5161_session 3 master production scheduling

8/7/2019 5161_SESSION 3 MASTER PRODUCTION SCHEDULING

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OM II

MASTER SCHEDULING

PROCESS


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AGREGATE PLAN

Match seasonal demand with capacity by

- Inventory

- Employment level , OT

- Outsourcing Minimize cost

Manage demand

Manage capacity ( peak demand, chase

demand, level production , hybrid Implications : Cost, capacity utilization,

Customer satisfaction,


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Short-range plans (Detailed plans)

Machine loading

Job assignments

Intermediate plans (General levels) Employment

Output

Long-range plans Long term capacity

Location / layout

Overview of Planning Levels


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MASTER SCHEDULING

Each product : Planned

- Quantity

- Timing- Delivery

Disaggregation


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DISAGGREGATION

Jan 2000 L

W O B

Jan : 1 L 100 50 1500.5 L 200 100 400

0.2 L 200 300 500

Change of units


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Master Scheduling Process

MasterScheduling

Beginning inventory

Forecast

Customer orders

Inputs Outputs

Projected inventory

Master production schedule

Uncommitted inventory

(Available- to promise)


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Projected OnProjected On--hand Inventoryhand Inventory

64 1 2 3 4 5 6 7 8

Forecast 30 30 30 30 40 40 40 40

Customer Orders(committed) 33 20 10 4 2

Projected on-hand

inventory 31 1 -29

JUNE JULY

Beginning

Inventory

Customer orders are

larger than forecast in

week 1

Forecast is larger than

Customer orders in week 2

Forecast is larger than

Customer orders in week 3


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MPS

64 1 2 3 4 5 6 7 8

Forecast

P j

6

MPS 7 7 7 7

7 79 7

JUNE JULY


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Time Fences in MPSTime Fences in MPS

Period

frozen

(firm or

fixed)

slushy

somewhat

firm

liquid

(open)

1 2 3 4 5 8


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OBJECTIVES

Meet due dates

Minimize lead time (P or D)

Minimize setup time Minimize WIP

Maximize resource utilization


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Priority Rules for Job Sequencing

1. First-come, first-served (FCFS)

2. Shortest operating time (SOT)

3. Earliest due date first (DDate)

4. Slack time remaining (STR) first

5. Slack time remaining per operation

(STR/OP)


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OBJECTIVE FUNCTIONS

Mean flow time

Mean Tardiness

Maximum Tardiness

Total no of tardy obs


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EXAMPLE

P


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SPT

JOB p d C F T

3 2 19 2 2 01 4 6 6 6 0

2 7 9 13 13 4

4 8 17 21 21 4


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DD

JOB p d C F T

1 4 6 4 4 0

2 7 9 11 11 2

4 8 17 19 19 2

3 2 19 21 21 2


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MOORE

JOB p d C F T

1 4 6 4 4 04 8 17 12 12 0

3 2 19 14 14 0

2 7 9 21 21 12


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EXAMPLE FLOW SHOP

JOBS p on m/c 1 p on m/c 2

1 4 7

2 6 3

3 2 3

4 7 7

5 8 6


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EXAMPLE FLOW SHOP

M/c 1 M/c 2 TIME

1

2

JOB 1 3

4

5

6

7

JOB 2 JOB 1 8

9

10

JOB 3 11

12

JOB 2 13

14

15

JOB 4 JOB 3 16

17

18

19

20

21

22

JOB 4 23

JOB 5 24

25

26

27

28

JOB 5 29

30

31

32

33

34

35


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JOHNSONS PROCEDURE

M/c 1 M/c 2 ME M/c 1 M/c 21 JO 32

JO 1 3

5 JO 16

JO 2 JO 1 8

9

10 JO 4 JO 1JO 3 11

12

JO 2 13

14

15

JO 4 JO 3 16

17 JO 4

18 JO 5

19

2021

22

JO 4 23

JO 5 24 JO 5

25 JO 2

26

27

28

JO 5 29 JO 2

30

31

32

33

34


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GENERAL JOB SHOP

JOB d

A B C A B C1 3 3 2 10

2 5 2 13

3 4 4 3 12

4 3 5 2 18

5 5 4 14

6 2 5 5 15

p FOR M/C'S


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INDEPENDENT EPQ

SCHEDULING

Product

no.

