
6
0
7
1
8
1
9
1
10
0
2
100%
0
2
100%
0
2
100%
0
2
0%
0
2
100%
45
2
100%
0
2
100%
0
2
0%
5
3
4
5
6
7
8
9
10
50
40
40
40
40
40
40
40
40
205
165
125
85
245
45
160
120
80
40
200
200
1
1
Fermentation Time:
0
1
35
150
115
3
2
3
4
1
5
6
7
8
9
10
40
30
30
40
40
40
40
50
50
75
45
215
175
135
95
55
5
5
150
200
200
1
1
1
1
200
200
1
1
1
1
Computing Spoilage and
Modified Inventory Position
Spoilage:
SPi = max{0, IPi-1-(SRi-1+SRi-2+…+SRi-sl+1)
-(BNRi-1+BNRi-2+…+BNRi-sl+1)}
Inventory Position:
IPi = max{IPi-1,0}+ SRi+BNRi -Di-SPi
(Material Balance Equation)
(IPi-1)+
SRi+BNRi
i
Di
SPi
IPi
Advantages and Disadvantages of the
Empirical Approach
• Advantages:
– Easy to present and motivate
– Provides clear visibility to the problems and their underlying
causes
– Supports effective and efficient “what-if” analysis
– Provides modeling flexibility
• Disadvantages
– No guarantee for optimality or exhaustive search for a feasible
solution
– Hard to trace for more complex production environments