Material Requirements Planning (MRP)
Unlike many other approaches and techniques, material
requirements planning “works” which is its best recommendation.
— Joseph Orlicky, 1974
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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1
History
• Begun around 1960 as computerized approach to purchasing and
production scheduling.
• Joseph Orlicky, Oliver Wight, and others.
• Prior to MRP, production of every part and end item was triggered by the
inventory falling below a given level (reorder point).
• APICS launched “MRP Crusade” in 1972 to promote MRP.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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1
Key Insight
• Independent Demand — finished products
• Dependent Demand — components
It makes no sense to independently forecast dependent demands.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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3
Assumptions
1. Known deterministic demands.
2. Fixed, known production leadtimes.
3. In actual practice, lead times are related to the level of WIP.
Flow Time = WIP / Throughput Rate (Little’s Law)
Idea is to “back out” demand for components by using leadtimes and bills of
material.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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2
Capacity Requirements Planning
100
Capacity
(Hours or
Units)
1
2
3
4
5
6
Who in the organization actually does this?
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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MRP Procedure
1. Netting: net requirements against projected inventory
--Gross Requirements over time (e.g., weekly buckets)
--Scheduled Receipts and current inventory
--Net Requirements
2. Lot Sizing: planned order quantities
3. Time Phasing: planned orders backed out by leadtime
4. BOM Explosion: gross requirements for components
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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3
Inputs
• Master Production Schedule (MPS): due dates and quantities for all top
level items
Due dates assigned to orders into time buckets (week, day, hour, etc.)
• Bills of Material (BOM): for all parent items
• Inventory Status: (on hand plus scheduled receipts) for all items
• Planned Leadtimes: for all items
Components of leadtime
Move
Setup
Process time
Queue time (80-90% total time)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
7
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Example - Stool
Indented BOM
Stool
Base (1)
Legs (4)
Bolts (2)
Seat (1)
Bolts (2)
Graphical BOM
Base (1)
Legs (4)
Stool
Level 0
Seat (1)
Level 1
Bolts (4)
Bolts (2) Level 2
Note: bolts are treated at lowest level
in which they occur for MRP calcs.
Actually, they might be left off BOM
8
altogether in practice.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Example
Item: Stool (Leadtime = 1 week)
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
0
1
2
3
4
5
120
6
20
20
20
20
20
-100
100
-100
100
Item: Base (Leadtime = 1 week)
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
0
1
2
3
4
100
5
6
0
0
0
0
-100
100
-100
-100
100
9
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© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Example (cont.)
BOM explosion
Item: Legs (Leadtime = 2 weeks)
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
0
1
2
0
0
200
0
3
400
4
5
6
-200
200
-200
-200
-200
200
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Terminology
Level Code: lowest level on any BOM on which part is found
Planning Horizon: should be longer than longest cumulative leadtime for any
product
Time Bucket: units planning horizon is divided into
Lot-for-Lot: batch sizes equal demands (other lot sizing techniques, e.g., EOQ or
Wagner-Whitin can be used)
Pegging: identify gross requirements with next level in BOM (single pegging) or
customer order (full pegging) that generated it. Single usually used because
full is difficult due to lot-sizing, yield loss, safety stocks, etc.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
11
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Pegging and Bottom up Planning
Table 3.7 MRP Calculations for Part 300
Part 300
1 2
Required from B
30
90
60
125
Scheduled Receipts
100
Adjusted Scheduled Receipts
100
Projected on-hand
50
4
35
Required from 100
Gross Requirements
3
50 25
90
6
7
8
15
15
25 -65
65
65
Net Requirements
5
15
15
Planed order receipts
65
15
Planed order releases
On-hand = 40
Scheduled releases = none Lot-for-lot LT = 1 week
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Bottom Up Planning
Reference Figure 3.7
Assume that the scheduled receipt for week 2 for 100 units is not
coming in!
Have 50 units of inventory, with requirements of 125.
Implications
I can fill 50 units of demand from part 100 or 50 units from part
B.