Annual

Requirement

R

Sales per

day(250

days a

year) p

Days reqd to

meet

requirement

Inventory

cost

Rs/year/unit

Set up

cost

Rs EPQ

No of

runs/year

Days per

lot

1 9000 36 225 40 0.1 40 2928 3.1 13.0

2 20000 80 500 40 0.2 25 2440 8.2 4.9

3 6000 24 200 30 0.15 50 2132 2.8 10.7

4 12000 48 600 20 0.1 40 3230 3.7 5.45 16000 64 500 32 0.02 50 9578 1.7 19.2

6 15000 60 500 30 0.5 40 1651 9.1 3.3

7 8000 32 1000 8 0.35 30 1190 6.7 1.2

8 9000 36 900 10 0.05 60 4743 1.9 5.3

9 2000 8 125 16 0.55 25 441 4.5 3.5

10 3000 12 200 15 0.2 20 799 3.8 4.0

241 380 4.5 70.4


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SCHEDULING INTERFERENCE

Productno. Days per lot Max Inventory

No of

days to

depletemax inv

1 13.0 2459 68

2 4.9 2049 26 Stock out

3 10.7 1876 78

4 5.4 2972 62 Stock out

5 19.2 8352 1316 3.3 1453 24 Stock out

7 1.2 1152 36 Stock out

8 5.3 4554 126

9 3.5 413 52 Stock out


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COMMON CYCLE SCHEDULING

(4 Cycles/Year )

Produc

no a s per o Max n en or

No o

da s o

dep e e

ax n

1 10 0 1890 53

2 10 0 4200 53

3 7 5 1320 55

4 5 0 2760 58

5 8 0 3488 55

6 7 5 3300 55

7 2 0 1936 61

8 2 5 2160 60

9 4 0 468 59

10 3 8 705 59

O L 60 3


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COMMON CYCLE SCHEDULING

(5 Cycles/Year )

Product

no. Days per lot Max Inventory

No of

days to

deplete

max inv

1 8.0 1512 42

2 8.0 3360 423 6.0 1056 44

4 4.0 2208 46

5 6.4 2790 44

6 6.0 2640 44

7 1.6 1549 48

8 2.0 1728 48

9 3.2 374 4710 3.0 564 47

TOTAL 48.2


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Waiting Lines in Service

Operations Irregular or random demand

Service times vary amongcustomers.

Managers try to strike a balance between

efficiently utilizing resources and keeping

customer waiting.


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WAITING LINE ANALYSIS

How many servers to use

Likelihood a customer will have to wait Average time a customer will wait

Average number of customers waiting

Waiting line space needed

Percentage of time all servers are idle


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Waiting Line Examples

Computer printing obs waiting for printing

Workers waiting to punch a time clock

Customers in line at ATM Trucks are waiting to be unloaded

Patients waiting at a path lab

Airplanes waiting to take off


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TERMINOLOGY

Queue - a waiting line

Channels - number of waiting lines in a

queuing system Service phases number of steps in

service process

Arrival rate (P) - rate at which persons orthings arrive (in arrivals per unit of time)

Service rate (Q) - rate that arrivals are

serviced (in arrivals per unit of time)


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TERMINOLOGY

Queue discipline - rule that determines the

order in which arrivals are serviced

Queue length number of arrivals waitingfor service

Time in system an arrivals waiting time

and service time

Utilization degree to which any part of

the service system is occupied by an

arrival


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Queuing System Structures

Single Phase - Single Channel

Single Phase - Multichannel

SS11

SS11

SS22

SS33


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Queuing System Structures

Multiphase - Single Channel

Multiphase - Multichannel

SS1212SS1111

SS1212SS1111

SS2222

SS2121

SS3232SS3131


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WAITI G LI E STRUCTURES

Single Channel

Multichannel

Single

PhaseMultiphase

One-person

barber shopCar wash

Hospital

admissions

Bank tellers

windows


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QUEUING SYSTEM

VARIABLESP = average arrival rate1/P = average time between arrivals

= average service rate for each server

1/ = average service timen1 = average number of arrivals waiting

nS = average number of arrivals in the system

t1 = average time arrivals wait

tS = average time arrivals are in the system

Pn = probability of exactly n arrivals in thesystem


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Independent and Dependent

DemandIndependent Demand

A

B(4) C(2)

D(2) E(1) D(3) F(2)

Dependent Demand

Independent demand is uncertain.

Dependent demand is certain.


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MRP

M R PR

M R

R R MP

R

M

PR R R

M R

PR

R R R

P R

R R

R R P R


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PRODUCT STRUCTURE

HIERARCHY

C O P O E T E E

A

S

R


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PRODUCT STRUCTURE

SSE ED

SSE ED

C

PURC SED

D

SSE ED

E

SSE ED

PURC SED

SSE ED

PURC SED

PRODUCED

PRODUCED

K

PURC SED

PRODUCED

PRODUCED


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PROCESS CHART

PART ( ) PART ( )

PERATI N

C P 1( 3 ) PERATI N 2

PURCHA ED

COMP 2( 1 ) OPERATION 2

PURCHA ED


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OUT PUT

OMPO T

QU T T Q O

U T T T

TOT QU T T

Q

G

G

5161_session 3 master production scheduling

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