Lecture05 MRP Indu6211

8/10/2019 Lecture05 MRP Indu6211

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Materials Requirement Planning (MRP)


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History

Begun around 1960 as computerized approach to purchasing and

production scheduling.

Joseph Orlicky, Oliver Wight, and others.

APICS launched MRP Crusade in 1972 to promote MRP.


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Key Insight

Independent Demandfinished products

Dependent Demandcomponents

It makes no sense to independently forecast dependent demands.


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Assumptions

1. Known deterministic demands.

2. Fixed, known production leadtimes.

3. Infinite capacity.

Idea is to back out demand for components by using leadtimes

and bills of material.


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Terminology

Level Code:lowest level on any BOM on which part is found

Planning Horizon:should be longer than longest cumulativeleadtime for any product

Time Bucket:units planning horizon is divided into

Lot-for-Lot:batch sizes equal demands (other lot sizingtechniques, 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.


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Schematic of MRP

Item Master(BOM)

On-handinventory

Scheduledreceipts

MasterProduction

schedule

MRP:

Netting

Lot sizing

Offsetting

BOM exploding

Planned

order

releases

Change

notices

Exception

notices


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MRP Procedure

1. Netting: net requirements against projected inventory

2. Lot Sizing: planned order quantities

3. Time Phasing: planned orders backed out by leadtime

4. BOM Explosion: gross requirements for components


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MRP Procedure

Dt = gross requirements (demand) for period t St = quantity currently scheduled to complete in

period t (a scheduled receipt)

It = projected on-hand inventory for end of period t,

where current onhand-inventory is given by I0 Nt = net requirements for period t


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Inputs

Master Production Schedule (MPS): due dates and quantities for

all top level items

Bills of Material (BOM): for all parent items

Inventory Status: (on hand plus scheduled receipts) for all items

Planned Leadtimes: for all items


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Example BOM

300 500

100

300 400

600

BA

100

(2 req) 200

400300


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Example

Part A

Gross requirements 15 20 50 10 30 30 30 30

1 2 3 4 5 6 7 8

Part A 1 2 3 4 5 6 7 8


Projected on-hand (at the end of

period)30 15 -5 __ __ __ __ __ __

Net requirements 0 5 50 10 30 30 30 30

Inventory on hand It=It-1-Dt+St

NettingNt=min{max(-It, 0), Dt)


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Example (cont.)

Part A 1 2 3 4 5 6 7 8


Projected on-hand 30 15 -5 __ __ __ __ __ __


Part A 1 2 3 4 5 6 7 8




Planned order receipts 75 75 75


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Example cont.