If I go with part 100, that will allow me to fill some of the demand
of part A (100 needed for part A). Can I ship 50 units to the
customer now and 50 units later? What if I cover the demand of
part B? Correct choice depends on the customers involved.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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More Terminology
Firm Planned Orders (FPO’s): planned order that the MRP system does not
automatically change when conditions change --- can stabilize system
Service Parts: parts used in service and maintenance --- must be included in gross
requirements
Order Launching: process of releasing orders to shop or vendors --- may include
inflation factor to compensate for shrinkage
Exception Codes: codes to identify possible data inaccuracy (e.g., dates beyond
planning horizon, exceptionally large or small order quantities, invalid part
numbers, etc.) or system diagnostics (e.g., orders open past due, component
delays, etc.)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Conceptual Changes in Lotsizing Approaches
Before, EOQ represented a basic trade-off between inventory costs
and setup costs.
Goldratt: If I am not at capacity on an operation requiring a setup,
the time spent on a setup is a mirage.
Make setups occur as frequently as possible (smaller lot sizes) as long
as capacity is available
Produce only when inventory level reaches zero (Wagner Whitin) is
not optimal when capacity is a constraint
Authors know of no commercial MRP system that uses WW.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Important Questions About “Optimal” Lot-sizing
Setup costs
Very difficult to estimate in manufacturing systems
-May depend on schedule sequence
-True costs depends on capacity situation
Assumption of deterministic demand and deterministic production
-production schedules are always changing because of dynamic
conditions in the factory.
Assumption of independent products that do not use common
resources. Very seldom will see common resources not used.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Important Questions About “Optimal” Lot-sizing
WW leads us to the conclusion that we should produce either
nothing in a period or the demand of an integer num ber of
future periods.
-generates a production schedule that is very “lumpy.”
There are reasons for generating a level loaded production
schedule, one in which the same amount of products are
produced in every time period.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Problem Formulation
t= A time period, t = 1 to T, where T is the planning horizon.
Dt = Demand in time period t (in units).
Ct = Unit production costs ($/unit), excluding setup or inventory cost in
period t.
At = Setup (order) cost to produce (purchase) a lot in period t ($).
Ht = Holding costs to carry a unit of inventory from period t to
period t+1 ($/unit). e.g., if holding costs consists entirely of interest on
money tied up in inventory, where i is the annual interest rate and
periods correspond to weeks, then
h=
I * Ct
52
It =Inventory (units) left over at the end of period t.
Qt =The lot size (units) in period t; this is the decision variable
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Problem Objective
Satisfy all demands at minimum cost (production, setup, and holding
costs)
All the demands must be filled, only the timing of production is open to
choice.
If the unit production cost does not vary with t, then production cost
will be the same regardless of timing and can be dropped from
consideration.
Look at an example: assume setup costs, production costs, and holding
costs are all constant over time. Thus, need only to consider setup
costs and holding costs.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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19
Lot Sizing in MRP
• Lot-for-lot — “chase” demand
• Fixed order quantity method — constant lot sizes
• EOQ — using average demand
• Fixed order period method — use constant lot intervals
• Part period balancing — try to make setup/ordering cost equal to holding
cost
• Wagner-Whitin — “optimal” method
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Data For An Example Problem
Table 2.1
t
1
Dt
20 50 10 50 50 10 20 40 20 30
2
3
4
5
6 7
8
9 10
ct 10 10 10 10 10 10 10 10 10 10
At 100 100 100 100 100 100 100 100 100 100
ht
1
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
1
1
1
1
1
1
1
1
1
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Lot-for-lot
Simply produce in period t the net requirements for period t.
Minimizes inventory carrying costs and maxim izes total setup
costs.
It is simple and it is consistent with just in time.
Tends to generate a more smooth production schedule.
In situations where setup costs are minim al (assembly lines), it
is probably the best policy to use.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Lot Sizing Example
t
Dt
1
20
2
50
3
10
4
50
5
50
6
10
7
20
8
40
9
20
10
30
LL
20
50
10
50
50
10
20
40
20
30
A = 100
h =1
300
D=
= 30
10
Lot-for-Lot: $1000
No carrying cost, ten setups @$100 each
23
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© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Lot Sizing Example (cont.)
EOQ:
Q=
2 AD
=
h
2 x100 x 30
= 77
1
t
1
2
3
4
5
6
Dt
20 50 10 50 50 10
Qt
77
77
77
Setup
100
100
100
Holding
57 7 74 24 51
Total
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
7
20
Note: EOQ is a
special case of
fixed order quantity.