Part A 1 2 3 4 5 6 7 8





Planned order releases 75 75 75


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MRP Procedure

Part A 1 2 3 4 5 6 7 8


Scheduled receipts 10 10 100

Adjusted SRs

Projected on-hand 20

Net requirements

Planned order receipts

Planned order releases

Part A 1 2 3 4 5 6 7 8



Adjusted SRs 20 100

Projected on-hand20 5 5 55 45 15 -15 __ __

Net requirements 15 30 30


Planned order releases


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Part A Final

Part A 1 2 3 4 5 6 7 8



Adjusted SRs20 100

Projected on-hand20 5 5 55 45 15 -15 __ __

Net requirements 15 30 30

Planned order receipts 45 30

Planned order releases 45 30


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Part B

t 1 2 3 4 5 6 7 8

Demand 10 15 10 20 20 15 15 15

Part

Number

Current

On-Hand

SRs Lot-Sizing

Rule Lead TimeDue Quantity

B 40 0 FOP, 2 weeks 2 weeks

100 40 0 Lot-for-lot 2 weeks

300 50 2 100Lot-for-lot

1 week

500 40 0Lot-for-lot

4 weeks


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MRP Processing for Part B

Part B 1 2 3 4 5 6 7 8


Scheduled receipts

Adjusted SRs

Projected on-hand40 30 15 5 -15 __ __ __ __

Net requirements 15 20 15 15 15




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Part 500

Part 500 1 2 3 4 5 6 7 8

Gross requirements 35 30 15

Scheduled receipts

Adjusted SRs

Projected on-hand

40 40 5 5 -25 __ __ __ __

Net requirements 25 15


Planned order releases 25* 15


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Part 100

Part 100 1 2 3 4 5 6

Required from A 90 60

Required from 500 25 15

Gross requirements 25 15 90 60

Scheduled receipts

Adjusted SRs

Projected on-hand40 15 0 0 -90 __ __





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Part 300

Part 300 1 2 3 4 5 6 7 8

Required from B 35 30 15

Required from 100 90 60

Gross requirements 125 90 15

Scheduled receipts 100

Adjusted SRs 100

Projected on-hand 50 50 25 25 -65 __ __ __ __





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MRP Summary

Transaction Part

Number

Old Due Date

or Release Date

New Due Date Quantity Notice

Change Notice

Change Notice

Planned order release











A

A

A

A

B

B

B

100

100

300

300

500

500

1

4

4

6

2

4

6

2

4

3

5

1

2

2

3

6

8

4

6

8

4

6

4

6

4

6

10

100

45

30

35

30

15

90

60

65

15

25

15

Defer

Expedite

OK

OK

OK

OK

OK

OK

OK

OK

OK

Late

OK


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Terminology

Level Code:lowest level on any BOM on which part is found

Planning Horizon:should be longer than longest cumulativeleadtime for any product

Time Bucket:units planning horizon is divided into

Lot-for-Lot:batch sizes equal demands (other lot sizingtechniques, 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) thatgenerated it. Single usually used because full is difficult due to

lot-sizing, yield loss, safety stocks, etc.


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Special Topics

Firm Planned Orders (FPOs):planned order that theMRP system does notautomatically change when conditions

changecan stabilize system

Service Parts:parts used in service and maintenancemust

be included in gross requirements

Order Launching:process of releasing orders to shop orvendorsmay 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.)


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Lot Sizing in MRP

Lot-for-lotchase demand

Fixed order quantity methodconstant lot sizes

EOQusing average demand

Fixed order period methoduse constant lot intervals

Part period balancingtry to make setup/ordering cost equal to

holding cost

Wagner-Whitinoptimal method


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Fixed Ordering Quantity



30 60 65 55 45


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Fixed Order Period

Period 1 2 3 4 5 6 7 8 9

Net requirements15 45 25 15 20 15

Planned order receipts60 60 15


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Part-Period Balancing

Quantity for

Period 2

Setup Cost ($) Part-PeriodsInventory

Carrying Cost ($)

15 150 0 0

60 150 45 x 1 = 45 90

85 150 45 + 25 x 4 = 145 290

Quantity for

Period 6Setup Cost ($) Part-Periods

Inventory

Carrying Cost ($)

25 150 0 0

40 150 15 x 1 = 15 30

60 150 15 + 20 x 2 = 55 110

75 150 55 + 15 x 3 = 100 200


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The Wagner-WhitinModel

Dynamic Lot Sizing


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EOQ Assumptions

1. Instantaneous production.

2. Immediate delivery.

3. Deterministic demand.

4. Constant demand.

5. Known fixed setup costs.

6. Single product or separable products.

WW model relaxes this one


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Dynamic Lot Sizing Notation

t a period (e.g., day, week, month); we will consider t = 1, ,T,

where Trepresents theplanning horizon.

Dt demand in period t(in units)

ct unit production cost (in dollars per unit), not counting setup or

inventory costs in period t

At fixed or setup cost (in dollars) to place an order in period t

ht holding cost (in dollars) to carry a unit of inventory from period tto period t +1

Qt the unknownsize of the order or lot size in period t decision var iables


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Wagner-Whitin Example

Data

Lot-for-Lot Solution

t 1 2 3 4 5 6 7 8 9 10

Dt 20 50 10 50 50 10 20 40 20 30

ct 10 10 10 10 10 10 10 10 10 10

At 100 100 100 100 100 100 100 100 100 100

ht 1 1 1 1 1 1 1 1 1 1

t 1 2 3 4 5 6 7 8 9 10 Total

Dt 20 50 10 50 50 10 20 40 20 30 300

Qt 20 50 10 50 50 10 20 40 20 30 300It 0 0 0 0 0 0 0 0 0 0 0

Setup cost 100 100 100 100 100 100 100 100 100 100 1000

Holding cost 0 0 0 0 0 0 0 0 0 0 0

Total cost 100 100 100 100 100 100 100 100 100 100 1000


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Wagner-Whitin Example (cont.)

Fixed Order Quantity Solution

t 1 2 3 4 5 6 7 8 9 10 Total

Dt 20 50 10 50 50 10 20 40 20 30 300

Qt 100 0 0 100 0 0 100 0 0 0 300

It 80 30 20 70 20 10 90 50 30 0 0

Setup cost 100 0 0 100 0 0 100 0 0 0 300

Holding cost 80 30 20 70 20 10 90 50 30 0 400

Total cost 180 30 20 170 20 10 190 50 30 0 700


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Wagner-Whitin Property

Under an optimal lot-sizing policy either the inventory

carried to period t+1 from a previous period will be zero or

the production quantity in period t+1 will be zero.


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Basic Idea of Wagner-Whitin Algorithm

By WW Property I, either Qt=0or Qt=D1++Dkfor some k. If

jk*= last period of production in a kperiod

problem

then we will produce exactlyDk+DTin periodjk*.

We can then consider periods 1, , jk*-1as if they are an

independentjk*-1period problem.


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Wagner-Whitin Example

Step 1: Obviously, just satisfyD1(note we are neglectingproduction cost, since it is fixed).

Step 2: Two choices, eitherj2* = 1 orj2

*= 2.

1

100

*

1

1

*

1

j

AZ

1

150

200100100

150)50(1100

min

2inproduce,Z

1inproduce,min

*

2

2

*

1

211*

2

j

A

DhAZ


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Step3: Three choices,j3* = 1, 2, 3.

1

170

250100150

21010)1(100100

17010)11()50(1100

min

3inproduce,Z

2inproduce,Z

1inproduce,)(

min

*

3

3*2

322

*

1

321211*

3

j

A

DhA

DhhDhA

Z


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Step 4: Four choices,j4* = 1, 2, 3, 4.

4

270

270100170

30050)1(100150

31050)11(10)1(100100

32050)111(10)11()50(1100

min

4inproduce,Z

3inproduce,Z

2inproduce,)(Z

1inproduce,)()(

min

*

4

4

*

3

433

*

2

432322

*

1

4321321211

*

4

j

A

DhA

DhhDhA

DhhhDhhDhA

Z


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Planning Horizon Property

If jt*=t, then the last period in which production occurs in an

optimal t+1 period policy must be in the set t, t+1,t+1.

In the Example:

We produce in period 4 for period 4 of a 4 periodproblem.

We would never produce in period 3 for period 5 in a 5

period problem.


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Step 5: Only two choices,j5* = 4, 5.

Step 6: Three choices,j6*

= 4, 5, 6.

And so on.

4

320

370100270

320)50(1100170min

5inproduce,Z

4inproduce,min

*

5

5

*

4

544

*

3*

5

j

A

DhAZZ


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Wagner-Whitin Example Solution

Planning Horizon (t)Last Periodwith Production 1 2 3 4 5 6 7 8 9 10

1 100 150 170 320

2 200 210 310

3 250 300

4 270 320 340 400 5605 370 380 420 540

6 420 440 520

7 440 480 520 610

8 500 520 580

9 580 610

10 620Zt 100 150 170 270 320 340 400 480 520 580

jt 1 1 1 4 4 4 4 7 7 or 8 8

Produce in period 8

for 8, 9, 10 (40 + 20

+ 30 = 90 units

Produce in period 4

for 4, 5, 6, 7 (50 + 50

+ 10 + 20 = 130

units)

Produce in period 1

for 1, 2, 3 (20 + 50 +

10 = 80 units)


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Wagner-Whitin Example Solution (cont.)