8
9
40 20
77
100
41 21 58
http://factory-physics.com
10
30
38
Total
300
308
$400
$371
$771
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Fixed Order Period From EOQ
Calculate EOQ using formula presented earlier.
Then Fixed Order Period, P = Q/D
Calculating P in this manner has all the limitations noted
earlier in Chapter .
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
25
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Fixed Order Period
Example--Further Comments
Example
Period
1
2
3
4
5
6
7 8
9
Net Requirements
15 45
25 15 20 15
Planned Order Recpts
60
60
15
Let P = 3. Skip first period, no demand. Sixty units covers demand
for periods 2, 3, and 4. Period 5 is skipped because there is no
demand. Sixty units covers demand in periods 6, 7, 8. Fifteen units
covers demand in period 9, which is the last period in the planning
Horizon.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Part-Period Balancing
Combines the assumptions of WW with the mechanics of the EOQ.
One of the assumptions of the EOQ is that it sets the average setup
costs equal to the average inventory carrying costs.
Part-period. The number of parts in a lot times the number of
periods they are carried in inventory.
Part-period balancing tries to make the setup costs as close to the
carrying costs as possible.
27
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© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
Part-Period Balancing Example (Cont.)
Period
1 2
Net Requirements
3
4
5 6
15 45
7
8 9
25 15 20 15
Planned Order Receipts
Quantity
Period 6
Setup Costs
25
$150
40
$150
60
75
Part-periods
Inventory
Carrying Costs
0
$0
15 x 1 = 15
$30
$150
15 + 20 x 2 = 55
$110
$150
55 + 15 x 3 = 100
$200
Fixed order quantity method (without modifications) tends to
work better than WW when dealing with multi-level production
systems with capacity limitations.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Nervousness
Item A (Leadtime = 2 weeks, Order Interval = 5 weeks)
Week
0
1
2
3
4
5
6
7
Gross Reqs
2
24
3
5
1
3
4
Sched Receipts
Proj Inventory
28
26
2
-1
-6
-7
-10 -14
Net Reqs
1
5
1
3
4
Planned Orders
14
50
Component B (Leadtime = 4 weeks, Order Interval = 5 weeks)
Week
0
1
2
3
4
5
6
7
Gross Reqs
14
50
Sched Receipts
14
Proj Inventory
2
2
2
2
2
2
-48
Net Reqs
48
Planned Orders
48
8
50
-64
50
8
Note: we are using FOP lot-sizing rule.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Nervousness Example (cont.)
Item A (Leadtime = 2 weeks, Order Interval = 5 weeks)
Week
0
1
2
3
4
5
6
7
8
Gross Reqs
2
23
3
5
1
3
4
50
Sched Receipts
Proj Inventory
28
26
3
0
-5
-6
-9
-13 -63
Net Reqs
5
1
3
4
50
Planned Orders
63
Component B (Leadtime = 4 weeks, Order Interval = 5 weeks)
Week
0
1
2
3
4
5
6
7
8
Gross Reqs
63
Sched Receipts
14
Proj Inventory
2
16 -47
Net Reqs
47
Planned Orders 47*
* Past Due
Note: Small reduction in requirements caused large change in orders and
made schedule infeasible.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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15
Reducing Nervousness
Reduce Causes of Plan Changes:
• Stabilize MPS (e.g., frozen zones and time fences)
• Reduce unplanned demands by incorporating spare parts forecasts into
gross requirements
• Use discipline in following MRP plan for releases
• Control changes in safety stocks or leadtimes
Alter Lot-Sizing Procedures:
• Fixed order quantities at top level
• Lot for lot at intermediate levels
• Fixed order intervals at bottom level
Use Firm Planned Orders:
• Planned orders that do not automatically change when conditions change
• Managerial action required to change a FPO
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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31
Handling Change
•
•
•
•
New order in MPS
Order completed late
Scrap loss
Engineering changes in BOM
Regenerative MRP: completely re-do MRP calculations starting with MPS and
exploding through BOMs.
Net Change MRP: store material requirements plan and alter only those parts
affected by change (continuously on-line or batched daily).