Optimal Policy:

Produce in period 8 for 8, 9, 10 (40 + 20 + 30 = 90units)

Produce in period 4 for 4, 5, 6, 7 (50 + 50 + 10 + 20 =

130 units)

Produce in period 1 for 1, 2, 3 (20 + 50 + 10 = 80 units)t 1 2 3 4 5 6 7 8 9 10 Total

Dt 20 50 10 50 50 10 20 40 20 30 300

Qt 80 0 0 130 0 0 0 90 0 0 300

It 60 10 0 80 30 20 0 50 30 0 0

Setup cost 100 0 0 100 0 0 0 100 0 0 300Holding cost 60 10 0 80 30 20 0 50 30 0 280

Total cost 160 10 0 180 30 20 0 150 30 0 580


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Problems with Wagner-Whitin

1. Fixed setup costs.

2. Deterministic demand and production (no uncertainty)

3. Never produce when there is inventory (WW Property

I).

safety stock (don't let inventory fall to zero)

random yields (can't produce for exact no. periods)


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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)


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Safety Stock and Safety Lead Times

Part B 1 2 3 4 5 6 7 8


Scheduled receipts

Adjusted SRs

Projected on-hand 40 30 15 5 __ __ __ __ __

Projected on-hand - SS 30 20 5 -5 __ __ __ __ __

Net requirements 5 20 20 15 15 15




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Lead Times

Part B 1 2 3 4 5 6 7 8


Scheduled receipts

Adjusted SRs

Projected on-hand 40 30 15 5 -15 __ __ __ __

Net requirements 15 20 15 15 15


Adjusted planned order receipts 35 30 15



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Problems with MRP

1. Capacity infeasibility

2. Long planned lead times

3. System nervousness


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Nervousness

Small change in master production schedule results inlarge change in planned orders

Note: we are using FOP lot-sizing rule.

Item A (Leadtime = 2 weeks, Order Interval = 5 weeks)

Week 0 1 2 3 4 5 6 7 8

Gross Reqs 2 24 3 5 1 3 4 50

Sched Receipts

Proj Inventory 28 26 2 -1 -6 -7 -10 -14 -64Net Reqs 1 5 1 3 4 50

Planned Orders 14 50

Component B (Leadtime = 4 weeks, Order Interval = 5 weeks)

Week 0 1 2 3 4 5 6 7 8

Gross Reqs 14 50Sched Receipts 14

Proj Inventory 2 2 2 2 2 2 -48

Net Reqs 48

Planned Orders 48


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Nervousness Example (cont.)

* Past Due

Note:Small reduction in requirements caused largechange in orders and made schedule infeasible.

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 63Component 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 47Planned Orders 47*


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Nervousness Example (cont.)

Note:Small reduction in requi rements caused large change inorders and made schedule infeasible.

Component B 1 2 3 4 5 6 7 8

Gross requirements 63


Adjusted SRs 14



Planned order receipts 47

Planned order releases 47*

* Indicates a late start


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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 conditionschange

Managerial action required to change a FPO


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Item A 1 2 3 4 5 6 7 8


Scheduled receipts

Firm planned orders 14

Projected on-hand 28 26 3 14 9 8 5 1 -49

Net requirements 49

Planned order receipts [14] 49

Planned order releases [14] 49

TABLE 3.15, Firm Planned Orders


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Component B 1 2 3 4 5 6 7 8

Gross requirements 14 49


Adjusted SRs

Projected on-hand 2 2 2 2 2 2 -47 __ __

Net requirements 47

Planned order receipts 47

Planned order releases 47

TABLE 3.16

H dli Ch


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Handling Change

Causes of Change:

New order in MPS

Order completed late

Scrap loss

Engineering changes in BOM

Responses to Change: Regenerati ve 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 but must be regenerated periodically.

R h d li


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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 plannedorders to guide rescheduling process

pegging allows tracing of release to sources in MPS

FPOs allow fixing of releases necessary for firm customer orders compressed leadtimes (expediting) are often used to justify using

FPOs to override system leadtimes

M f t i R Pl i (MRP II)


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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 ResourcePlanning).

Extended MRP into:

Master Production Scheduling (MPS)

Rough Cut Capacity Planning (RCCP)

Capacity Requirements Planning (CRP)

Short Term Control

MRP II Pl i Hi h


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MRP II Planning Hierarchy

Aggregate

Production

planning

Resource

planning

Master

Production

scheduling

Material

requirements

planning

Jobpool

Job

release

Job

dispatchingI/O control

Long-term

forecast

Rough-cut

capacity

planning

Bills of

material

On-hand &

Scheduled

receipts

Firm

orders

Short-term

forecast

Demand

management

Capacity

requirementsplanning

Routing

data

Long-range

planning

Intermediate-range

planning

Short-term

control

L R Pl i


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Long Range Planning

Time horizon 6 months to 5 years

Forecasting

Long range forecast for part families

Short term forecasts of individual items

Resource planning

Available capacity over the long term Decisions to expand

Aggregate planning

levels of production, staffing, inventory

I t di t L l


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Intermediate Level

Production planning functions

Master Production Scheduling

Rough-cut Capacity Planning

Capacity Requirements Planning

M t P d ti S h d li (MPS)


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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

R h C t C it Pl i (RCCP)


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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)

RCCP


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RCCP

Week 1 2 3 4 5 6 7 8

Part A 10 10 10 20 20 20 20 10

Part B 5 25 5 15 10 25 15 10

Process

CenterPart A Part B

21 2.5 2.0

Week 1 2 3 4 5 6 7 8

Part A (hour) 25 25 25 50 50 50 50 25

Part B (hour) 10 50 10 30 20 50 30 10

Total (hour) 35 75 35 80 70 100 80 35

Available 65 65 65 65 65 65 65 65

Over (+)/under(-) 30 -10 30 -15 -5 -35 -15 30



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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

CRP load profile


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0

100

200

300

400

500

1 2 3 4 5 6 7 8

Days

CRP load profile

Load

Day 1 2 3 4 5

Planned order releases 300 350 400 350 300

Day 1 2 3 4 5

Planned order releases 1,200 0 0 1,200 0

Short Term Control / Shop Floor control


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Short Term Control / Shop Floor control

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.

Short Term Control cont


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Short Term Control cont.

Job Dispatching

Shortest processing time, earliest due date etc..

I/O Control

WIP levels

Kanban vs. MRP

Enterprise Resources Planning


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Enterprise Resources Planning

MRP MRP II

SCM

BPR

ERP

IT

Goal: link information

across entire enterprise:manufacturing

distribution

accounting

financial

personnel

Integrated ERP Approach


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Integrated ERP Approach

Advantages:

integrated functionality

consistent user interfaces

integrated database

single vendor and contract

unified architecture

unified product support

Disadvantages:

incompatibility with existing systems

long and expensive implementation

incompatibility with existing

management practices

loss of flexibility to use tactical point

systems

long product development and

implementation cycles long payback period

lack of technological innovation

Other Planning Tools


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Other Planning Tools

Manufacturing Execution Systems (MES):

automated implementation of shop floor control

data tracking (WIP, yield, quality, etc.)

merging with ERP?

Advanced Planning Systems (APS):

algorithms for performing specific functions

finite capacity scheduling, forecasting, available to promise,

demand management, warehouse management, distribution, etc.

partnerships between developers and ERP vendors

Conclusions


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Conclusions

Insight: distinction between independent and dependent

demands

Advantages:

General approach

Supports planning hierarchy (MRP II, ERP)

Problems:

Assumptionsespecially infinite capacity

Cultural factorse.g., data accuracy, training, etc. Focusauthority delegated to computer

Lecture05 MRP Indu6211

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