Comparison:
– Regenerative fixes errors.
– Net change responds faster to changes (but must be regenerated
occasionally for accuracy.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Rescheduling
Top Down Planning: use MRP system with changes (e.g., altered MPS or
scheduled receipts) to recompute plan
• can lead to infeasibilities (exception codes)
• Orlicky suggested using minimum leadtimes
• bottom line is that MPS may be infeasible
Bottom Up Replanning: use pegging and firm planned orders to guide
rescheduling process
• pegging allows tracing of release to sources in MPS
• FPO’s allow fixing of releases necessary for firm customer orders
• compressed leadtimes (expediting) are often used to justify using FPO’s to
override system leadtimes
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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33
Safety Stocks and Safety Leadtimes
Safety Stocks:
– generate net requirements to ensure min level of inventory at all times
– used as hedge against quantity uncertainties (e.g., yield loss)
Safety Leadtimes:
– inflate production leadtimes in part record
– used as hedge against time uncertainty (e.g., delivery delays)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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34
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Safety Stock Example
Item: Screws (Leadtime = 1 week)
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
1
2
400
500
100
3
4
200
5
800
6
100
-100
120
800
-900
800
-
120
Note: safety stock level is 20.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
35
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Safety Stock vs. Safety Leadtime
Item: A (Leadtime = 2 weeks, Order Quantity =50)
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
0
1
20
40
20
2
40
50
30
3
20
4
0
5
30
10
10
-20
20
3
20
4
0
5
30
10
10
10
-20
30
50
Safety Stock = 20 units
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
0
1
20
40
20
2
40
50
30
50
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18
Safety Stock vs. Safety Leadtime (cont.)
Safety Leadtime = 1 week
Week
Gross Reqs
Sched Receipts
Proj Inventory
Net Reqs
Planned Orders
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
0
1
20
40
20
2
40
50
30
3
20
4
0
5
30
10
10
-20
20
50
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Manufacturing Resource Planning (MRP II)
• Sometime called MRP, in contrast with mrp (“little” mrp); more recent
implementations are called ERP (Enterprise Resource Planning).
• Extended MRP into:
– Master Production Scheduling (MPS)
– Rough Cut Capacity Planning (RCCP)
– Capacity Requirements Planning (CRP)
– Production Activity Control (PAC)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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38
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MRP II Planning Hierarchy
Demand
Forecast
Resource
Planning
Ag gregate Production
Planning
Rough-cut Capacity
Planning
Master Production
Scheduling
Bills of
Material
Inventory
Status
Material Requirements
Planning
Job
Pool
Capacity Requirements
Planning
Job
Release
Routing
Data
Job
Dispatching
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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39
Master Production Scheduling (MPS)
• MPS drives MRP
• Should be accurate in near term (firm orders)
• May be inaccurate in long term (forecasts)
• Software supports
– forecasting
– order entry
– netting against inventory
• Frequently establishes a “frozen zone” in MPS
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40
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Rough Cut Capacity Planning (RCCP)
• Quick check on capacity of key resources
• Use Bill of Resource (BOR) for each item in MPS
• Generates usage of resources by exploding MPS against BOR (offset by
leadtimes)
• Infeasibilities addressed by altering MPS or adding capacity (e.g.,
overtime)
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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41
Capacity Requirements Planning (CRP)
• Uses routing data (work centers and times) for all items
• Explodes orders against routing information
• Generates usage profile of all work centers
• Identifies overload conditions
• More detailed than RCCP
• No provision for fixing problems
• Leadtimes remain fixed despite queueing
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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Production Activity Control (PAC)
• Sometimes called “shop floor control”
• Provides routing/standard time information
• Sets planned start times
• Can be used for prioritizing/expediting
• Can perform input-output control (compare planned with actual
throughput)
• Modern term is MES (Manufacturing Execution System), which
represents functions between Planning and Control.
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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43
Conclusions
Insight: distinction between independent and dependent demands
Advantages:
• General approach
• Supports planning hierarchy (MRP II)
Problems:
• Assumptions --- especially infinite capacity
• Cultural factors --- e.g., data accuracy, training, etc.
• Focus --- authority delegated to computer
© Wallace J. Hopp, Mark L. Spearman, 1996, 2000
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